Shaping the sea ice: how ocean and atmosphere drive the patterns of wintertime Arctic sea ice leads
Sascha Willmes, Günther Heinemann, Frank Schnaase
Corresponding author: Sascha Willmes
Corresponding author e-mail: willmes@uni-trier.de
Based on a novel sea-ice lead climatology for the Arctic derived from thermal-infrared satellite imagery we highlight prominent patterns of wintertime sea-ice dynamics and identify their responsible drivers in the ocean and atmosphere. We find that the overall spatial patterns in lead occurrences show a significant signature of ocean bathymetry, associated surface currents, and ocean eddy kinetic energies. Especially over the shelf and at water depths above 500 meters, ocean floor topography seems to prime the stability of the overlying sea ice significantly through surface current gradients, energy transport and potentially also tides. In the temporal domain of the Arctic wintertime sea-ice lead variability we find the divergence of the wind field to have the largest impact on the question of where and when the sea ice becomes prone to weakening and break-up. Implications for sea ice–ocean–atmosphere interactions in general, for sea-ice modelling and for future sea-ice changes are discussed.
Large scale climate modes as drivers of low-frequency regional Arctic sea ice variability
Christopher Wyburn-Powell, Alexandra Jahn
Corresponding author: Christopher Wyburn-Powell
Corresponding author e-mail: chwy8767@colorado.edu
Arctic sea ice has been declining precipitously during the observational record but with large variability on short and medium time scales. Approximately two-thirds of internal variability is accounted for by interannual variability, which is largely unpredictable at lead times in excess of one year. The remaining one-third is due to low-frequency variability, which may be partially predictable. In our analysis using climate model output, up to 40% of this low frequency variability in certain parts of the Arctic can be explained by large-scale modes of climate variability. The regions of the Arctic identified with the greatest predictability by modes of climate variability are the Chukchi Sea, East Siberian Sea and central Arctic in the autumn. Due to the low frequency nature and multitude of modes of climate variability, observational records are too short to clearly determine their influences on regional sea-ice concentration. We use 660 realizations forced by historical CMIP6 forcing from 58 global climate models. The many instances of climate mode phases are used to train machine learning algorithms against regional Arctic sea ice anomalies in the same realizations. We find the largest drivers of lower Arctic sea ice concentrations in the shelf seas in the autumn are a positive phase of the Atlantic Multidecadal Oscillation (AMO), Atlantic Nino (ATN), and El Niño Southern Oscillation (ENSO), and a negative phase of the Interdecadal Pacific Oscillation (IPO) and Pacific Decadal Oscillation (PDO).
Learning from local snow properties for large-scale Antarctic ice pack volume: The SNOWflake project
Stefanie Arndt, Helge Gößling, Christian Haas, Petra Heil, Stefan Hendricks, Frank Kauker, Joshua King, Glen Liston, Rob Massom, Dirk Notz, Ghislain Picard, Martin Schneebeli
Corresponding author: Stefanie Arndt
Corresponding author e-mail: stefanie.arndt@awi.de
Snow depth on sea ice is an essential climate variable, as it dominates the energy and momentum exchanges across the atmosphere–ice–ocean interfaces and actively contributes to the sea ice mass balance. Antarctic sea ice is characterized by a year-round snow cover preventing/delaying surface melt in summer, and amplifying sea ice growth through extensive snow-to-ice conversion processes. The lack of knowledge on both snow depth and its complex seasonal stratigraphy causes substantial uncertainties in large-scale data products from satellite remote sensing. Also, the accurate representation of small-scale snowpack processes in numerical climate models remains a major challenge, leading to critical uncertainties in estimates of the Antarctic sea ice energy and mass budgets. This poster presents the new Young Investigator Group SNOWflake project that will test the hypothesis that seasonal variations in snowpack properties on Antarctic sea ice are sensitive indicators of changing atmospheric forcing, as they could trigger snow–albedo feedbacks that accelerate sea ice melting and retreat. Climate warming may reverse the contribution of widespread snow-to-ice conversion processes to a positive Antarctic sea ice mass balance, and lead to increased surface melting, as currently prevalent for Arctic sea ice – with potential feedbacks for Earth’s climate. However, those feedbacks are not yet thoroughly investigated. Addressing this key gap, SNOWflAke will describe the temporal evolution of seasonal processes and properties of the Antarctic sea ice snowpack across all relevant spatial scales. The resulting improved snow parameterization will be linked to satellite remote sensing measurements in order to develop a novel and more accurate Antarctic sea ice thickness data product. Finally, the improved snow process formulations will be introduced into climate models to achieve an enhanced atmospheric sensitivity, and thus reduced uncertainties in sea ice forecasts and predictions for the Southern Ocean. These advances will then allow us to understand implications for the occurrence of characteristic Arctic snow processes, such as melt pond formation, on Antarctic sea ice, and vice versa, in order to draw appropriate conclusions on snow as an indicator and modulator of climate warming in the polar regions.
Relevance of inherent snow property variability for the large-scale Antarctic sea ice mass budget
Stefanie Arndt, Marcel Nicolaus, Christian Haas
Corresponding author: Stefanie Arndt
Corresponding author e-mail: stefanie.arndt@awi.de
Snow on sea ice alters the properties of the underlying ice cover as well as associated exchange processes at the interfaces between atmosphere, sea ice and ocean. As Antarctic snow cover persists during most of the year, it contributes significantly to the sea ice mass and energy budgets due to comprehensive physical (seasonal) transition processes within the snowpack. However, field studies reveal not only a strong seasonality but also spatial variations from local to regional scales. We therefore present here a comprehensive compilation of in-situ observations of physical snowpack properties obtained during numerous expeditions in the Weddell Sea since the 1990s, covering all seasons. Preliminary seasonal comparisons in the perennial ice of the northwestern Weddell Sea show high mean bulk densities up to 350 kg m–3 associated with high proportions of compacted wind slab and melt–freeze clusters in the lower snowpack in late summer and autumn. In contrast, high proportions of depth hoar crystals result in lower bulk densities below 300 kg m–3 in winter. On seasonal sea ice, however, mean bulk densities exceeding 400 kg m–3 were observed in summer due to high slush fractions that freeze to snow ice in late summer, reducing the bulk snow density back to values below 300 kg m–3. These regional and seasonal differences of the snow bulk density determine its effective heat conductivity in a non-linear relation. This ability of the snow to insulate the underlying Antarctic sea ice cover governs the thermodynamic ice growth. However, this unappreciated variability in snowpack properties results in significant uncertainties. Hence, large-scale data products from both satellites and numerical sea ice models can only inadequately represent sea ice mass budgets.
Snow depth vs snow accumulation in the Weddell Sea
Stefanie Arndt, Leonard Rossmann, Marcel Nicolaus
Corresponding author: Stefanie Arndt
Corresponding author e-mail: stefanie.arndt@awi.de
A year-round snow cover is a characteristic of Antarctic sea ice, which substantially impacts the sea ice energy and mass budgets, e.g. by preventing surface melt in summer and by amplifying sea ice growth through extensive snow ice formation. However, substantial observational gaps in the seasonal cycle of the Antarctic pack ice and its snow cover limit the understanding of important processes in the ice-covered Southern Ocean. They also cause huge uncertainties in satellite remote sensing applications and in climate studies. Here, we present results from 10 years of autonomous snow observations (by snow buoys) in the Weddell Sea. To differentiate between actual snow depth and potential snow ice thickness within the accumulated snowpack, a one-dimensional thermodynamic sea ice model is applied along the drift trajectories of the buoys. Snow accumulation data show highest accumulation rates of 8–10 cm per month between May and October, while significant snow melt is observed only in the summer months in the marginal ice zone. Over the entire year, 65 cm of snow accumulates in the northwestern Weddell Sea. These accumulation rates retrieved from the snow buoys as well as the surface temperature and heat fluxes from reanalysis data are used to force the thermodynamic model. Simulation results show a snow ice formation of up to 22 cm in this region. Thus, one-third of the snow pack consists of snow ice and only two-thirds (43 cm) remain as snow pack. Extending the work to the entire Weddell Sea and the whole observational period from 2013–23, these estimates will make an important contribution as a reference dataset for both snow depth and snow ice rates in the Southern Ocean.
Stefanie Arndt, Mario Hoppmann, Marcel Nicolaus, Mara Neudert, Markus Janout, Christian Haas
Corresponding author: Stefanie Arndt
Corresponding author e-mail: stefanie.arndt@awi.de
Landfast sea ice attached to the Antarctic coast is a critical element of the local physical and ecological systems. Through its direct coupling with the atmosphere and ocean, changes in fast ice and its snow cover are also potential manifestations of climate change. Since 2010, a monitoring program that is part of the Antarctic Fast Ice Network (AFIN) has been conducted on the seasonal fast ice of Atka Bay, located on the northern edge of the Ekström Ice Shelf in the eastern Weddell Sea. Here, we show results of regularly measured snow depth, freeboard, sea ice and sub-ice platelet layer thickness across the bay from 2010–22. On average, the fast ice thickness at the end of the growth season is about 2 m, with a platelet layer thickness of 4 m beneath. Due to the substantial snow accumulation on the sea ice, a characteristic feature is the frequent negative freeboard and associated flooding of the snow–ice interface. During the recent austral summer (November to December 2022), we complemented the regular monitoring program with intensified measurements of various ice and snow properties, which enable us to better understand the annual growth history of the regional fast ice cover. In particular, the additional analysis of conductivity–temperature–depth profiles obtained at several sampling sites across the bay, together with the seasonal pack ice evolution in front of the bay, provides us with a better picture of the platelet ice distribution in the study area. Our findings not only provide an important baseline for an exemplary Antarctic fast ice system that is expected to undergo drastic changes in the near future, but also highlight the need for intensified multidisciplinary studies in the coastal regions of Antarctica.
Biogeochemical regimes of sea ice microhabitats in the high Arctic
Karley Campbell, Benjamin Lange, Megan Lenss, Jack Landy, Pedro De La Torre, Geir Johnsen, Philipp Assmy, Rolf Gradinger, Janina Osanen, Sebastien Moreau, Rolf Gradinger
Corresponding author: Karley Campbell
Corresponding author e-mail: karley.l.campbell@uit.no
Accurate representations of ice algal activity and photophysiology within sea ice microhabitats are essential for understanding primary production in the Arctic, today and in the modelling of forecasted climate change scenarios. In this study we present data from the AO2022 high Arctic cruise aboard the Norwegian RV Kronprins Haakon, where the biogeochemical conditions and algal communities were characterized for contrasting sea ice microhabitats during the heavily under sampled summer season. Results highlight significant variability in community composition, acclimation state and productivity between bottom-ice, floating aggregate and ridge-keel microhabitats. Data support previous observations that aggregates and ridge communities represent biological hotspots in a system otherwise devoid of significant activity. This work also evaluates the biogeochemical conditions of the sea ice microhabitats, including nutrient and O2 states. The study represents an important step in accurately describing diversity and production regimes of high Arctic sea ice and is a contribution to the BREATHE (bottom–sea ice respiration and nutrient exchanges assessed for the Arctic) research project funded by the Norwegian Research Council.
Towards sea ice classification using combined Sentinel-1 and Sentinel-3 data
Stefan Wiehle, Anja Frost, Dimitri Murashkin, Martin Bathmann, Christine König, Thomas König
Corresponding author: Stefan Wiehle
Corresponding author e-mail: stefan.wiehle@dlr.de
In this contribution, a new machine learning approach is presented that is intended for the classification of sea ice using a combination of synthetic aperture radar (SAR) data from the Sentinel-1 satellites and an existing sea ice classification method for optical–thermal data from the Sentinel-3 satellites. Compared to a SAR-only classification, initial results show that the new approach improves the classification reliability especially in areas of open water. Sea ice is constantly changing: wind and ocean currents can push together large ice masses and close leads; the pack ice formed by these processes is often not navigable even by icebreakers. Remote sensing data reveal different structures within the ice for remote polar areas, and provide the basis for automatic sea ice classification in terms of its stage of development. In spaceborne Sentinel-1 SAR data, different ice classes can mostly be distinguished by different radar backscatter, but some ice classes exhibit a similar backscatter, limiting the applicability of radar-based classification. In Sentinel-3 SLSTR optical/thermal data, information of water, ice and snow allows a refined ice class separation after classification, but the observations are in lower spatial resolution and clouds may obstruct the view. Combining radar satellite measurements of Sentinel-1 and results of a sea ice classification using the optical/thermal measurements of the SLSTR instrument onboard the Sentinel-3 satellite offers the possibility to gain a deeper look into sea ice properties than just using one sensor. The fused classification presented here is based on a Convolutional Neural Network (CNN) classifier and discriminates 6 ice types. Its input data are the HH and HV polarization channels of the Sentinel-1 image plus pre-classified Sentinel-3 images with continuous RGB labels. Improved sea ice classification allows planning of safer routes and better awareness for possible dangerous situations for polar ships. This work was prepared in the scope of the project EisKlass2, funded by the German Federal Ministry for Digital and Transport’s mFUND programme under grant 19F2122A.
A comparison of Arctic Ocean sea ice export between Nares Strait and the Canadian Arctic Archipelago
Stephen Howell, David Babb, Jack Landy, Kent Moore, Benoit Montepetit, Mike Brady
Corresponding author: Stephen Howell
Corresponding author e-mail: stephen.howell@ec.gc.ca
Nares Strait and the channels of the Canadian Arctic Archipelago (CAA) act as conduits for sea ice outflow from the Arctic Ocean but have never been directly compared. Here, we perform such a comparison for both the sea ice area and volume fluxes from October 2016 to December 2021. Nares Strait provided the largest average seasonal (October through September) ice area flux of 95±8×103 km2 followed by the CAA regions of the Queen Elizabeth Islands (QEI) at 41±7×103 km2 and M’Clure Strait at 2±8×103 km2 with corresponding ice volume fluxes of 177±15 km3, 59±10 km3, and 8±8 km3, respectively. Larger Arctic Ocean ice outflow at Nares Strait was associated with a shorter ice arch duration (237 days) compared to M’Clure Strait (163 days) and QEI (65 days). Seasonal Arctic Ocean ice outflow was dominated by Nares Strait in 2017 to 2019 and 2021 but was remarkably exceeded by the QEI in 2020. Large-scale atmospheric circulation patterns were found to influence the ice area flux in the absence of ice arches but no occurrence of coherent Arctic Ocean ice outflow events coinciding across all gates were observed. Average net seasonal Arctic Ocean ice area and volume outflow were 138×103 km2 and 245 km3, which represent ~16% of the area and ~25% of the volume of sea ice outflow from Fram Strait. Divergent Arctic Ocean outflow ice trajectories are apparent for Nares Strait and the QEI when compared to Fram Strait.
Comparison of snow height buoy measurements with 1-D snow cover simulations in the Weddell Sea
Nina Maaß
Corresponding author: Nina Maaß
Corresponding author e-mail: nina.maass@uni-hamburg.de
In the Snow Covers impact on Antarctic Sea Ice (SCASI) project, we combine snow simulations on Antarctic sea ice with buoy observations and satellite data. The overall goal is to develop a new and consistent snow data product for Antarctic sea ice that quantifies amount, distribution and physical properties of snow on various length scales and different seasons. The product will be useful for sea ice and radiation models, altimetry-based ice thickness retrievals and other research that depends on information on snow on sea ice, e.g. regarding biological production or geochemical cycles. To achieve this goal, we compare snow depth simulated with the sea ice version of the 1-D snow cover model SNOWPACK (Wever et al., 2020) with snow buoy measurements in the Weddell Sea. The SNOWPACK simulations are initiated with the snow and ice thicknesses as measured when deploying the buoys and are run with meteorological ERA5 reanalysis data. We analysed 23 snow buoys drifting autonomously on sea ice for altogether ~5000 days. Here, we present how well precipitation (non-)events in ERA5 reanalysis data coincide with snow height as measured by the buoys. First, we identify days with low wind speeds and either low (a) or high (b) precipitation. We expect the buoy-observed snow heights on these days to show no changes (a) or positive changes (b), respectively. In only half of the cases (out of ~900 days), the expected snow height changes are observed by the buoys. Deviations can be caused by the uncertainty of the reanalysis data, the difficulties to interpret snow buoy data, and the very local scale of the buoy measurements (~1 m, not necessarily representative for a larger area). The agreement with simulated snow depth is (of course) higher: 70–90% agreement, depending on model settings for snow drift and thresholds for wind speed. This analysis can help us to identify suitable cases for comparison with satellite data. A further goal is to combine the SNOWPACK model with microwave emission models for simulating passive microwave radiation and investigating the impact of snow properties on satellite retrieval methods.
Microstructure-based parametrization of the salinity of young growing sea ice
Sönke Maus
Corresponding author: Sönke Maus
Corresponding author e-mail: sonke.maus@ntnu.no
The salinity of sea ice is essential to predict many other sea ice properties (strength, elastic modulus, permeability, thermal conductivity) that in turn impact the behaviour of sea ice in the environment, and the role sea ice plays in the climate system. However, there is currently no consensus how to parametrize sea ice salinity in numerical sea ice models. Though there have been efforts to model desalination and salinity of sea ice, the current models are not well constrained in terms of model parameters (e.g. critical Rayleigh number, permeability) and do not perform better than simple empirical relations. Most empirical and model-based predictions of sea ice salinity are based on brine porosity only. However, from a concise modelling point of view one needs to know the pore space details (pore sizes, vertical and horizontal connectivity) to model the salinity evolution. The present approach uses results from recent X-ray micro-computed imaging of young sea ice to propose and validate a microstructure-based parametrization of the salinity of young sea ice during its growth phase. The approach combines characteristic microstructure metrics (median pore size, plate or brine layer spacing, grain size, vertical and horizontal pore network connectivity), a consistent parametrization of the permeability–porosity relationship, and a formulation of the critical Rayleigh number for convection in a porous medium. It predicts the salinity and level in the ice at which brine convection is expected to cease, and its dependence on ice thickness and growth velocity. Predictions show good agreement with observational data (of salinity and skeletal layer thickness) from the field and laboratory, highlighting the role of microstructure for proper sea ice salinity prediction. The parametrization is validated by microstructure data for young growing sea ice, where desalination is dominated by convection in primary pores between ice lamellae. It sets the initial conditions for modelling the long-term salinity evolution, affected by other processes like slow brine diffusion and formation of wide secondary brine channels during warming. Such modelling is expected to be more complex and requires microstructure and salinity observations over a full annual cycle.
Development and testing of spatially varying landfast ice parameters in CICE6
Richard Allard, Elizabeth Douglass, Gleb Panteleev, David Hebert
Corresponding author: Richard Allard
Corresponding author e-mail: richard.allard@nrlssc.navy.mil
In this study, we use the CICE Consortium CICE6 model which includes the landfast ice parameterization developed by Lemieux (2015, 2016) to perform Arctic landfast ice experiments. We set up regional CICE model domains for areas including the Laptev, East Siberian, Chukchi and Beaufort Seas to optimize and generate spatially varying landfast parameters responsible for grounding sea ice in shallow regions. The regions are subsets of the Navy Earth System Prediction System, which is the target system for this research, and each have a grid resolution of 2 km. The regional standalone models receive initial/boundary conditions from the Global Ocean Forecast System (GOFS 3.1) reanalysis and are run independently for the years 2015/16, and 2017/18. Hindcast studies begin 1 October for a given year and continue through at least 1 July of the following year depending on the region. Atmospheric forcing from the Navy Global Environmental Model (NAVGEM) is used. Optimization of the grounding parameter k1 is accomplished through a Conjugate Gradient minimization of the squared difference (quadratic cost function) between the modeled distribution of the landfast ice and historical landfast ice charts data from the National Ice Center. Minimization of the cost function determines the optimal setting of parameters of the landfast ice parametrization. Typically the optimization converges in less than 25 iterations for 8 independent parameters. Here we present results of our minimization experiments for 9 regional Arctic sub-regions compared to a baseline configuration using default values (no spatial variability) for k1 vs the optimized parameters generated in this study. A qualitative analysis of our results shows a reasonable agreement of the landfast ice extent for each region versus observed extent. These spatially varying parameters are being incorporated into the Navy Earth System Prediction Capability (ESPC).
Claude de Rijke-Thomas, Jack Landy, Michel Tsamados, Joshua King
Corresponding author: Jack Landy
Corresponding author e-mail: jack.c.landy@uit.no
This study introduces a comparison between airborne laser-Ku radar snow depths estimated from Operation IceBridge data during the Spring 2016 campaign and coincident in situ measurements from landfast sea ice near Eureka, Canada, concentrating on first-year ice. Backscattering properties of the air–snow and snow–ice interface were also assessed at Ku-band. Coincident measurements of the air–snow interface elevation were used to reference the OIB laser scanner and Ku-band radar altimeter in height. Snow depth was then obtained from the difference between air–snow interface elevation detected by the laser and snow–ice interface elevation detected by the radar. This method represents an airborne proxy for the aligned ICESat-2 and CryoSat-2 orbits of the Cryo2Ice campaign. On average, 4–5 times more radar power was scattered from the snow–ice interface than from the air–snow interface, over first-year sea ice. However, large variations in relative return power of up to 20 dB could also be observed, particularly from the snow–ice interface, between consecutive radar echoes. The accuracy of measured laser–radar snow depths was higher in the presence of a specular radar return, but there was no systematic bias found between laser–radar and in situ snow depth observations. The observations suggest that a coherent backscatter mechanism can be dominant at the snow–ice interface, of which the theory implies a non-monotonic relationship between the coherent backscatter strength and measurement height, where the measuring height at which the coherent backscatter is optimized depends on the slope distribution of the surface. These findings have important implications for satellite-estimated snow depths and ice freeboards.
Aku Riihelä, Emmihenna Jääskeläinen, Viivi Kallio-Myers
Corresponding author: Aku Riihelä
Corresponding author e-mail: aku.riihela@fmi.fi
The reflectivity or albedo of the Earth’s surface is the principal driver of the surface radiative energy budget. The largest surface albedo variations are linked with the losses and gains of the Earth’s snow and ice cover, both at seasonal and interannual scales. The ongoing warming of the Arctic region has resulted in large losses in its sea ice cover. The surface albedo of the Arctic sea ice zone has declined correspondingly, with the remaining sea ice also becoming thinner, wetter, and subsequently dimmer. Recent substantial losses in Antarctic sea ice (2016–19) also show that the Southern Hemisphere’s sea ice cover is less stable than hoped. As these albedo reductions create a warming impact on the climate via the Snow/Ice Albedo Feeback (SIAF), there is a clear need for sustained monitoring of the sea ice regions of both polar regions. The Satellite Application Facility on Climate Monitoring (CM SAF), a project of EUMETSAT, seeks to answer this need through provision of long-term climate data records from homogenized satellite observations. For surface albedo, first and second editions of the CLARA (CM SAF Clouds, Albedo and Radiation) data records provided global coverage of (black-sky) surface albedo between 1982–2009 and 1982–2015, respectively. Now, the third edition of CLARA has been produced, covering 1979–2020 based on the observations of all AVHRR-carrying weather satellites from TIROS-N to Metop-C. Here, we will present the CLARA-A3 data record’s surface albedo component, now containing black-, white-, and blue-sky albedo estimates, with a focus on the trends and variability of the sea ice albedo of both Northern and Southern Hemispheres. We will also discuss the strengths and limitations of the CLARA-A3 data, drawing on the extensive pre-release validation effort and analysis of the retrieval algorithm. A comparative view on sea ice albedo in CLARA-A3 versus its predecessor CLARA-A2 is also provided for additional perspective to potential users. The overarching message is that CLARA-A3 surface albedo estimates match or improve upon the performance of CLARA-A2.
Sabrina Allard, Émilie Saulnier-Talbot, Michel Gosselin
Corresponding author: Sabrina Allard
Corresponding author e-mail: sabrina.allard.1@ulaval.ca
In the St Lawrence system (Canada), environmental disturbances associated with climate change and increased anthropogenic activities are impacting winter conditions and sea ice dynamics, with repercussions on aquatic coastal ecosystems. To contextualize future seasonal changes, we must improve knowledge about the natural variability of seasonal ice cover prior to the satellite era (1970), by generating reconstructions of past conditions. However, palaeoceanographic indicators used to infer past ice conditions generally have a regional significance and calibration is required. Studies of sea ice cover have focused primarily on polar regions, while little information is available on indicators of seasonal sea ice in sub-Arctic environments, such as the Gulf of St Lawrence, or in coastal and anthropized environments such as the Bay of Sept-Îles (BSI), which houses one of the busiest deepwater ports in Canada. The dual pressure on the BSI, as well as the lack of knowledge about long-term winter dynamics of this ecosystem, justify the need to acquire information on this subject. This project will apply a multidisciplinary approach combining the study of various biogeochemical indicators of winter conditions in subarctic port environments to better understand the state of this high-use ecosystem. Our objective is to identify and characterize biological and geochemical indicators of sea ice that are traceable in the sediment archive and that could be used to trace past sea ice fluctuations in coastal environments of the Gulf of St Lawrence, particularly in port areas currently under heavy anthropogenic pressure. Microbiological content, essential nutrients and elements, diatom assemblages, algal pigments and lipid biomarkers like IP25 and other HBIs will be studied in ice, under-ice water, surface sediments and at various depths of the sedimentary archive. This research is funded by the Port of Sept-Îles, NSERC and INREST.
Johannes Lohse, Catherine Taelman, Alistair Everett, Nick Hughes
Corresponding author: Johannes Lohse
Corresponding author e-mail: johannes.p.lohse@uit.no
Maritime activities in the Arctic require timely and reliable information about sea ice and iceberg conditions. Such information is most commonly transferred to vessels in the form of manually drawn ice charts produced from synthetic aperture radar (SAR) because of its fine spatial resolution and all-weather imaging capability. SAR images are sometimes transferred to the vessels, but manual interpretation of these is challenging and requires considerable training and experience. Increasing volumes of SAR data make automation of sea ice mapping a desirable goal. Although there has been progress in developing (semi-)automated analysis of SAR imagery, promoted by new generations of sensors with capabilities including multiple polarizations and finer spatial resolutions, the transfer of this research into operations remains challenging. In this study, we demonstrate how to bridge this gap, using the CIRFA-22 cruise as a test application and validation case. This cruise was conducted by the Center for Integrated Remote Sensing and Forecasting for Arctic Operations in April/May 2022, using the Norwegian icebreaker RV Kronprins Haakon (KPH). The expedition spent 3 weeks in the Belgica Bank area outside the north-east coast of Greenland, where the sea ice situation can be challenging, consisting of both level and heavily deformed landfast ice close to the coast, and drift ice at various stages of development further east. Before the cruise, we set up a fully automated processing chain that (a) downloads new Copernicus Sentinel-1 data covering the area of interest, (b) processes the data and maps different sea ice types, and (c) uploads the classification results, geo-coded to different spatial resolutions, to an ftp server. This could be accessed from KPH and, depending on the available internet bandwidth, the highest possible spatial resolution result was downloaded to the ship. In this presentation, we outline the technical setup of the processing chain and data transfer, explain how the classification results were used for route planning and navigation in the field, and show validation examples of the classification result.
A study on the properties of granular ice from laboratory experiments
Takenobu Toyota, Yudai Yamashita, Haruka Koda
Corresponding author: Takenobu Toyota
Corresponding author e-mail: toyota@lowtem.hokudai.ac.jp
The crystal alignments of sea ice are categorized mainly into two types: columnar ice and granular ice. Whereas columnar ice is produced through the bottom freezing under calm conditions and its growth rate can be estimated with good accuracy, the formation processes of granular ice produced under turbulent conditions have not been fully understood yet because of its complexity and the lack of observation. Given that granular ice occupies significant fraction of total ice thickness especially in the seasonal ice zone (SIZ) and the increase in the fraction of SIZ, the understanding of granular ice formation is quite important. One of the characteristic properties of granular ice is its wide range of grain size and shape. Aiming at retrieving the growth conditions from the sea ice samples obtained, we conducted a tank (0.30 m×0.30 m×0.65 m) experiments with various air temperatures, degrees of turbulence, and snowfall amounts in a cold room. Our experiments successfully reproduced realistic granular ice, and the results reveal that grain sizes and shapes are controlled mainly by thermodynamical conditions (air temperature) than dynamic conditions (degree of turbulence), and snow particles act efficiently as a seeding to increase ice production rates significantly.
Shiming Xu
Corresponding author: Shiming Xu
Corresponding author e-mail: xusm@tsinghua.edu.cn
We introduce the high-resolution simulations of Arctic sea ice kinematics within the CESM/CICE modeling framework. Multi-resolution grid hierarchy is implemented in CESM/CICE, with the highest resolution of about 1–2 km in the Arctic. Online Lagrangian diagnostics is built into the CICE to facilitate the analysis of sea ice kinematics. We carry out climatological runs and diagnostics of the sea ice kinematics, with both traditional scaling analyses and the novel statistics based on linear kinematic features (LKFs). Specifically, we compare the rheology models of EVP and EAP in CICE5, as well as the two parameterization schemes for ice strength. The multi-fractal characteristics and the LKF statistics are shown to be sensitive to the both model options. The model implementation of the grid and the add-ons are openly available for the CESM/CICE system.
A climate record of wave-affected marginal ice zone in the Atlantic Arctic based on CryoSat-2
Shiming Xu
Corresponding author: Shiming Xu
Corresponding author e-mail: xusm@tsinghua.edu.cn
The marginal ice zone (MIZ) is a region of extensive interactions between the polar atmosphere, ocean and sea ice. Waves and swells develop over the open ocean and propagate into the ice edge, breaking the ice into smaller floes and modifying the bottom of the atmosphere and the surface ocean. Given the ongoing climate change in polar regions, wave-affected MIZ is of particular importance, which is also a focus of the ongoing effort of the community for better defining and observing MIZs. We introduce a new climate record for wintertime wave-affected MIZ based on CryoSat-2 (CS2), covering the Atlantic Arctic during the winter months since 2010. The retrieval method is based on the delay-Doppler radar altimetry over sea ice, and in particular, the waveform stack parameters of CS2. Large MIZs can reach over 300 km into the ice pack, as observed by CS2. No statistically significant change of the wave-affected MIZ has been found since 2010, but large interannual and intraseasonal variability is present. We relate the MIZ width to both wave/swell conditions and the sea ice parameters in the MIZ. Especially, the new dataset sheds light on the swell attenuation in the MIZ, which: (1) contains systematic coverage of the various sea ice conditions, and (2) is consistent with various Arctic and Antarctic in-situ measurements. Related issues, including altimetric representation for MIZ, as well as extensions to the dataset are also discussed.
Mike Brady, Stephen Howell, Alexander Komarov
Corresponding author: Mike Brady
Corresponding author e-mail: mike.brady@ec.gc.ca
Arctic sea ice motion is an important component in quantifying changes in Earth’s climate but is difficult to monitor on the spatial and temporal scales required to improve understanding. Earth-observing satellite synthetic aperture radar (SAR) sensors provide all-weather, high-resolution data with regular revisit capacity; thus facilitating rapid and detailed observations of sea ice conditions. Combining several complimentary sources of SAR data allows the Environment and Climate Change Canada automated sea ice tracking system (ECCC-ASITS) to achieve pan-Arctic-scale information on sea ice motion (SIM). Since March 2020, the ECCC-ASITS ingests ~100–150 SAR images per day from the RADARSAT Constellation Mission (RCM) and Sentinel-1 (S1) missions to produce and publish new RCMS1SIM products with two configurations: 7-day SIM at 25 km and 3-day at 6.25 km spatial resolution. The 7-day SIM product provides the most complete picture of SIM across the Arctic solely from SAR data, and the 3-day 6.25 km product fills a vital gap by providing information in regions where narrow channels and inlets would not be resolved in coarser-resolution SIM products. Evaluation of RCMS1SIM products against drifting buoys indicated a root mean square error (RMSE) of 2.78 km d–1 under dry-ice conditions and 3.43 km d–1 during melt conditions. The RCMS1SIM products from ECCC-ASITS represent the first routinely generated SIM products derived entirely from SAR imagery across the pan-Arctic domain.
Seasonal variations in the sea ice-mixed layer depth relationship in the West Antarctic Peninsula
Milo Bischof, Daniel Goldberg, Sian Henley, Neil Fraser
Corresponding author: Milo Bischof
Corresponding author e-mail: milo.bischof@ed.ac.uk
Sea ice plays an important role in determining mixing conditions in the upper-ocean. This is due to freshwater and salt fluxes across the ice–ocean interface related to sea ice formation and melt, as well as a moderation of the mechanical forcing of wind acting on the ocean surface. In turn, water column structure and mixing conditions in the upper ocean are vital factors shaping the environment in which biological production occurs. With sea ice conditions projected to undergo large changes over the course of the century, understanding the relationship between sea ice and upper-ocean mixing is crucial for understanding the impacts of climate change on biological productivity in the polar oceans. Due to the inaccessibility of sea ice-covered waters, mixed layer depth observations are often not available at a high temporal and spatial resolution. Here we present an analysis of sea ice-mixed layer depth relationships during a 40-year regional sea ice–ocean MITgcm model simulation of the West Antarctic Peninsula (WAP) and Bellingshausen Sea, a highly biologically productive region undergoing large present-day changes in climate. The relationship between winter sea ice and spring mixed layer depth shows clear differences on and off the WAP continental shelf, with decadal variations in the location of the boundary between negative and positive correlations. These results are used as a starting point to explore mechanisms that might give rise to regional differences in the sea ice-mixed layer depth relationship in the WAP. We discuss the nonlinear relationship between sea ice concentration and momentum flux into the ocean; the transport of sea ice within our model domain; the timing of seasonal processes in different regions of the WAP; and the impacts of Circumpolar Deep Water on and off the continental shelf.
H. Jakob Belter, Jonathan Bahlmann, Lasse Rabenstein, Bernhard Schmitz, Panagiotis Kountouris, Christine Eis, Martin Bathmann, Anja Frost, Stefan Wiehle, Kim Knauer, Christof Büskens
Corresponding author: H. Jakob Belter
Corresponding author e-mail: belter@driftnoise.com
Climate change and the subsequent retreat of sea ice favour the increase of maritime traffic in both polar regions. Despite the growing importance of the ice-covered oceans for all types of global shipping and the availability of massive Earth observation (EO) and weather data archives, navigational decision making is still limited. This is due to the fact that manual data pick up by the ship crews continues to be next to impossible for at least the following two reasons. (1) Communication bandwidth is limited in the polar regions and (2) the conversion of such data into navigational decisions is inherently a big data process. The FastCast-2 project develops innovative solutions to enhance the value of satellite-based EO and weather data. Furthermore, we process that data into near-real time and on-demand route suggestions for stakeholders transiting through or around ice-infested waters. AI-techniques are used to accelerate underlying processing steps and state-of-the-art web technologies such as ‘Progressive Web Apps’ are utilized for user interaction. The International Maritime Organization’s Polar Code requires ships to have up-to-date ice information on board when heading towards the polar regions. Although the ice is retreating, sea ice, icebergs and uncharted bathymetry remain hazardous for modern day polar shipping. The FastCast-2 consortium strives to combine improved sea ice drift forecasts with up-to-the-minute ice and weather information, which are processed into continuously updated route suggestions. These route suggestions will also avoid shallow areas detected by satellite-derived bathymetry. This kind of service will not only help ships to fulfill the Polar Code requirements. It will also advance digitization of the shipping industry and enable ship crews and their companies to find the safest, fastest, and most fuel-efficient routes in and around ice-covered waters.
Optimized routes for ship in-ice navigation based on sea ice classification and ice drift forecasts
Christine Eis, Bernhard Schmitz, Christof Büskens
Corresponding author: Christine Eis
Corresponding author e-mail: c.eis@uni-bremen.de
Sea ice retreat as a consequence of climate change leads to increasing shipping activities within polar waters, as newly opened shipping routes can be much shorter than the established ones. Cargo ships benefit from about 30% reduced travel distances between Europe and Asia by taking Arctic passages. Consequently the demand for time and fuel is strongly reduced. However, navigation in polar waters is still challenging and even dangerous, e.g. because of fast-changing ice conditions or unknown bathymetry. Even with having access to the proper Earth observation data such as radar images, ice classifications or ice charts, manoeuvring in polar waters is not trivial and requires trained staff as well as expert knowledge. To provide navigational assistance in polar regions, we develop a system that provides route suggestions based on Earth observation data, given ship characteristics, bathymetry and drift/weather models. Using these models, ice classifications derived from Earth observation data are interpolated in time to gain high-resolution knowledge about the changing ice conditions. The resulting 3-dimensional route optimization problem can be solved using an A* algorithm. However, this algorithm is inefficient when applied to long-distance routes, because large datasets offer too many possible combinations of connecting waypoint candidates. To overcome this issue, different methods are tested, which can be divided in two categories: preprocessing steps and further modification of the A* algorithm. The preprocessing techniques reduce the number of waypoint candidates, while keeping important information about small features in the ice, such as (open) leads or divergence zones. The reduced set of identified waypoint candidates and the connections between them is called ‘road map’ and serves as input for the A* algorithm. Investigated variants of the A* algorithm include, e.g., weighting methods and an anytime implementation. Both approaches and their combination are evaluated in terms of efficiency and reasonability.
Yuxian Ma, Bin Cheng, Matti Leppäranta, Shuai Yuan, Ning Xu
Corresponding author: Bin Cheng
Corresponding author e-mail: bin.cheng@fmi.fi
Temperature and salinity are essential thermodynamic parameters of sea ice. Research of sea ice temperature–salinity processes has been largely focused on the polar oceans. Little attention has been paid recently to seasonally ice-covered seas, which are more vulnerable to climate change owing to their location at the climatological sea ice margin with higher winter air temperature and stronger solar radiation compared with the polar oceans. A 40-day long field campaign was carried out in winter 2020/21 in the northern Bohai Sea in the landfast sea ice zone. We investigated sea ice temperature and salinity characteristics based on field observations. A thermistor string was used to measure the ice temperature, and ice core samples were collected routinely to measure the ice salinity and analyse the crystal structure. To tackle the uncertainties of ice salinity due to the unavoidable brine drainage during ice sample collection, we applied a simple but novel methodology to obtain the in situ ice salinity and compared the results with the conventional ice core sampling method. A numerical sea ice model was applied with a special focus on the role of ice salinity in the ice mass balance. Our results have potential applicability to the Arctic sea ice considering that the Arctic Ocean is predicted by climate models to be only seasonally ice-covered in the near future.
Reducing uncertainty in projections of Antarctic sea ice
Caroline Holmes, Tom Bracegirdle, Paul Holland, David Stephenson
Corresponding author: Caroline Holmes
Corresponding author e-mail: calmes@bas.ac.uk
There is low confidence in projections of Antarctic sea ice area (SIA), due to deficiencies in climate model representation of the sea ice mean state and sea ice processes. Previous studies have suggested that accounting for historical mean state biases by using ensemble regression techniques can reduce uncertainty in projections. We present relationships between SIA historical climatology and SIA change by 2100 in the CMIP6 multi-model ensemble, and compare results to those found for CMIP5. In summer (February), under a strong forcing scenario, the historical climatology of SIA is a strong linear constraint on projections of SIA in both CMIP5 and CMIP6. This is because almost all models have near-zero SIA by the end of the century, so that the models that start with greater SIA exhibit greater reductions. This relationship is even more robust in CMIP6 than CMIP5; this can be understood by the fact that CMIP5 contains many models that have very large positive biases in historical SIA, such that this ‘no ice’ limit is not reached. In winter, ensemble spread in historical mean SIA explains approximately half the spread in projected change for CMIP6 under a strong forcing scenario, despite the fact that the no ice limit does not apply. Moreover, CMIP6 displays greater winter ice loss than CMIP5 despite similar historical climatologies and regression relationships; we find this to be statistically related to the well-known higher climate sensitivities of some CMIP6 models. These findings suggest a dependence of Antarctic SIA loss on the initial SIA state, both through the constraint provided by the no-ice limit and through other mechanisms, as well as on the rate of global temperature change. However, such a multi-model linear regression hides assumptions about the time evolution of sea ice. We will therefore present some novel ideas regarding a simple statistical model, grounded in physical considerations, to capture the time evolution of CMIP6 SIA with a small number of parameters. We will discuss how well such a model can emulate CMIP6 simulations, and the potential for using it for constraining projections, as well as how it relates to our existing approach.
Resolving drag coefficients estimates on Arctic-wide spatial and monthly temporal scales
Alexander Mchedlishvili, Alek Petty, Christof Lüpkes, Michel Tsamados, Gunnar Spreen
Corresponding author: Gunnar Spreen
Corresponding author e-mail: gunnar.spreen@uni-bremen.de
The effect that sea ice topography has on the momentum transfer between ice and atmosphere is not yet fully quantified. Reasons for this are the limitation of current measurement techniques for sea ice topography, the vast extent of the Arctic, and necessary simplifications in parameterizations. As a result, coupled sea ice–ocean–atmosphere models still assume drag force to be mostly constant Arctic-wide or base the variability only on the effect of floe edges and on sparse airborne and in-situ measurements. Especially in the central Arctic, where there are not as many floe edges due to high sea ice concentrations, the current approaches and measurements are insufficient to characterize such a dynamic and vast area. Our findings show that assuming a constant drag coefficient in both space and time misrepresents the variability of momentum fluxes near the surface and thus the main forcing of sea ice drift. Here we present a method to estimate pan-Arctic momentum transfer via a parameterization which links sea ice–atmosphere form drag coefficients with ridge height and spacing. The sea ice surface feature parameters are measured using the ICESat-2 laser altimeter which has a higher along-track spatial resolution than other contemporary altimeter satellites. To bridge the gap between the high-resolution satellite data product and the resolution of airborne measurements, we derive a scaling factor from near-coincident Operation IceBridge measurements to modify our surface feature parameters to be within the expected range. Using this technique, a pan-Arctic monthly drag coefficient estimate product was produced. With this product, we are able to better resolve the temporal and spatial evolution of drag. By producing time series of average Arctic-wide drag coefficient estimates for the period 11.2018–06.2022, we have found interesting seasonal and annual patterns in the data, whereas mapping the product for individual months, allowed us to better analyze the spatial variability
Realizing the potential of data driven sea ice retrieval methods from SAR
Karl Kortum, Suman Singha, Gunnar Spreen
Corresponding author: Karl Kortum
Corresponding author e-mail: karl.kortum@dlr.de
The remoteness and environmental hostility of the Arctic and Antarctic regions greatly impact polar remote sensing research, because high-resolution ground measurements are sparse and have only limited tempo-spatial validity. In the case of sea ice class retrieval from space-borne synthetic aperture radar (SAR), research thus becomes heavily reliant on human annotated datasets. Due to the limited time that a human observer can spend on a scene and the difficulty of labelling sea ice from the backscatter alone, these annotations suffer from a range of drawbacks. Real (measured) ground truth data will likely not become readily available for a large range of SAR acquisitions at high resolution and coverage. Thus, it is difficult to realize the potential of data driven algorithms: To become increasingly more proficient with the influx of more reference data. The only way to build such retrieval algorithms is to be independent of additional data sources which are not readily available. This implies that (high-resolution) ice classification is not a task that can reap the benefits of data-driven algorithms, as added data in the form of high-resolution labels is required but not available. However, we can use local incidence angle dependence of sea ice backscatter as a proxy for ice class labels: Using physics informed networks enables learning such incidence angle dependencies without any additional data but the SAR imagery. This allows for a sustainable sea ice retrieval method, that circumvents a majority of shortcomings originating from the lack of readily available ground truth and is truly able to improve with the SAR data alone.
Carmen Nab, Davi Mignac, Michel Tsamados, Matthew Martin, Julienne Stroeve
Corresponding author: Carmen Nab
Corresponding author e-mail: carmen.nab.18@ucl.ac.uk
Sea ice thickness (SIT) estimates derived from the Cryosat-2, Sentinel-3, Soil Moisture and Ocean Salinity (SMOS) and ICESat-2 satellites are assimilated into the Met Office’s global ocean–sea ice forecasting system, FOAM, using a 3D-Var assimilation scheme, NEMOVAR. The CryoSat-2/Sentinel-3 and ICESat-2 along-track SIT estimates are converted from ice and total freeboard measurements, respectively, using the model snow depth and assimilated together with the daily, gridded SMOS SIT product to constrain the model SIT. It is commonly assumed that radar pulses from Ku-band altimeters such as Cryosat-2 and Sentinel-3 penetrate all the way through the snowpack, reflecting off the snow–ice interface, although an increasing body of studies has shown this not to be the case. We start by assimilating CryoSat-2 and Sentinel-3 sea ice thickness, assuming varying levels of radar penetration through the snowpack. We then use this optimized penetration factor to assimilate CryoSat-2 and Sentinel-3 sea ice thickness estimates together with those from SMOS and ICESat-2. We compare our model SIT results to in situ observations taken as part of the Beaufort Gyre Exploration Project (BGEP), MOSAiC and Operation IceBridge expeditions, as well as a combined CS2 + SMOS sea ice thickness product. This work evaluates for the first time the impacts of using a varying assumed penetration depth for CryoSat-2 and Sentinel-3 on the SIT assimilation, as well as representing the first assimilation of ICESat-2 SIT data into a coupled ocean–sea ice system.
David Babb, Sergei Kirillov, Jack Landy, Stephen Howell, Julienne Stroeve, Jens Ehn
Corresponding author: David Babb
Corresponding author e-mail: david.babb@umanitoba.ca
Fram Strait is the primary pathway for sea ice export from the Arctic Ocean. The volume of sea ice exported exerts a significant influence on both the ice mass balance of the Arctic Ocean and the freshwater budget of the North Atlantic. Despite its importance, present estimates of sea ice volume export are either confined to the winter season, extrapolated from sparse in situ observations of ice thickness or rely on modeled estimates of thickness. Here, we use a new year-round ice thickness product derived from Cryosat-2 to provide a consistent estimate of the annual record of sea ice volume export through Fram Strait from 2010–2021. We estimate that on average 1733 km3 was exported annually across a flux gate at 82° N, with 80% occurring during the ice growth season (October–April) and only 20% occurring during the melt season. Our record is too short to confirm the previously reported trend towards reduced sea ice volume export through Fram Strait; howeverwe find export to be highly variable with a peak of 2500 km3 in 2015 and a minimum of 900 km3 in 2018. Our estimate of export during the growth season is slightly less than previous estimates of seasonal ice export using Cryosat-2, which we attribute to differences in the ice thickness products, specifically ways of accounting for snow, and a longer study period that includes the minimum in 2018. Furthermore, for comparison with previous studies we calculate sea ice volume flux across gates at different latitudes. Although comparisons are limited by the different methods used to quantify ice thickness in the volume flux calculations, there was a clear transition over the past 30 years towards a thinner ice pack being exported through Fram Strait. Additionally, calculating ice volume flux at different latitudes reveals that ice volume export declined linearly at a rate of 311 km3/° between 82° N and 79° N and accounts for a nearly 50% reduction in ice volume export over these 4°. Ultimately, we provide a consistent and temporally complete analysis of sea ice volume export through Fram Strait, and briefly examine its contribution to the overall sea ice volume budget of the Arctic Ocean.
New ice production in leads estimated from SAR-derived sea ice divergence
Luisa von Albedyll, Nils Hutter, Christian Haas
Corresponding author: Luisa von Albedyll
Corresponding author e-mail: luisa.von.albedyll@awi.de
In the polar winter, leads in sea ice created by divergent motion are important sites for new ice production and salt rejection. This is because ice grows faster in open water and under thin ice, and growth is thus enhanced in leads compared to the surrounding ice. New ice formation followed by ridging in leads can contribute 25–40% to the sea ice volume budget in a mobile, dynamic ice pack and is thus an effective mechanism to increase the sea ice volume. With the Arctic transitioning towards ice-free summers, accurate and precise methods are needed to quantify and monitor trends in new ice formation in leads for model evaluation. We present a study of new ice production and salt rejection in leads using high-resolution synthetic aperture radar (SAR)-derived divergence data along the Transpolar Drift in 2019/20. We use sequential Sentinel-1 A/B scenes with a spatial resolution of 50 m and a nominal temporal resolution of 1 day to calculate sea ice drift and divergence on a scale of approximately 300×300 km. The re-sulting divergence data can resolve leads with a width of a few hundred meters. By drift-correcting and accumulating deformation information, we can calculate accumulated lead frac-tions that accurately indicate when, where, and with which width a lead has formed. Tracking this information over time allows us to reconstruct the deformation history of individual leads, including opening, closing, inactive periods, or reactivation. By combining the accumulated lead fractions with a well-established 1D model for thermodynamic growth, we can reconstruct new ice formation for each grid cell. The daily resolution makes our estimates much more reliable compared to previous attempts. Our results show good agreement with in-situ and air-borne ice thickness observations within the expected range of uncertainties. In conclusion, SAR-derived divergence is a powerful method for estimating new ice production and salt rejec-tion on regional scales.
Influence of warm air intrusions on satellite sea ice concentration climatologies
Philip Rostosky, Gunnar Spreen
Corresponding author: Philip Rostosky
Corresponding author e-mail: prostosky@iup.physik.uni-bremen.de
Warm air intrusions entering the Arctic during wintertime (Nov–Apr) can lead regional to a rapid increase of air temperature, which for the full duration of the intrusion can reach large parts of the sea-ice-covered Arctic. Temperatures can get above –2°C (a threshold we use in this study) and consequently snow metamorphism and surface glazing can take place. Such changes modify the microwave emission of the snow–ice system. Satellite-based sea ice concentration retrievals rely on the microwave emission contrast and/or the polarization difference of ice and open water. Studies have shown that changes in the snow–ice due to the warm air intrusions can lead to an underestimation of retrieved sea ice concentration. Analyzing 40 years of winter sea ice climate data record from different algorithms and ERA5 reanalysis data, we show that large-scale warming waves have become more frequent in the last 20 years. In particular, we have found that the warming waves reaching above –2°C have a strong impact on most sea ice concentration retrievals, which lead to significant underestimation of sea ice area estimates. In the last 10 years, these warming events occurred frequently in April and are an important source of uncertainty in satellite-derived sea ice data.
Inverting spectral albedo to estimate solar heat deposition at the surface of sea ice
Christophe Perron, Martin Vancoppenolle, Marcel Babin
Corresponding author: Christophe Perron
Corresponding author e-mail: chper110@ulaval.ca
Earth system models, among other purposes, predict sea ice evolution at large scale and over many decades. To represent surface melting processes of sea ice in these models, one needs to account for the shortwave heat deposition at the surface of sea ice. To calculate shortwave heat deposition , the albedo and the surface absorptance (the percentage of shortwave radiation transformed to heat at the surface) are parametrized. While the albedo has been well documented for different ice surfaces, there are few observations, and therefore an ill-informed parametrization of the surface absorptance. Using the existing methods, estimating surface absorptance is challenging. In opposition to the albedo measurement, it is necessary to dig a hole to obtain physical and optical measurements from the surface onto the bottom of the ice column. These methods are destructive and time consuming, which explains the lack of observations. We show in this presentation that a full-spectrum inversion of the spectral albedo measured on the ground or by remote sensing could be used to obtain non-destructive, thorough surface absorptance estimations. Spectral albedo measurements are widely available both from the ground and by remote sensing, providing substantial data for modellers to improve surface absorptance parametrization in Earth system models.
Atmospheric turbulent intermittency over the Arctic sea-ice surface during the MOSAiC expedition
Changwei Liu, Qinghua Yang, Matthew Shupe, Yan Ren, Shijie Peng, Bo Han, Dake Chen
Corresponding author: Qinghua Yang
Corresponding author e-mail: liuchw8@mail.sysu.edu.cn
Turbulent motion in the Arctic stable boundary layer is characterized by intermittency, but it is rarely investigated due to limited observations, in particular over the sea-ice surface. In the present study, we explore the characteristics of turbulent intermittency over the Arctic sea-ice surface by using the data collected during the MOSAiC expedition from October 2019 to September 2020. We firstly develop a new algorithm, which performs well in identifying the spectral gap over the Arctic sea-ice surface. Then the characteristics of intermittency are presented, and it is found that the strength of intermittency increases under lower surface wind speed and wind speed gradient and under higher surface air temperature gradient. The intermittency leads to an overestimation of 3%, 10% and 24% for the momentum flux, sensible heat flux and latent heat flux, respectively, calculated by raw eddy-covariance fluctuations. Furthermore, the characteristics of atmospheric boundary layer structure under various intermittency conditions reveal that strong low-level jets are favorable to surface turbulent motions that result in weak intermittency, while strong temperature inversions above surface layer suppress surface turbulent motions and lead to strong intermittency.
Implications of Antarctic sea-ice change on Southern Ocean ecology and biogeochemical cycles
Klaus Meiners, Martin Vancoppenolle, Rob Massom, Delphine Lannuzel, Philipp Assmy, Ilka Peeken, Hauke Flores, Jeff Bowman, Sian Henley, Marcello Vichi, Lynn Russell, Jacqueline Stefels, Francois Fripiat, Maria A. van Leeuwe, Agneta Fransson, Inge Deschepper, Karley Campbell
Corresponding author: Klaus Meiners
Corresponding author e-mail: klaus.meiners@aad.gov.au
Changing sea-ice coverage has major, though regionally and seasonally varying, effects on the structure and function of Antarctic marine ecosystems and Southern Ocean biogeochemical cycling. While much focus has been given to the spiralling decline in Arctic sea-ice coverage, major and rapid changes are also currently occurring in the Antarctic sea-ice zone, reaching another record low in 2023. Long-term observations from the West Antarctic Peninsula have shown how a decline in sea-ice extent and duration has impacted food webs across multiple levels and affected biogeochemical processes in intricate ways, including through cascading effects and changes in community structures. Here we summarize how these key processes are responding to observed patterns of Antarctic sea-ice change and variability, notably in the modern satellite era since 1979. We then synthesize this information to provide a perspective of the likely state of the system at the end of the 21st century, based on CMIP6 high radiative forcing (SSP5-8.5) sea-ice simulations. In particular we contrast likely impacts in the Antarctic marginal sea-ice zone, the interior pack-ice zone and fast-ice areas. Our synthesis highlights important knowledge gaps including understanding and better model parameterizations of: (i) light transmission through snow and ice; (ii) controls on primary production in sea ice; iii) uptake and release of iron from sea ice, (iv) supply and cycling of macronutrients in sea ice and exchange with surface waters, and (v) fluxes, deposition and emission of climatically active gases and aerosols from the ice-covered Southern Ocean.
Mirjam Bourgett, Martin Losch
Corresponding author: Martin Losch
Corresponding author e-mail: Martin.Losch@awi.de
Sea ice dynamics in climate models are usually quasi-homogenous non-normal fluids with a viscous-plastic (VP) rheology. Recent alternatives are brittle models where a parameterization of damage due to tension, compression, and shear stress allows fast feedbacks between forcing and ice state and hence high spatial heterogeneity and intermittency in agreement with observations. VP models tend to achieve similar statistical properties only at higher resolution (smaller grid spacing). For a comparison between rheologies that is not biased by grid type, discretization, or advection schemes, a Maxwell-elasto-brittle (MEB) rheology is implemented in the sea ice component of a community general circulation model code that already contains different VP-rheologies. As expected, the spatial heterogeneity of the solutions depends to a large degree on horizontal grid spacing, but also on the parameterization of sub-grid scale variability for both VP and MEB rheologies. The sub-grid scale variability is parameterized as randomly perturbed internal parameters such as ice strength and cohesion. The observed differences between rheologies are much smaller than the differences between models with and without parameterized sub-grid scale variability.
Forced and internal components of observed Arctic sea ice changes
Jakob Dörr, David Bonan, Marius Årthun, Lea Svendsen, Robert Wills
Corresponding author: Jakob Dörr
Corresponding author e-mail: jakob.dorr@uib.no
The Arctic sea ice cover is strongly influenced by internal variability on decadal time scales, affecting both short-term trends and the timing of the first ice-free summer. Several mechanisms of variability have been proposed, but how these mechanisms manifest both spatially and temporally remains unclear. The relative contribution of internal variability to observed Arctic sea ice changes also remains poorly quantified. Here, we use a novel technique called low-frequency component analysis to identify the dominant patterns of winter and summer decadal Arctic sea-ice variability in the satellite record. The identified patterns account for most of the observed regional sea ice variability and trends, and thus help to disentangle the role of forced and internal sea ice changes over the satellite record. In particular, we identify a mode of decadal ocean–atmosphere–sea ice variability, characterized by an anomalous atmospheric circulation over the central Arctic, that accounts for approximately 30% of the accelerated decline in pan-Arctic summer sea-ice area between 2000 and 2012. For winter sea ice, we find that internal variability has dominated decadal trends in the Bering Sea but has contributed less to trends in the Barents and Kara Seas. These results, which detail the first purely observation-based estimate of the contribution of internal variability to Arctic sea ice trends, suggest a lower estimate of the contribution from internal variability than most model-based assessments.
Extension of the sea ice climate time series with historical satellite data from the 1970s
Wiebke Margitta Kolbe, Rasmus Tage Tonboe
Corresponding author: Wiebke Margitta Kolbe
Corresponding author e-mail: wmako@space.dtu.dk
Arctic sea ice is an important climate indicator, since global climate change effects are amplified in the arctic. Current satellite sea ice climate data records (CDRs) documenting this change are beginning with data from the scanning multichannel microwave radiometer on board NASA’s NIMBUS-7 satellite in October 1978. However, satellite missions from the early and mid 1970s can be used for mapping sea ice and extending the current CDRs. One example is the data from the electrically scanning microwave radiometer (ESMR) on board the NIMBUS-5 satellite, operating between 1972 and 1977. With a swath width of about 3100 km ESMR provided full coverage of polar regions in half a day, measuring the horizontally polarized brightness temperature at 19.35 GHz for 78 different incidence angles. The data are available at NASA Earth data archive (GES DISC) and a first reprocessing using modern sea ice retrieval methods as part of the ESA CCI+ program showed that, while older satellite instruments have their limitations compared to modern sensors, they still provide useful data for mapping sea ice. The work continues in a PhD project developing new methods to process historical satellite data in order to extend existing sea ice CDRs into the past. The project is a part of the Danish National Centre for Climate Research at DMI and will provide insights into historical sea ice development and serve as an important sea ice extent reference from the 1970s, which can be used for input to climate models and re-analysis. The sea ice concentration (SIC) from the ESMR data is derived using a single channel algorithm and modern processing steps including dynamical tie-points, regional noise reduction with a correction based on a radiative transfer model and numerical weather prediction model data. The results (data at DOI:10.5285/34a15b96f1134d9e95b9e486d74e49cf) show interesting sea ice features in the years 1972–77, e.g. the Maud Rise Polynya in Antarctica and the new ice Odden in the Greenland Sea, an ice tongue that extends eastward from the East Greenland Current. Both features were much larger in extent in the mid-1970s than they are today, providing an important reference of the past. Current work on the ESMR data includes re-calibration, further noise reduction and validation/inter-comparison to other sea ice datasets during this period and further investigation of other satellite data of the 1970s for comparison and filling gaps with respect to SIC and ice type.
How much does Antarctic landfast ice affect coastal polynyas at the circumpolar scale?
Noé Pirlet, Thierry Fichefet, Martin Vancoppenolle, Alexander Fraser, Clément Rousset, Pierre Mathiot, Casimir de Lavergne
Corresponding author: Noé Pirlet
Corresponding author e-mail: noe.pirlet@uclouvain.be
The coastal polynyas of the Southern Ocean play a crucial role in the formation of dense water and have an impact on the stability of ice shelves. Therefore, it is important to accurately simulate them in climate models. To achieve this goal, the relationship between grounded icebergs, landfast ice and polynyas appears to be central. Indeed, grounded icebergs and landfast ice are believed to be key drivers of coastal polynyas. However, ESMs do not simulate Antarctic landfast ice. Moreover, at a circumpolar scale, there are no observations of grounded icebergs available. Hence, we must seek model representations that can overcome these issues. To address these gaps, we conducted a study using the global ocean–sea ice model NEMO4.2-SI–3. We ran two simulations for the period 2001–17, with the only difference being the inclusion or exclusion of landfast ice information based on observations. All other factors, including initial conditions, resolution and atmospheric forcings, were kept the same. We then compared the results of these simulations with observations from the advanced microwave scanning radiometer to evaluate the performance of the new simulation. Our analysis allowed us to determine the extent to which prescribing the distribution of landfast ice and setting the sea ice velocity to zero on landfast ice regions influenced various aspects of the sea ice, such as polynyas, landfast ice and sea ice distribution in the model. In the future, we plan to refine this technique by testing more complex methods, such as assimilating icebergs and physical parameterization.
Janina Osanen, Karley Campbell, Laura Martín, Zoé Forgereau, Ilka Peeken, Rolf Gradinger, Janne Søreide, Mats Granskog, Benjamin Lange
Corresponding author: Janina Osanen
Corresponding author e-mail: janina.osanen@gmail.com
Sea ice algae are a fundamental part of the sea ice ecosystem, but they remain under-sampled due to the limitations of current sampling and logistical challenges of conducting research in the Arctic. In this study, we assess the use of novel remote sensing technologies by remotely estimating sea ice algal biomass using an underwater hyperspectral imager (UHI) in both laboratory conditions and in situ in two Svalbard fjords. Optimal normalized difference indexes (NDIs) were obtained and applied to the UHI surveys using transmittance (%), and results revealed differences in chlorophyll a concentration up to 6 mg mg–2 within only 2 cm on the sea ice subsurface. Using a unique laboratory setup with optically clear incubation tanks, we successfully applied an NDI combination, obtained from an incubated subsample from Van Mijenfjorden, to our in situ surveys. This NDI combination explained up to 87% of chl a variability, whereas a slight shift in species composition reduced the model performance down to 2%. The optimal NDIs, combined with oxygen-optode incubations, enabled the remote estimation of net community production, revealing a heterotrophic state of the community and considerable variability in production per chl a across multiple scales. Paired with time-series surveys, the spatial and temporal variability of chl a and related production could be mapped without extensive sampling efforts. This study demonstrates the potential of using UHIs paired with bio-optical models for multi-scale estimation of biomass and production, minimizing the need for invasive and time-consuming in situ sampling.
Guillaume Boutin, Einar Ólason, Pierre Rampal, Heather Regan, Camille Lique, Claude Talandier, Laurent Brodeau, Robert Ricker
Corresponding author: Guillaume Boutin
Corresponding author e-mail: guillaume.boutin@nersc.no
Sea ice is a key component of the Earth’s climate system as it modulates the energy exchanges at the air–sea interface in polar regions. These exchanges strongly depend on openings in the sea-ice cover, which are associated with fine-scale sea-ice deformations. However, the impact of these deformations remains poorly understood as their representation in numerical models generally requires using very high and costly horizontal resolutions. Here, we present results from a 12 km resolution ocean–sea-ice coupled model, involving the ocean component of NEMO and the sea ice model neXtSIM. This is the first coupled model that uses a brittle rheology to represent the mechanical behaviour of sea ice. Using this rheology enables the reproduction of the observed characteristics and complexity of fine-scale sea ice deformations. We investigate the sea ice mass balance of the model for the period 2000–18. After evaluating the modelled sea ice against available observations (extent, drift, volume, deformations, etc.), we assess the relative contribution of dynamical vs thermodynamic processes to the sea-ice mass balance in the Arctic Basin. We find a good agreement with ice volume changes estimated from the ESA CCI sea-ice thickness dataset in the winter, demonstrating for the first time the ability of brittle rheologies to reproduce the Arctic sea ice mass balance over long periods. Using the unique capability of the model to reproduce sea-ice deformations, we estimate the contribution of leads and polynyas to winter ice production. We find that this contribution adds up to 25–35% of the total ice growth in pack ice in winter, showing a significant increase over the 18 years covered by the model simulation. This coupled framework opens new opportunities to understand and quantify the interplay between small-scale sea-ice dynamics and ocean properties that cannot be inferred from satellite observations.
A model intercomparison provides new insights into carbon cycling in the Canadian Arctic Ocean
Johanna Länger, Benjamin Richaud, Inge Deschepper, Yarisbel Garcia-Quintana, Katja Fennel, Paul G. Myers, Nadja Steiner
Corresponding author: Johanna Länger
Corresponding author e-mail: jlanger@uvic.ca
The Arctic Ocean is experiencing rapid changes in terms of sea ice seasonality and properties, freshwater inputs by ice melt and terrestrial runoff, stratification and mixing. These physical changes impact biogeochemical cycles in the Arctic Ocean, including the carbonate system. Numerical models are useful tools to assess these changes in the carbon system. However the complexity of the models used varies, which might impact modeled results. To quantify these intra-model variations, we use three biogeochemical models, set up and run by different research groups. All models were forced with the Drakkar Forcing Set 5 (DFS5) atmospheric forcing for the year 2015 and run on the NEMO ocean modeling framework. The three carbon modules are Biogeochemistry with Light Iron Nutrients and Gases (BLINGv0+DIC), Canadian Ocean Ecosystem with Canadian Sea Ice Biogeochemistry (CANOE-CSIB) and the Pelagic Interactions Scheme for Carbon and Ecosystem Studies volume 2 (PISCESv2). Additionally, differences in the Louvain–La-Neuve sea ice modules versions 2 and 3 (LIM2 and LIM3) are highlighted for the studied region. We focus on the Gulf of Amundsen and Baffin Bay.The model results are compared to satellite-based chlorophyll-a, sea-ice concentration and temperature data for performance assessment. All models compare well with the satellite observations. Seasonal patterns in the carbonate system are similar between models. However, variations in each model’s carbon chemistry exist. We show differences in monthly carbon cycle dynamics, dissolved inorganic carbon, alkalinity and partial pressure of carbon dioxide, to highlight impacts of each model’s complexity in their carbon modules.
Modelling the carbon system in a rapidly changing Arctic Ocean
Johanna Länger, Nadja Steiner, Adam Monahan, Tessa Sou
Corresponding author: Johanna Länger
Corresponding author e-mail: jlanger@uvic.ca
The Arctic Ocean experiences rapid changes, most visibly the change in sea ice properties and seasonality. Together with changes in surface temperature, stratification, and freshwater addition by runoff, the changes in sea ice impact the marine carbon system. However, our understanding of the impacts by the changes on the carbon system is still evolving. We use CanOE-CSIB (Canadian Ocean Ecosystem–Canadian Sea Ice Biogeochemistry) to highlight the spatial and temporal variations in the oceanic carbon system in the Canadian Arctic. CanOE-CSIB is a coupled sea ice–ocean biogeochemistry model with pelagic and sea-ice ecosystem components including carbon cycling. The model has been run over recent and future time periods (1979–2080) and evaluated with respect to ocean and sea-ice changes, ocean acidification and CaCO3 saturation states. The results indicate significant regional variability with respect to carbon fluxes and ocean acidification in the Arctic with some regions already perpetually undersaturated with respect to aragonite at the surface. The analysis highlights regional and interannual variability and the evolution over the recent past with strong sea-ice loss. while future projections indicate a continuation of the past trend. In areas with more persevering sea ice cover, the Carbon fluxes are much more sea ice dependent than regions close to the mainland, that are mostly influenced by runoff and temperature.
New insights on Arctic sea-ice ridges from the MOSAiC expedition – an overview
Mats A. Granskog, Evgenii Salganik, Benjamin Lange, Dmitry Divine, Morven Muilwijk, Yusuke Kawaguchi, Marcel Nicolaus, Polona Itkin
Corresponding author: Mats A. Granskog
Corresponding author e-mail: mats.granskog@npolar.no
Ridges compose a large fraction of the Arctic sea-ice volume, but are still the least studied and understood part of the Arctic ice pack, in part due the logistical challenges studying these ice masses. During MOSAiC focused ridge studies were conducted from winter to advanced melt in summer with a diverse set of methods, from manual drilling and sampling through electromagnetic mapping to automated observations and remotely operated vehicle (ROV) mapping of the ice underside. Both physical and biological sampling were conducted. Despite challenging conditions, e.g.with loss of instruments to ridging events, novel data sets of the temporal evolution of ridges were collected. Here we highlight some of the new findings. New insights into the consolidation, i.e. refreezing of water filled voids in the ridge keels, include evidence for either snow–slush or snow meltwater to significantly contribute to rapid consolidation of ridge keels. The exact mechanisms require further study. Rare observations over time during advanced melt also indicate complex and spatially varying melting of ridge keels, but overall more rapid melt of keels than adjacent level ice was observed. Thus ridge keels provide a significant but often overlooked contribution to the summer meltwater balance (both through melting but also through refreezing of meltwater in the ridge keel). Ridge keels also affect the lateral extent of meltwater layers below the ice, and thus also exert some indirect control of exchange between the ice and ocean. Furthermore, ridge keels can impact ocean mixing and atmosphere–ocean momentum transfer. Acoustic Doppler current profilers deployed upstream and downstream a large ridge reveal increased turbulent kinetic energy near the ridge keels, compared to under-level ice on the same floe. Surprisingly, however, at this particular ridge there were no significant differences in horizontal currents or turbulence between the fore and lee sides of the ridge. The negligible difference in turbulence can be accounted for by evanescent internal waves in the deep and well-mixed boundary layer, maintained by brine rejection due to the sea-ice growth during the winter. Given the large fraction of deformed ice, it’s probably time to pay closer attention to how well models capture ridge-related processes and whether these subgrid processes need to be better represented in sea-ice models. Do any of these processes matter on a climate-scale?
Observation and modeling of snow and land fast sea ice interaction in Young Sound, East Greenland
Bin Cheng, Naakka Tuomas, Timo Vihma, Yubing Cheng, Mikael Kristian Sejr
Corresponding author: Bin Cheng
Corresponding author e-mail: bin.cheng@fmi.fi
A thermistor string-based snow and ice mass balance apparatus (SIMBA) was successfully deployed on the landfast sea ice in Young Sound, East Greenland, in October 2020, and operated until April 2021. The SIMBA temperature data were used to derive snow depth and ice thickness. Monthly manual observations were used to validate the SIMBA results. The observed seasonal maximum snow depth and ice thickness were 80 cm and 120 cm, respectively. Ice bottom evolution retrieved from SIMBA temperature data agreed well with the manual observations. Snow surface revealed large temporal variations, most probably due to snow drift and snowstorms. The reliability of SIMBA temperature-based surface evolution remains to be validated. The data indicated that cold sea ice could resist the pressure of a heavy snow load before massive flooding occurs when holes or ice cracks suddenly appear in late spring. A thermodynamic snow and ice model was applied to simulate the snow and ice mass balance. The Copernicus Arctic Regional Reanalysis (CARRA) data were used as weather forcing. CARRA air temperature was higher than the locally observed surface air temperature. The main difference was 3.4°C and occasionally as large as 10°C. Based on the observations and modelling, we concluded that snow and ice interaction may be intensified under global warming and polar amplification. The impact of precipitation and oceanic heat flux are critical factors for snow–ice interaction. Due to strong insulation by the deep snowpack, the total ice mass balance was not very sensitive to air temperature. The oceanic heat flux played an important role in ice mass balance on a seasonal scale.
Wave impact on sea ice dynamics in the marginal ice zone using a coupled wave–sea-ice model
Guillaume Boutin, Timothy Williams, Christopher Horvat, Laurent Brodeau
Corresponding author: Guillaume Boutin
Corresponding author e-mail: guillaume.boutin@nersc.no
As sea ice extent decreases in the Arctic, surface ocean waves have more time and space to develop and grow, exposing the marginal ice zone (MIZ) to more frequent and energetic wave events. Waves can fragment the ice cover over tens of kilometres, and the prospect of increasing wave activity has brought a recent interest in their potential impact on the sea ice cover, which remains mostly unknown. Here, we introduce a new coupled framework involving the spectral wave model WAVEWATCH III and the sea ice model neXtSIM. neXtSIM can efficiently track and keep a memory of the level of damage of sea ice. We propose that the level of damage of sea ice increases when wave-induced fragmentation occurs. We use this coupled modelling system to investigate the potential impact of fragmentation on sea ice kinematics. To constrain the extent over which waves can impact the sea ice in our model, we evaluate the MIZ extent by comparing our model results to pan-Arctic wave‐affected sea ice regions derived from ICESat-2 altimetry over the period December 2018–May 2020. The model produces MIZ extent comparable to observations, especially in winter, but underestimates the MIZ extent in autumn. We estimate the potential impact of wave-induced fragmentation on ice dynamics, which the model suggests is important at short time scales and for some regions of the Arctic, such as the Barents Sea, as sea ice mobility increases in the aftermath of storm events.
Trends and variability from a sea ice thickness proxy in the Canadian Arctic, 1996–2021
Isolde Glissenaar, Jack Landy, David Babb, Stephen Howell, Geoffrey Dawson
Corresponding author: Isolde Glissenaar
Corresponding author e-mail: isolde.glissenaar@bristol.ac.uk
Sea ice thickness (SIT) is a key variable when characterizing an ice cover and its impact on the local environment, and provides important insight into how an ice cover is changing in response to climate change. Unfortunately, observations of ice thickness at appropriate spatial and temporal scales for climate research are sparse. Seasonal estimates of ice thickness from satellite altimeters only go back to 2003 and represent a rather short record for examination of long-term trends and variability. Furthermore, satellite altimeters have difficulty resolving ice thickness in coastal areas and either mask out or have a high degree of uncertainty over the Canadian Arctic Archipelago (CAA). We combine information from the Canadian Ice Service (CIS) ice charts and scatterometer backscatter data to create a proxy SIT product for the Canadian Arctic for November-April, including the CAA. We apply machine learning methods on these long-term remote sensing datasets trained on CryoSat-2 SIT observations to determine the relationship between sea ice stage of development, form of ice, backscatter and SIT. This machine learning model is used to create a SIT proxy-product for the Canadian Arctic covering the period 1996–021 (November–April), including SIT in the channels of the CAA, as well as the Beaufort Sea and Baffin Bay. Additionally, the model can be used moving forward to provide estimates of ice thickness, as ice charts and scatterometer imagery are available. The presented proxy SIT product is the longest available record for large-scale SIT in the Canadian Arctic and the first product that provides SIT in the channels of the CAA without the need for interpolation. We find an average sea ice thinning of 35 cm over the 25-year record in April, but with large spatial and interannual variability. The Beaufort Sea and Baffin Bay show significant negative trends during all months, though with peaks in January (–3.2 cm a–1) and March (–1.8 cm a–1), respectively. The Arctic Ocean Periphery shows thinning above 2 cm a–1 during all months but April, with a peak of –3.4 cm a–1 in December. The Parry Channel, which is part of the Northwest Passage and relevant for shipping, shows weaker thinning trends, but with high yearly variability. We will discuss the methods in obtaining the proxy SIT product and dive deeper into trends, variability, and processes affecting SIT in the region.
Towards a high-resolution multi-scale sea ice model combining continuum and DEM approaches
Andrei Tsarau, Wenjun Lu, Raed Lubbad, Sveinung Løset, Yuan Zhang
Corresponding author: Andrei Tsarau
Corresponding author e-mail: andrei.tsarau@ntnu.no
The understanding of sea-ice dynamics at both regional and local scales is crucial to comprehending the Arctic climate system. While continuum models have been widely used to simulate large-scale sea ice characteristics, such as the distribution of ice thickness, concentration and circulation over, e.g., the entire Barents Sea, they have limitations in accurately representing the behaviour of sea ice at local scales. discrete element models (DEMs), on the other hand, are well-suited for modelling the behaviour of individual ice floes but are limited by computational constraints. To overcome some of these limitations, we are developing an integrated model that combines the strengths of both continuum and DEM approaches. The proposed integrated model consists of a regional continuum elastic–viscous–plastic model (CICE) that sets the initial and boundary conditions for a local 3-D DEM, which runs at a kilometric scale (up to ~100 km). The local DEM simulates the behaviour of ice floes at high spatial and temporal resolution using the exact contact geometry and the material properties of the interacting floes. It provides information about local ice concentration, floe distribution and deformation features back to the continuum model. The resulting integrated model is expected to improve the understanding of sea ice dynamics by resolving possible sharp, heterogeneous differences in ice concentration, which are critical to sea-ice melting and ocean heat exchange. In the future, this program will be integrated with a ‘large-scale ice fracture model’ to simulate local ice deformation (e.g. ridging and lead opening) to enable the creation a high-resolution multi-scale sea ice model. The authors would like to thank the Research Council of Norway for financial support through the research project ‘Multi-scale integration and digitalization of Arctic sea ice observations and prediction models (328960)’.
Ben Redmond Roche, Martin King
Corresponding author: Ben Redmond Roche
Corresponding author e-mail: benjamin.redmondroche.2020@live.rhul.ac.uk
Sea ice algae play an important role in the Arctic Ocean ecosystem, driving primary production in the spring and sequestering carbon to the deep ocean. Up to 45% of Arctic Ocean primary production occurs in ice-covered areas; photosynthetically active radiation (PAR) is fundamental to driving this production. Sea ice, and particularly snow, strongly scatter light and reduce the amount of PAR transmitted to the ice–ocean interface. This study considers the effect that varying thicknesses of sea ice (0.2–3.5 m) and snow (0.05–1 m) have on the value of PAR transmittance at the ice–ocean interface for a winter, early spring, and summer scenario. When typical Arctic Ocean conditions (2 m thick sea ice and ~0.2 m thick snowpack) are considered for the winter, early spring, and summer scenarios there is an order-of-magnitude difference in the value of PAR transmission at the ice–ocean interface: 0.04%, 0.4% and 4%, respectively. The modelled values correlate within one standard deviation (winter and early spring scenarios) or two standard deviations (summer scenario) of the measured values. The results also indicate that simple exponential decay methods may lead to inaccurate results, and careful radiative transfer modelling is required to accurately predict PAR transmittance at the ice–ocean interface. Therefore, this study offers a novel mathematical technique to predict the value of PAR transmission at the ice–ocean interface. Coupled with year-round near-real-time sea ice and snow thickness remote sensing data, this technique may improve understanding of primary production and carbon budgets in the changing Arctic Ocean.
Hoyeon Shi, Gorm Dybkjær, Sang-Moo Lee, Suman Singha, Fabrizio Baordo, Byung-Ju Sohn
Corresponding author: Hoyeon Shi
Corresponding author e-mail: drive.hoyeon@gmail.com
To support assessing the performance and sensitivity of the Snow Microwave Radiative Transfer Model (SMRT), realistic input data of snow depth and sea ice thickness are required for the SMRT to simulate the brightness temperature. This study produced a daily snow depth and sea ice thickness dataset based on a method that simultaneously estimates snow depth and sea ice thickness from radar freeboard, snow surface temperature and snow–ice interface temperature. The concept of the simultaneous estimation method is to use the ratio of snow depth to sea ice thickness (hereafter referred to as α), which can be estimated from the snow surface and snow–ice interface temperatures, for converting CryoSat-2 radar freeboard into snow depth and sea ice thickness. The snow surface and snow–ice interface temperatures were derived from the advanced very high-resolution radiometer (AVHRR) and the advanced microwave scanning radiometer (AMSR) measurements, respectively. Three updates for the simultaneous estimation method have been made to enhance the quality of the product. First, a parameterization for the bulk sea ice density that depends on the ice freeboard portion and the sea ice type was implemented. Second, the empirical equation for estimating α was updated to reduce the retrieval period from a month to a day. Third, an empirical relationship that converts radar freeboard to total freeboard was found as a function of snow depth by matching CryoSat-2 and Operation IceBridge (OIB) data, and it was implemented to deal with potential systematic bias in the radar freeboard dataset. The dataset of snow depth and sea ice thickness on a daily time scale was produced for the 2011–22 period from January to March. The validation was done by comparing the constructed dataset to the OIB dataset and the upward-looking sonar measurements of the Beaufort Gyre Exploration Project (BGEP) mooring observation. Good consistency between the retrieval results and the validation datasets was found. The retrieved sea ice thickness agreed with other datasets from Copernicus Climate Change Service (C3S) and Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS). Besides, the retrieval results based on the new bulk sea ice density parameterization support the recent finding that the bulk density of multiyear sea ice is not as low as the widely used value of 882 kg m–2. This project was supported by OSI SAF and the National Center for Climate Research (NCKF) of Denmark.
Characteristics and composition of sea ice in the transpolar drift over the annual cycle
Marcel Nicolaus, Luisa von Albedyll, Mats A. Granskog, Christian Haas, Mario Hoppmann, Donald K. Perovich, Andreas Preusser, Matthew Shupe, Gunnar Spreen
Corresponding author: Marcel Nicolaus
Corresponding author e-mail: marcel.nicolaus@awi.de
Arctic sea ice has decreased in extent and thickness during all seasons. Also its physical properties changed to a younger and more seasonal ice pack. However, it is still challenging to characterize sea ice and snow properties and processes during all seasons in relation to feedbacks with the atmosphere and the ocean. As a result, numerical simulations and forecasts as well as satellite data retrieval algorithms still have large uncertainties. Many parameterizations are based on distinctions into first- (FYI) and second or multi-year sea ice (SYI) in order to cover main differences within the ice pack. At the same time, it seems that the observed changes in the pack ice request revisions of existing parameterizations. During the Multidisciplinary drifting Observatory for the Study of Arctic Climate, MOSAiC, sea ice and snow properties were observed over a full annual cycle in 2019/20. The measurements were performed in direct relation to atmospheric and oceanographic conditions with the aim of describing their interaction and closing observational gaps across the interfaces. Here we summarize and review the sea ice and snow conditions from formation in autumn to (partially complete) melt in summer. We present mean properties of key parameters ranging from the lowest atmosphere, through snow and sea ice, into the upper ocean. We present all data sets with measures of their spatio-temporal variability and uncertainties. The results indicate that the contrasts of FYI and SYI diminish along the transpolar drift from autumn to spring. Hence, commonly used differentiation between these two types might be less relevant, at least from the physical point of view. In contrast, a more explicit and detailed inclusion of pressure ridges and new ice types, as well as adaptations of snow distributions on sea ice are recommended to improve process descriptions and simulations. Advantages and disadvantages of different sea ice classifications are discussed for the Arctic. Finally, the aim is to provide suggestions on how to adapt the implementation of sea ice properties into numerical models and to provide data sets that ease comparisons with large-scale data sets, e.g. from remote sensing or re-analyses.
Evaluating ACCESS-OM2 zooplankton biomass estimates using empirical observations
Sylvie King, Pat Wongpan, Alex Fraser, Kerrie Swadling
Corresponding author: Sylvie King
Corresponding author e-mail: sylviek@utas.edu.au
In the Southern Ocean (SO) ecosystem, zooplankton are a crucial link between primary production and upper trophic level species, particularly in regions of sea ice cover where the seasonal formation and melt of ice drives distinct annual productivity cycles. Zooplankton biomass also broadly influences biogeochemical cycles, food web dynamics and energy flow within the SO. Therefore, it is important to understand how zooplankton biomass is responding to changing environmental conditions over a broad spatial and temporal scale to ensure effective management, monitoring and conservation of this ecosystem. The remote nature of the SO means in-situ observations of broad scale zooplankton dynamics are costly and time-consuming, especially in ice-covered oceans. Modelling is a powerful tool for overcoming such limitations, as estimations of multiple parameters can be obtained over large scales at a relatively high resolution. The new version of the Australian Community Climate Earth System Simulator global ocean–sea ice model (ACCESS-OM2) includes coupled sea ice and ocean biogeochemistry (World Ocean Model of Biogeochemistry and Trophic-dynamics: WOMBAT model). The model outputs include daily mean zooplankton biomass (mmol N m–3), meaning it has great potential as a tool for understanding the drivers of zooplankton biomass variability in Antarctica. However, model outputs must first be evaluated using empirical observations to ensure the modelled estimates can be confidently accepted. This project evaluates ACCESS-OM2 zooplankton biomass estimates within the marginal ice zoneof the Indian Ocean sector of the SO. Zooplankton counts collected by the Southern Ocean Continuous Plankton Recorder survey (SO-CPR) in the summer months between 1991 and 2020 were transformed into biomass estimates before being compared to the values predicted by the model over the same time period and geographical extent. Only the summer period was considered, as winter observations based on the SO-CPR are rare. After the model evaluation, ice-associated ecosystem dynamics were explored by examining the influence of sea ice on zooplankton biomass variability. Ultimately, this project provides novel insight into the efficacy of ACCESS-OM2 as a tool for understanding important biological-physical interactions in the SO.
Arctic sea ice type distribution from various microwave remote sensing products
Yufang Ye, Yanbing Luo, Mohammed Shokr, Signe Aaboe, Fanny Girard-Ardhuin, Fengming Hui, Xiao Cheng, Zhuoqi Chen
Corresponding author: Yufang Ye
Corresponding author e-mail: yeyf8@mail.sysu.edu.cn
Arctic sea ice type (SITY) variation is a sensitive indicator of climate change. This study analyzed eight daily SITY products from five retrieval approaches covering the winters of 1999–2019, including purely radiometer-based (C3S-SITY), scatterometer-based (KNMI-SITY and IFREMER-SITY) and combined ones (OSISAF-SITY and Zhang-SITY). These SITY products were inter-compared against a weekly sea ice age product (NSIDC-SIA) and evaluated with five synthetic aperture radar images. The average Arctic multiyear ice (MYI) extent difference between the SITY products and NSIDC-SIA varies from -1.32×106 km2 to 0.49×106 km2. Among all, KNMI-SITY and Zhang-SITY in the QSCAT period (2002–09) agree best with NSIDC-SIA and perform the best, with smallest bias of -0.001×106 km2 in FYI extent and -0.02×106 km2 in MYI extent, respectively. In the ASCAT period (2007–19), KNMI-SITY tends to overestimate MYI (especially in early winter), whereas Zhang-SITY and IFREMER-SITY tend to underestimate MYI. C3S-SITY performs well in some early winter cases however exhibits large temporal variabilities as OSISAF-SITY. Factors that could impact performances of the SITY products are analyzed and summarized: (1) Ku-band scatterometer generally performs better than C-band scatterometer on SITY discrimination, while the latter sometimes identifies first-year ice (FYI) more accurately, especially when surface scattering dominants the backscatter signature. (2) Simple combination of scatterometer and radiometer data is not always beneficial without further rules of priority. (3) The representativeness of training data and efficiency of classification are crucial for SITY classification. Spatial and temporal variation of characteristic training dataset should be well accounted in the SITY method. (4) Post-processing corrections play important roles and should be considered with caution.
Xiangshan Tian-Kunze, Lars Kaleschke, Stefan Hendricks, Marko Maekynen
Corresponding author: Xiangshan Tian-Kunze
Corresponding author e-mail: xiangshan.tiankunze@awi.de
Validation of satellite-derived products with ground-based measurements often reveals limitations and biases due to the mismatch between point-scale ground observations and footprint-scale satellite observations. The sea-ice thickness product derived from ESA’s Soil Moisture and Ocean Salinity mission (SMOS) has a coarse resolution of more than 35 km at nadir, whereas the validation and verification datasets from upward-looking sonars (ULS) and moderate resolution imaging spectroradiometer (MODIS) have a resolution of between several meters and 1 km. Here, we apply an extended triple collocation (ETC) method to solve this upscaling problem. We collocate sea-ice thickness data from SMOS, ocean-ice models, another independent satellite MODIS, and ULS measurements to estimate the RMSE and correlation coefficient of the different datasets referring to the unknown truth. The merged sea-ice thickness product from SMOS and CryoSat2 (CS2SMOS) is also evaluated using the ETC method. Our analysis suggests that at different validation sites the RMSEs of both SMOS and CS2SMOS data are less than 20 cm, with a correlation coefficient to the unknown truth higher than 0.7. Furthermore, SMOS sea-ice data showed better performance during the freeze-up period than the late winter.
Two decades (2000–23) of pan Arctic meltpond fraction data
Niklas Neckel, Anja Rösel, Lars Kaleschke, Gerit Birnbaum, Christian Haas
Corresponding author: Niklas Neckel
Corresponding author e-mail: niklas.neckel@awi.de
Melt ponds are influencing the Arctic energy budget as they strongly reduce the surface albedo of sea ice. It is therefore highly important to monitor their temporal and spatial evolution. Here we build on the work of Rösel and Kaleschke (2012) to extend their time series of moderate resolution image spectroradiometer (MODIS) melt pond estimates to the present. To do so we make use of a spectral unmixing algorithm implemented via a neural network to reduce computational costs. The results will be compared to classification results of helicopter-borne camera data acquired during the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Furthermore, we will apply classification results from the modular aerial camera system (MACS) newly employed on AWI’s research aircrafts to validate the MODIS results on a larger scale. The derived time series of 23 years meltpond data will be carefully analyzed for any trends, both in the temporal and spatial domain, and might be of interest to better parametrize sea ice models.
Ocean eddies drive heterogeneity in the sea-ice growth
Josué Martínez Moreno, Camille Lique, Claude Talandier
Corresponding author: Josué Martínez Moreno
Corresponding author e-mail: josue.martinez.moreno@ifremer.fr
Large lateral gradients in salinity and temperature are commonly found in the marginal ice zones leading to the emergence of ocean eddies in these zones. Previous studies have shown the impact eddies may have during the ice melting phase, when processes such as advection, lateral and subsurface heat transport, and changes in heat fluxes in the mixed layer modify the melting rate of sea-ice. Yet, it remains unclear if eddies could also play an important role during the freezing phase, by modulating the growth and evolution of sea ice. Here, we explore the dependency of the sea ice growth on the presence and varying intensities of eddy fields using an idealized periodic zonal channel simulation (NEMO + SI3). We show that an increase in the strength of the eddy field leads to a more spatially heterogeneous sea-ice cover during the freezing period. Since ice freezing depends on the ocean surface reaching freezing point, the presence of eddies through steering and mixing of water properties can induce heterogeneity in the ice, heat and salt fluxes at the ice–ocean interface. Our results also suggest that the sea ice conditions can keep a memory of the eddy-modulated growth over a season: a stronger eddy field during summer also modifies ice production during the following winter. These processes may become crucial in the Arctic, where a rapid decline of sea-ice and a transition towards an open-ocean regime are observed. Therefore, exploring the sea-ice eddy interactions may become increasingly important to the future formation and evolution of the sea-ice.
Bounds on the macroporosity of sea ice pressure ridges
Sönke Maus
Corresponding author: Sönke Maus
Corresponding author e-mail: sonke.maus@ntnu.no
The mass and heat balance of Arctic sea ice is strongly related to the deformation of level ice by ridging, and the amount of ice stored in sea ice ridges and rubble fields. The ridge formation process, in particular its dependence on the physical (floe-scale) properties of level ice from which the ridge forms, is still not fully understood. One important property of sea ice ridges, related to fracture and packing of sea ice floes during ridging, is the macroporosity or void fraction. Its relevance for sea ice modelling is obvious, as it is proportional to the ice mass and latent heat stored in a ridge. While macroporosity has been observed in field and laboratory studies, a concise theory of its evolution is still lacking. The present work is a step to close this gap. It combines recent advances in the theory of particle packing with concepts of sea ice fracture mechanics and thermodynamics to predict (loose and dense packing) bounds of the macroporosity of ridged sea ice and rubble. The approach allows to evaluate the dependence of these bounds on the growth conditions and physical properties of level sea ice (thickness, mechanical and thermodynamic properties, microstructure). A comparison of macroporosity predictions to observations from field and laboratory studies shows good agreement, and indicates the potential of the approach to predict the initial porosity of a ridge after its formation. The predicted porosity, and related internal ridge morphology, can serve as input to modelling of the consolidation and property evolution of ridges and rubble fields, and their proper account in large scale sea ice models.
Vera Schlindwein, Shuquan Li, Mechita Schmidt-Aursch
Corresponding author: Vera Schlindwein
Corresponding author e-mail: Vera.Schlindwein@awi.de
Stress and deformation of sea ice produces icequakes and other seismic emissions that can be exploited to monitor the stress state of the sea ice cover. Ambient and transient seismic wavefields recorded by seismic sensors on ice floes have also been used to estimate the thickness and elastic properties of sea ice. During the first year-round deployment of broadband ocean bottom seismometers at a deep-water location in the Laptev Sea, Arctic Ocean, we accidentally discovered that the seismic noise emissions of sea ice are recordable at water depths of 4000 m. Thus, information on the state of the sea ice cover can also be gained from spectral analysis of the ambient seismic noise recorded at the seafloor. Microseisms with periods of 2–5 s are strongly seasonally modulated and appear when the Laptev Shelf area becomes ice-free. At high frequencies (6–50 Hz), short, distinct noise bands appear in winter. We associate these signals with noise generated by the sea ice over an area at least tens of square kilometers in extent. To analyze the seasonality of the noise sources, we extracted the spectral power in various frequency bands and compared it with variations of the significant wave height from Wave Watch III hindcast models and of ice concentration and drift from satellite data. This comparison revealed that sea-ice-related noise decays suddenly in late May while sea ice concentration is still 100%, suggesting that the physical properties of the sea ice change at this time prior to break-up. Likewise, sea ice only gradually develops its noise-generating capabilities after the freezing period, probably when compression of ice floes contributes to their thickening. During autumn, several swell events cause large-amplitude microseisms and simultaneously high-frequency noise although ice noise is otherwise not present in this season. Ice concentration decreases following the swell events, showing the impact of swell on the state of the sea ice during the freezing season.
Modelling ridging on local scales using discrete element methods
Marek Muchow, Arttu Polojärvi
Corresponding author: Marek Muchow
Corresponding author e-mail: marek.muchow@aalto.fi
When sea ice is moved by wind and currents, ice ridges can form either due to compression or shear. Ridging at local scales is a factor influencing the strength of the larger-scale sea-ice field. However, the relation of ridging forces at local scale and the ice strength used, for example, in contemporary Earth system models at large scale remains unclear. To investigate ridging of sea ice in detail, we use the Aalto University in-house three-dimensional discrete-element-method simulation tool. The tool enables modeling deformable, multi-fracturing, ice floes. As the floes come into contact, they deform and fail forming ridges. During the simulations, we can gauge ridging forces and make detailed observations on ridging processes. We validate our model by showing that ridging load values from the simulations fit measurements from experiments performed in the Aalto Ice and Wave tank. We additionally present preliminary results from a parametric study on ridging.
Thomas Krumpen, Jakob Belter, Christian Haas, Stefan Hendricks, Jörg Hartmann, Christof Lüpkes, Mira Suhrhoff
Corresponding author: Thomas Krumpen
Corresponding author e-mail: tkrumpen@awi.de
The thickness, deformation and surface roughness of Arctic sea ice play a crucial role in the Earth’s climate system. For more than two decades, these parameters have been routinely measured in the Arctic by the Alfred Wegener Institute (AWI) using aircraft and helicopters equipped with an electromagnetic sensor and a laser altimeter. In this presentation, we will report on the interannual variability and trends observed in key regions such as Fram Strait and the Lincoln Sea. Our results show that both sea ice thickness and, surprisingly, surface deformation (sail frequency) have decreased over the last two decades. The decrease is particularly pronounced in the last ice areas. The changing sail frequency is a new and intriguing finding, and the implications for energy and mass balance are still being explored. In order to understand the mechanisms responsible for the observed changes in sea ice thickness and deformation, we trace the overflown ice back in time and link airborne records to satellite-derived parameters extracted along the tracks. Our analysis shows that sea ice age is an important component influencing sail frequency, while thickness anomalies are likely a consequence of an increased influence of upward-directed ocean heat flux in the eastern marginal ice zones, termed Atlantification.
Arctic rapid sea ice loss events in model simulations
Annelies Sticker, François Massonnet, Thierry Fichefet, Alexandra Jahn, Christopher Wyburn-Powell, Daphne Quint, Makayla Ortiz, Erica Shivers
Corresponding author: Annelies Sticker
Corresponding author e-mail: annelies.sticker@uclouvain.be
The summer Arctic sea ice is projected to disappear completely by the middle of the century in response to anthropogenic greenhouse gas emissions, according to simulations conducted with the latest global climate models. The decrease in summer Arctic sea ice extent is marked by periods of rapid ice loss, known as rapid ice loss events (RILEs), which are expected to become more frequent in the coming decades. However, the causes of RILEs are not well understood and it is difficult to predict their occurrence a season to several years ahead. It is essential to improve our understanding of these events and their potential impacts on ecosystems and societies, as the rate of sea ice decline can affect the ability to adapt to rapid change. To gain a better understanding of RILEs, we conducted an analysis using climate simulations from the Coupling Model Intercomparison Project phase 6 (CMIP6) and from the CLIVAR large ensemble models using CMIP5 forcing. Our results show that the frequency of RILEs increases as the Arctic sea ice extent diminishes, and the probability of observing a RILE is highest during the period 2025–30. Moreover, the observed September Arctic sea ice extent is critically approaching the value corresponding to the peak of probability of occurrence of RILEs. This suggests that we may be on the verge of a RILE, after a slowdown in sea ice loss since the early 2010s. In the future, we plan to identify the climatic conditions that are favorable for the formation of RILEs, with the goal of predicting the probability of their occurrence in real-time. We also aim to study the impacts of these rapid ice loss events on the wider climate system.
Seasonal prediction of NorCPM in the regional Antarctic sea ice
Yongwu Xiu, Yiguo Wang, Hao Luo, Qinghua Yang
Corresponding author: Yiguo Wang
Corresponding author e-mail: luohao25@mail.sysu.edu.cn
The Norwegian Climate Prediction Model (NorCPM), which combines the fully coupled Norwegian Earth System Model and the Ensemble Kalman Filter, is a state-of-the-art climate prediction system. Previous studies have investigated its seasonal sea ice prediction skill in the Arctic. On the other hand, compared to the Arctic, seasonal Antarctic sea ice predictions have received relatively little attention. In this study, we assess the seasonal Antarctic sea ice prediction skill of NorCPM and the predictability of regional Antarctic sea ice (e.g. in the Weddell Sea and the Ross Sea). We utilize several sets of retrospective seasonal predictions initialized in January, April, July and October in the period of 1985–2010. Each prediction set was initialized by weakly coupled data assimilation (updating the ocean state alone) when assimilating oceanic observations or strongly coupled data assimilation (jointly updating the sea ice and ocean states) when assimilating sea ice observations or both ocean and sea ice observations. The results will provide insights into the impact of ocean and sea ice initialization on Antarctic sea ice prediction, which will help to understand the mechanisms of regional Antarctic sea ice predictability.
Do melt-ponds matter? Sea-ice parametrizations during three different climate periods
Rachel Diamond, David Schroeder, Louise Sime, Jeff Ridley, Danny Feltham
Corresponding author: Rachel Diamond
Corresponding author e-mail: radiam24@bas.ac.uk
The impact of melt-ponds on sea-ice has been observed and documented. However, despite the development of different melt-pond parameterizations for use in models, there has been a lack of studies showing their impacts on Arctic climate. Here, we rectify this using the general circulation model HadGEM3, one of the few models with a detailed explicit melt-pond scheme. We identify the role of melt-ponds on the sea-ice and their impacts on the climate. We run a set of constant forcing simulations for three different periods and show, for the first time, using mechanistically different pond-schemes can lead to very significantly different sea-ice and climate states. For example, under near-future conditions, an implicit pond-scheme never yields an ice-free summer Arctic, whilst the explicit pond-scheme yields an ice-free Arctic 35% of years and raises autumn Arctic air temperatures by 5–10°C. We explain this in terms of the sea-ice state, and interactions of the ice with ocean and atmosphere. This shows that changes to physical parametrizations in the sea-ice model can have large impacts on simulated sea-ice, ocean and atmosphere.
Béatrice Lessard-Hamel, Marcel Babin, Simon Thibault, Guislain Bécu
Corresponding author: Béatrice Lessard-Hamel
Corresponding author e-mail: beatrice.lessard-hamel.1@ulaval.ca
Gaining microscopic insight into the internal structure and biology of sea ice has traditionally been limited to destructive and extrusive ice-core sampling methods. To make progress in the exploration of sea-ice micro-habitats, and in the study of sea-ice microorganisms with minimal disturbance, we are developing an innovative in-situ microscopic imaging system inspired by medical endoscopes to observe the living microorganisms directly within sea ice. This endoscope will be used to determine how these organisms thrive inside the sea ice without extracting them from the environment. The complex and heterogeneous nature of sea ice, including its water crystal lattice, brine channels, air bubbles and various impurities, presents numerous engineering challenges for the development of this imaging system. A suitable solution is an oblique back-scatter microscope probe. This phase contrast technique used in tissue optics provides reflective gradient images of thick scattering samples. A quantitative phase reconstruction can be achieved via deconvolution by modelling the system’s transfer function if the sea ice optical properties are known. A ray-tracing simulation in Zemax was performed to evaluate the feasibility of this imaging technique, and a field-proof endoscope probe was built and tested as a proof of concept. Despite the challenges related to the fragile nature of the sea-ice matrix, results from the lab and field tests are encouraging and provide a foundation for further system development. The hardware conception of the endoscope probe, the computational phase reconstruction algorithm and the results of our simulations, lab and field tests are presented. Our goal is to demonstrate the potential for this new in-situ microscopic imaging system to revolutionize the way we study sea-ice and provide a deeper understanding of its complex microstructures and living microorganisms.
Modulation of future sea ice loss by ocean heat transport
Jake Aylmer, David Ferreira, Daniel Feltham
Corresponding author: Jake Aylmer
Corresponding author e-mail: j.aylmer@reading.ac.uk
Projections of Arctic and Antarctic sea ice suffer large uncertainties arising from inter-model spread. Studies point to ocean heat transport (OHT) as a major driver of sea ice on multidecadal timescales. Yet, the factors setting the sea ice sensitivity to OHT and its role in model spread remain poorly understood. This work brings new insight through an analysis of CMIP6 simulations from multiple models. We verify a strong relation between OHT and sea ice cover in the pre-industrial through historical period, as identified in prior literature. The relation exists in both hemispheres, albeit with radically different mechanisms. In the future simulations, we find OHT increases in roughly half of simulations analysed, enhancing sea ice retreat, while in some cases OHT decreases enough to offset sea ice loss entirely. The multi-model, linear relationship between sea ice and OHT collapses to a single equation derived from a toy model of the polar climate system, with the aforementioned mechanisms and atmospheric role built in. This reveals the emergent sensitivity of sea ice to OHT as a constraint on large-scale energy conservation. This result also holds for future projections, implying a critical role of the ocean in long-term sea ice simulation.
Antarctic sea ice types with active and passive microwave satellite observations: first improvements
Christian Melsheimer, Gunnar Spreen, Mohammed Shokr, Yufang Ye
Corresponding author: Christian Melsheimer
Corresponding author e-mail: melsheimer@uni-bremen.de
In order to properly understand and model the evolution of the sea ice cover and its interaction with the global climate system, we need detailed information about sea ice, i.e. not only its extent but also, for example, its type, the property discussed here. We can broadly distinguish three sea ice types that have different dynamic and thermodynamic properties: young ice (YI, thin/smooth new ice), first-year ice (FYI, formed during one cold season), and multiyear ice (MYI, which has survived at least one melt season). The last is of particular interest as it is usually thicker than other ice types (thus, takes more time to melt), much less saline, and may accommodate a unique ecosystem. Sea ice types in the Antarctic, until recently, have not been monitored much because of the lack of appropriate remote sensing methods. While the Antarctic sea ice is greatly dominated by FYI, there are, nevertheless, considerable amounts of MYI, in particular in the Weddell Sea. We have recently adapted a method to retrieve sea ice types from active and passive microwave satellite data, originally developed for the Arctic, to Antarctic conditions and produced a first dataset spanning the freezing seasons from 2013 until now. The method uses several channels of the microwave radiometer AMSR2 on the Japanese satellite GCOM-W1, as well as radar backscattering data from the scatterometer ASCAT on the European MetOp satellites. Based on sample distributions representative of the microwave emission and scattering of the three ice types (and open water) in the used channels the method retrieves the surface fraction of each ice type in each grid cell. A correction for the effect of melt freeze processes and snow metamorphism that modify the radiometric signatures and cause misclassification of the ice types is then applied. However, the first results still show misclassifications of ice types in particular in the marginal ice zone, which are not properly corrected by the second step of the method. One reason for this is that the samples for the radiometric and scattering behaviour of the different ice types are not representative enough as they do not cover enough subtypes, especially pancake ice. Here we investigate the effect of extending the sample distribution data, i.e. including more ice subtypes under more diverse conditions. This work contributes to the explanation of the different response of sea ice in the two polar regions to climate change.
Satellite remote sensing of snow on Antarctic sea ice with microwave radiometry
Christian Melsheimer, Philip Rostosky, Gunnar Spreen
Corresponding author: Christian Melsheimer
Corresponding author e-mail: melsheimer@uni-bremen.de
Snow on sea ice has a large effect on the heat and energy fluxes because it is a strong thermal insulator, is very bright, and a thick snow layer even influences the freeboard of the underlying ice. Therefore, comprehensive and up-to-date data about the variable snow layer on sea ice are very much sought after, which makes satellite remote sensing of snow on sea ice an important topic. Until now, more research has gone into snow on Arctic sea ice, and also the amount of direct snow measurement data from the Arctic is much larger than the amount of data from the Antarctic. Therefore, here we want to concentrate on the Antarctic. Several, conceptually different, satellite remote sensing methods for snow on sea ice have been developed. While an indirect method, snow depth retrieval from microwave radiometers has the advantage of providing data back to the 1970s or 1990s depending on the used frequencies. Here, we evaluate different methods based on satellite-based microwave radiometer data. Besides a well-known method using brightness temperatures (TBs) measured at 19 and 37 GHz which works on first-year ice (FYI), there is a more recent one using 7 and 19 GHz TBs that can be applied on both FYI and multiyear ice in the Arctic. We have applied these methods in several versions to the Antarctic, using data from the satellite radiometer AMSR2 (Advanced Microwave Scanning Radiometer, on the Japanese Satellite GCOM-W1), and intercompare the results and also compare them to airborne snow depths measurement data from two flight campaigns (NASA Operation Ice Bridge).
Summertime rapid sea ice loss events on sub-seasonal timescales
Jake Aylmer, Daniel Feltham, John Methven, Ambrogio Volonté
Corresponding author: Jake Aylmer
Corresponding author e-mail: j.aylmer@reading.ac.uk
Arctic sea ice sometimes undergoes localized, very rapid retreat on timescales of days to weeks. These very rapid ice loss events (VRILEs) are poorly forecasted and their underlying physical drivers are not well understood. We analyse VRILEs occurring during the melt season in a simulation (1980–2022) with the sea ice model CICE forced by atmospheric reanalyses. Our configuration includes novel marginal ice physics, such as an atmospheric and oceanic form drag scheme, that have been shown to enhance the fidelity of sea ice simulation. Most VRILEs are dominated by thermodynamic processes, despite accounting for climatological seasonal melt. However, some events occurring near the start or end of the melt season are driven by advective redistribution of the ice, often associated with the presence of a cyclone. We illustrate this with representative case studies and generalize the results to all simulated VRILEs by relating the dominant contributions to the sea ice area tendencies to atmospheric diagnostics during each event. Our results highlight possible improvements to operational forecasting of the Arctic environment which may benefit stakeholders such as the shipping industry.
In situ observations of the thermal expansion coefficient of sea ice
Larson Kaidel, Christopher Polashenski
Corresponding author: Larson Kaidel
Corresponding author e-mail: Larson.M.Kaidel.TH@dartmouth.edu
As first year sea ice (FYI) becomes more dominant in the Arctic sea ice cover, the properties of FYI become more important to quantify. As a two-phase material, sea ice exhibits a complex thermal response, potentially enhanced by the high surface salinity of FYI. We seek to quantify this as a thermal expansion coefficient dependent on temperature and salinity. Laboratory studies have come to varying conclusions, differing because of the assumption of connectivity of the ice to its surroundings. Studies at larger scales have been unable to corroborate laboratory and theoretical results that assumed an entirely closer or open system, suggesting a more complex set of variables. This study examines in situ measurements of the thermal deformation of sea ice over scales from 0.1–1.5 km at ice temperatures from –2–18°C. We find that the observed thermal expansion at these scales differs from laboratory observations. A theoretical model is proposed to match the observed expansion and contraction with a physical understanding of providing a function for the thermal expansion coefficient of sea ice at geophysical scales. The function will be incorporated into a mechanical model for the stress and strain of sea ice. The findings of this study are expected to improve the understanding of underlying dynamics in sea ice models with the aim of enhancing models built on remote sensing data assimilation.
Frazil ice in CTDs: effects on measurements of supercooling
Maren E. Richter, Inga J. Smith, Jonathan R. Everts, Peter Russell, Pat J. Langhorne, Greg H. Leonard
Corresponding author: Maren E. Richter
Corresponding author e-mail: maren.richter@otago.ac.nz
Salinity effects of particles entrained into conductivity cells have previously mainly been studied in the context of suspended sediment. Particles influencing conductivity cells can also be small ice crystals (frazil) that may form in supercooled water. The detection of supercooled water depends on accurate, high precision temperature, salinity and pressure measurements. As it is currently not possible to measure salinity in situ, the standard procedure is to measure conductance over a known volume and calculate salinity. Frazil ice entrained into a conductivity cell changes the volume of conductive fluid in the conductivity cell, thus changing the conductivity, salinity and supercooling measurements. We present results on the effect of entraining microplastic into a Sea-Bird Electronics (SBE) conductivity cell to simulate the effect of frazil. We show that particle volumes comparable to frazil volumes observed in the ocean change the measured conductivity and led to changes in calculated supercooling between 0.3 mK and 10 mK, possibly up to the same order of magnitude as naturally observed supercooling in the ocean. Further, we demonstrate that where supercooling is present, natural frazil ice concentrations can have an appreciable effect on parameters calculated with both the EOS-80 and TEOS-10 equations of state of seawater. Thus, to ensure accurate measurements in locations of very high frazil concentration, the entrainment of frazil needs to be prevented, which is not possible with methods currently available, or corrected for. An example for such a correction is given and could be modified to be applicable to other particles, e.g. sediment.
Improved sea ice drift estimates from enhanced-resolution passive microwave data
Walter N. Meier, J. Scott Stewart, Mark A. Tschudi
Corresponding author: Walter N. Meier
Corresponding author e-mail: walt@colorado.edu
Sea ice drift is a key element of the seasonal and long-term evolution of the sea ice cover. Drift can be estimated from satellite imagery via cross correlation methods where features are matched between two coincident images separated in time. Passive microwave imagery has long been used as a source for drift estimates because of its complete daily coverage and all-sky capability. However, these advantages come with the significant limitation of coarse spatial resolution. Historically, passive microwave data is gridded at 12.5 km or 25 km (although new sensors have a resolution as high as 5 km for some frequencies). This limits precision of the drift estimates and results in a ‘granular’ motion field. Visible and infrared sensors have finer spatial resolution (on the order of 1 km) but are limited to clear sky conditions. SAR sensors have high resolution and the all-sky capability, but have historically had limited spatial coverage. The National Snow and Ice Data Center has distributed an interpolated sea ice motion climate record, starting in 1979. It is largely based on relatively low-resolution passive microwave data, augmented by buoy data and other sources. Here, we present new drift vectors derived from enhanced resolution passive microwave data. Resolution enhancement is obtained through optimal combination of overlapping sensor footprints using signal processing techniques. The method yields a gridded spatial resolution up to 3.25 km, substantially finer compared to the earlier gridded products. Thus, motion estimates are less granular and better capture smaller-scale drift. In comparisons with buoy data, the enhanced resolution motions have errors that are ~30–50% lower than motions from the standard passive microwave data. These new drift vectors promise a significant improvement to NSIDC’s long-term climate record of drift. There will also be improvement in drift-derived Lagrangian tracking of parameters such as sea ice age. This presentation is dedicated to Charles W. (‘Chuck’) Fowler, the progenitor of NSIDC’s sea ice motion and age products, who died on 12 February 2023.
Drivers of interannual fast-ice variability in McMurdo Sound: an investigation on multiple scales
Maren Elisabeth Richter, Greg H. Leonard, Inga J. Smith, Pat J. Langhorne, Matthew Parry
Corresponding author: Maren Elisabeth Richter
Corresponding author e-mail: maren.richter@otago.ac.nz
The fast-ice cover in McMurdo Sound has been remarkably stable since the earliest records more than 100 years ago. This is likely due to supercooled water flowing out from under the McMurdo Ice Shelf, which allows the sea ice to grow through heat loss to the ocean, as well as to the atmosphere. We will present a dataset of fast-ice thickness and extent covering the years 1986–2022. We will connect this to atmospheric and ocean drivers on time scales from events to seasons in order to provide a baseline of the interannual variability in fast-ice thickness and the formation/break-out history. This provides one of the longest studies of drivers of interannual fast-ice thickness variability from high-quality, in situ observations. Our work highlights the drivers most likely to influence fast-ice presence and thickness in McMurdo Sound. Thicker fast ice is related to lower temperatures, higher average off-shore winds and lower offshore storminess. Fast-ice formation and winter break-out is connected to the severity and timing of southerly storm events. Future extreme events and long-term trends can be assessed against the baseline presented here, helping us to better understand the balance between ice, ocean, and atmosphere. Further, we provided information on gaps in our understanding of regional fast-ice processes, which will hopefully contribute to future work towards a model with regional predictive capability of fast-ice in McMurdo Sound.
Yijun Yang, Chao Min, Hao Luo, Frank Kauker, Robert Ricker, Qinghua Yang
Corresponding author: Hao Luo
Corresponding author e-mail: luohao25@mail.sysu.edu.cn
Sea ice export through the Fram Strait is crucial in the dynamic evolution of Arctic sea ice and can further modulate Arctic sea ice mass balance as well as the ocean thermohaline circulation. In this study, based on outputs from a parameter-optimized and fully physical ocean-sea ice coupled model and sea ice age observation, we estimate sea ice volume (SIV) flux and its age evolution via the Fram Strait. The estimate of mean annual SIV flux is about 1605±315 km3 a–1 without a significant trend for 1979–2021. Combining with sea ice age data, the variation of the sea ice age and its corresponding SIV flux are obtained for 1984–2020. The SIV flux of first-year ice significantly increases as expected, but it still contributes very little to the total flux in the 2010s, with a proportion of 3.5%. SIV fluxes of different ages in multi-year ice present diverse variations. The proportions of second-year ice and third-year ice in the annual SIV flux show an extreme increase from 6.8% and 25.0% in the 1980s to 49.0% and 38.8% in the 2010s, respectively, while the proportions of fourth-year ice and fifth-year and older (5+-year) ice significantly decrease from 22.8% and 45.0% in the 1980s to 7.1% and 1.6% in the 2010s, respectively. Meanwhile, the prevailing age of annual volume export via Fram Strait shifts from fourth-year and 5+-year ice to second-year and third-year ice around 2007/08. It’s worth noting that the variation in Fram Strait ice export modulates the variation in Arctic SIV prior to 2008, but the reverse is true after 2008, indicating a decreasing influence of Fram Strait SIV export on Artic SIV variability with decreasing sea ice age. The results are beneficial to promote the understanding of the evolution of Fram Strait SIV export under the warming Arctic.
Solar heat partitioning at the MOSAiC Central Observatory
Don Perovich, Madison Smith, Melinda Webster, Bonnie Light, David Clemens-Sewall, Chris Polashenski, Marika Holland, Felix Linhardt, Amy MacFarlane, Chris Cox, Matthew Shupe
Corresponding author: Don Perovich
Corresponding author e-mail: donald.k.perovich@dartmouth.edu
The partitioning of incident solar irradiance between reflection to the atmosphere, absorption in the ice and transmission to the ocean impacts the surface heat budget, the upper ocean heating, and the magnitude of the surface, internal, bottom and lateral ice melt. Solar partitioning at the MOSAiC Central Observatory was estimated by assimilating observations with a two stream radiative transfer model. Data sources include observations of incident solar irradiance, albedo, surface state, snow depth, ice thickness and pond depth. The temporal evolution of solar partitioning at specific sites and the spatial variability along transect lines were determined. There was a slow increase in absorption during spring due to increasing incident solar irradiance and a steady albedo. The largest amount of absorbed solar heat was in summer due to increasing incident solar irradiance and decreasing albedo due in large part to melt pond formation. There was a rapid decrease in absorbed solar heat during late summer as incident irradiance decreased and albedo increased from freezeup and snowfall. Ponds absorbed more than twice as much solar heat as bare ice. On 25 July, ponds covered about 18% of the area and contributed roughly 50% of the absorbed solar heat.
Challenges of dedicated snow modeling in high latitudes
Daniela Krampe, Frank Kauker, Marie Dumont, Andreas Herber
Corresponding author: Daniela Krampe
Corresponding author e-mail: daniela.krampe@awi.de
For reliable sea ice modelling, the overlying snow cover plays an important role. The snow insulates the underlying sea ice from the cold atmosphere and inhibits sea ice growth in autumn. In summer, the insulating properties and high albedo of the snow cover reduce sea ice melt. However, many sea ice models treat the overlying snow cover only very roughly, for example by using a constant snow density and conductivity. This approach obviously cannot reflect the changing properties of the snow cover throughout the year. In addition, the existing snow models have many weaknesses in simulating snow in the polar regions. This is already evident when the models are used to simulate snow on polar land without taking into account the complex feedbacks between sea ice and snow. So before we can adequately simulate snow on sea ice, snow modelling on land in the polar regions must first be improved. Another challenge is the use of appropriate surface forcing data. Since in-situ atmospheric data are limited in the polar regions, atmospheric reanalyses are often used. Various global and regional reanalysis products are available here. To ensure reliable model results, the strengths and weaknesses of the forcing data used should be known. We present results from a case study conducted on land in Northeast Greenland. We show results of the adaptation of the alpine snow model Crocus to the harsh Arctic conditions. We also investigate how representative the global reanalysis ERA5 and the new regional reanalysis CARRA are. ERA5 is widely used to drive models of snow and ice in the Arctic but few results are yet available for CARRA. These analyses will help to further develop snow modelling in the Arctic and eventually a better representation of snow in sea ice models.
Towards quantifying frazil ice using retrievals from an acoustic profiler, a camera and plume models
Nina Caldarella, Gregory H. Leonard, Inga J. Smith, Lars H. Smedsrud, Max Thomas, Eamon Frazer
Corresponding author: Nina Caldarella
Corresponding author e-mail: nina.caldarella@postgrad.otago.ac.nz
Frazil ice nucleates in supercooled water underneath ice shelves (ice shelf water). Less is known about what is underneath ice shelves than about the surface of the moon, while this zone and its inhabitants may be very vulnerable to changes in ocean temperature and circulation due to global warming. Earlier and on-going research offers a range of models for frazil-laden ice shelf water. Only recently have direct observations indicated the presence and effects of frazil-laden ice shelf water in McMurdo Sound. Additionally, recent efforts on the development of an acoustic water column profiler (AZFP) with the purpose of retrieving parameters of a frazil ice crystal size distribution have resulted in data that can be used with the earlier models for frazil-laden ice shelf water. Validating and constraining the models using AZFP retrievals is in progress. This will quantify ice shelf water parameters more accurately and help to better understand the significance of including frazil ice in larger scale models. This is a logical and necessary step to predict the future state of frazil ice and super cooled water on a warming planet. In this talk the first results from the measurements from the 2022 field season in McMurdo Sound will be presented and evaluated with tide model outputs and previous modelling studies.
Projections of a summer ice-free Arctic: a review of current climate model projections
Alexandra Jahn, Marika M Holland, Jennifer E Kay
Corresponding author: Alexandra Jahn
Corresponding author e-mail: alexandra.jahn@colorado.edu
The loss of summer sea ice has put the Arctic on a trajectory to ice-free conditions across the Arctic Ocean in September for the first time in many thousands of years. Many studies have assessed the probability and likely occurrence of such ice free conditions over the past few years, albeit with often slightly different definitions of what constitutes ‘ice-free’ conditions. Here, we present a review of the published literature on the subject, as well as show updated analysis using the CMIP6 model output. Among the things we show is that climate models have shown that the timing of the first ice-free Arctic will be determined by internal variability, not scenario differences. That makes the first occurrence of ice-free conditions challenging to predict, but CMIP6 models show it is likely to occur before 2050 at least once in September. Some regions of the Arctic are already ice-free in September or will become ice-free very soon, well before the entire Arctic Ocean is ice-free. This can have considerable local impacts. Climate models also show that ice-free conditions may occur in months beside September if warming is large enough, for potentially up to 5 months a year under the highest warming scenarios by 2100. Nonetheless, sea ice will continue to form in the winter, so ice-free conditions will remain limited to the summer and fall during the 21st century.
Fundamental changes in the North Water Polynya are less likely if warming is limited to 2°C
Jed E. Lenetsky, Alexandra Jahn, Patrick Ugrinow, Christopher R Wyburn-Powell, Rajan Patel, Hannah Zanowski
Corresponding author: Alexandra Jahn
Corresponding author e-mail: alexandra.jahn@colorado.edu
The North Water Polynya (NOW) is one of the most productive biological regions in the Arctic, with high importance for Inuit and Greenlandic peoples of Northern Baffin Bay. To provide insights into the potential changes to this region as global temperatures rise, we investigated the physical and biological oceanic responses of the NOW to 1.5°C, 2.0°C, and 3.5°C of global warming using the CESM1 climate model. We find different regimes of biological productivity for different warming levels. Under 1.5°C and 2.0°C of warming, increased polynya areas and sea ice melt occur alongside increased stratification, isolating surface waters from those at depth, leading to increased concentrations of nutrient-rich West Greenland Irminger Waters throughout the NOW region. These waters can replenish the surface with nutrients, leading to an increase in productivity relative to the historical simulation along the Greenlandic coastline. Under 3.5°C of warming, we see a similar but stronger increases in stratification and Irminger Waters as lower warming scenarios, leading to a decrease in biological productivity during all months of the growing season. This is because despite increased nutrient availability at depth, coastal convection is unable to counter the increased stratification and bring those nutrients to the surface. These results point to the importance of limiting global temperature increases to 2°C or less in order to avoid fundamental changes of the NOW ecosystem.
A century-long decreasing trend in Bering Sea ice melt revealed by T-S-based estimates
Vigan Mensah, Yen-Chen Chen, Kay I. Ohshima
Corresponding author: Vigan Mensah
Corresponding author e-mail: vmensah@lowtem.hokudai.ac.jp
The Bering Sea plays a crucial role in the physical and biogeochemical properties of the Pacific Arctic (Bering Sea, Chukchi Sea, Beaufort Sea). It provides up to 40% of the freshwater flux to the Arctic Ocean, contributes to the stratification of the Pacific Arctic, and is also a primary source of nutrients to this ocean. The Bering Sea only has seasonal sea ice cover between December and June, and, contrary to the Chukchi and Beaufort seas, no clear trend in sea ice extent, concentration or production has been detected in it since the beginning of sea ice satellite measurements. In this study, we used historical data of ocean temperature and salinity from 1930–2020 to estimate sea ice melt and establish meltwater thickness climatologies spanning the period before and after 1980 (i.e. the beginning of satellite measurements). The estimated ice melt amounts are consistent both qualitatively and quantitatively with ice thickness data obtained from the CRYOSAT-2-SMOS merged product. The climatologies and yearly time series of sea ice melt reveal a decreasing trend, with a decrease of 15% between the climatologies after and before 1980. To further confirm this trend, we also produced decadal climatologies of the Bering Sea winter water salinity, which is used as a proxy for sea ice production. These climatologies also revealed a significant salinity decrease (–0.14) between 1940–60 and 2000–20. Lastly, vertical profiles of climatological salinity indicate an increase in sea surface salinity and a decrease in sub-surface (below 30 m) salinity after 1980. All three variables that we estimated are thus consistent in indicating a decrease in sea ice production and sea ice melt in the Bering Sea, starting before the beginning of the satellite era.
Multisensor observations of sea ice melt across the marginal ice zone
Christian Haas, Mara Neudert, Mario Hoppmann
Corresponding author: Christian Haas
Corresponding author e-mail: chaas@awi.de
The marginal ice zone (MIZ) is an important region between the open ocean and the inner pack ice zone with strong ice thickness gradients due to temporally and spatially varying ocean and atmospheric heat fluxes. Ice thickness gradients and melting behavior need to be known to correctly predict seasonal sea ice retreat and the location of the sea ice edge. Here we present results of extensive sea ice observations during the interdisciplinary Atlantic Water Pathways to the Ice (ATWAICE) cruise of the German icebreaker RV Polarstern carried out in the MIZ north of Svalbard between July and August 2022. Observations included airborne ice thickness and photo surveys, continuous ship-based ice thickness profiling, and manual and autonomous in-situ observations on three ice floes along a 100 km long transect across the MIZ. The transect and ice floes were visited three times over a short 2.5 week observational period, following roughly the same ice marked by buoys. Airborne and ship-based thickness measurements showed clear, stepwise or non-linear gradients across the MIZ, with modal thicknesses increasing from zero to up to initially 1.6 m. After 2.5 weeks, 30–40 cm of total melt were detected, approximately equally distributed between surface and bottom melt. This was in good agreement with ground-based electromagnetic surveys, ice mass balance buoys, and ablation stakes on the ice floes. However, the most dramatic melt, including disappearance of the ice, was only observed very near the ice edge. Our results show good intercomparability of spatio-temporal thickness changes observed by the different methods despite relatively small total melt. However, interpretation of the atmospheric and oceanic forcing of the observed variability and change will require careful joint analysis of the complete met–ice–ocean and remote sensing data sets that were acquired during ATWAICE, which is ongoing.
Trends in sea ice melt in the Labrador Sea and Baffin Bay estimated from spring salinity profiles
Vigan Mensah, Miho Ikeda, Mizuki Komatsu, Kay I. Ohshima
Corresponding author: Vigan Mensah
Corresponding author e-mail: vmensah@lowtem.hokudai.ac.jp
The Labrador Sea plays an important role in the Atlantic Meridional Ocean Circulation (AMOC) as it provides waters that become a part of the North Atlantic Deep Water, one of the main components of AMOC. The Labrador Sea is connected to the north to Baffin Bay, which is itself connected to the fresher Beaufort Sea via the Nares Strait. The hydrography of the Labrador Sea and Baffin Bay is strongly influenced by the cycle of sea ice production, drift and melt. These areas have probably been affected by the long-term changes in seasonal sea ice production as well as the increasing trend in multi-year ice and glacier ice melting. Satellite-derived sea ice thickness data only provides a record of ~20 years, and direct observations of sea ice thickness are usually scarce in both space and time. In this study, we used historical data of ocean temperature and salinity from 1950–2020 to estimate sea ice melt and establish meltwater thickness climatologies and time series, allowing us to document the multidecadal variability of ice melt in the Labrador Sea and Baffin Bay. Climatologies for the periods before and after 2003 reveal a clear decline in meltwater thickness between 45° N and 62° N, which we attribute to the decrease in seasonal sea ice production from the southern Baffin Bay to the Labrador Sea. A clear decreasing trend in ice melt is also visible in the time series, with a decrease in meltwater thickness of 6.2 cm per decade since 1970. In contrast, northern Baffin Bay exhibits a large increase in meltwater thickness, which might be caused by the melting and subsequent southward transport of multi-year ice from the Beaufort Sea. Another possible cause could be the transport of increasing amounts of meltwater from the east Greenland glaciers via the local coastal currents.
Thickness of the Berkner Island fast ice tongue: implications for Ice Shelf Water
Christian Haas, Stefanie Arndt
Corresponding author: Christian Haas
Corresponding author e-mail: chaas@awi.de
Landfast sea ice (fast ice) attached to the Antarctic coast between ice shelves and pack ice is a key component of the Antarctic cryosphere. Most importantly, depending on oceanographic conditions, it may accumulate thick layers of platelet ice underneath. Platelet ice is an indicator of the presence of supercooled, near-surface ice shelf melt water (ISW) which forms as a result extensive ice shelf bottom melt. The supercooled water leads to stronger thermodynamic fast ice growth than would be possible with cold air alone, and its detection beneath fast ice supports conclusions about ice shelf melt in the otherwise hard to access ice shelf cavities. Here we present results of the first-ever airborne electromagnetic ice thickness and platelet ice surveys of the recurring Berkner Island fast ice tongue in the southern Weddell Sea, located in front of and between the Filchner and Ronne Ice Shelves. Anecdotal prior evidence suggested that the fast ice is extremely thick due to thick snow and the widespread presence of thick platelet ice. Surveys were carried out during a research cruise of the German icebreaker RV Polarstern in February 2018. Results showed moderate modal thicknesses ranging between 1.8 and 2.4 m, with mean thicknesses of 4.7 ± 2.9 m. The very large mean thicknesses up to 18 m were mainly due to strong ice deformation because much of the fast ice forms when pack ice gets jammed between grounded icebergs. Thinner and younger ice was found closer to the edge of the Filchner Ice Shelf which had formed during polynya events off the Filchner Ice Shelf in the preceding winter of 2017. In contrast to fast ice along the coast of the eastern Weddell Sea and elsewhere in Antarctica we hardly found evidence of the presence of platelet ice below the fast ice. This result has important implications for oceanographic conditions in the region off the Filchner Ronne Ice Shelves as it indicates the absence of ISW near the ocean surface, in agreement with conclusions drawn from oceanographic observations and modeling.
Amy Swiggs, Andrew Shepherd, Isobel Lawrence
Corresponding author: Amy Swiggs
Corresponding author e-mail: eeaesw@leeds.ac.uk
Leads are narrow, dynamic openings within the sea ice pack. They are of vital importance for heat and moisture exchange between the atmosphere and the ocean, and their distribution and geometry can affect the movement and stability of the surrounding ice. Furthermore, leads are essential for providing safe shipping routes, with sea ice being hazardous to transiting ships. The identification of leads is also crucial for calculating sea ice freeboard from satellite altimetry because the correct discrimination of leads and floes allows the sea surface height to be determined, which is an essential component of sea ice freeboard and thickness calculation. Inaccurate discrimination of leads can therefore lead to systematic errors in estimates of sea ice thickness. Here, we investigate changes in the density and distribution of leads in the Canadian Arctic Archipelago, with a focus on the Northwest Passage due to its strategic and economic interest as a shipping route. Leads and floes are discriminated in CryoSat-2 waveforms using measurements of their pulse peakiness and stack standard deviation, and in Landsat 8 thermal infrared imagery, using a classification of their heat anomalies. We then evaluate the agreement between these two independent estimates, and present the spatial and temporal trends in lead density in the Northwest Passage, thereby assessing how the ice pack is changing in a region of high economic interest. Our results reveal increases in lead density of ~10% in regions of the Northwest Passage since 2010, and we validate these results with over 50 near-coincident optical images.
Simon F. Reifenberg, Wilken-Jon von Appen, Ilker Fer, Christian Haas, Mario Hoppmann, Torsten Kanzow
Corresponding author: Simon F. Reifenberg
Corresponding author e-mail: simon.reifenberg@awi.de
Given the prospect of a merely seasonally ice-covered Arctic Ocean in the future and a consequential new quality of atmosphere–ocean coupling, understanding and quantifying oceanic processes that contribute to sea ice melt is of particular relevance. A region of intense melting is the marginal ice zone north of Fram Strait, where inflowing warm Atlantic Water meets sea ice advected southward by the Transpolar Drift. We present observations of the ice–ocean boundary layer (IOBL) from a cruise of the German research vessel Polarstern to that region in summer 2022, where we gathered continuous-in-time hydrographic observations from autonomous drifting stations on three separate ice floes, supplemented by intense observation periods of vertical microstructure profiles and ice cores from crewed stations during three revisits per floe throughout the drifting period. The three occupied floes were oriented on a line approximately perpendicular to the ice edge, initially about 25 km apart from each other, with the southernmost floe located 75 km away from the edge. The drifting instrument platforms cover a common time period of approximately 2 weeks, under relatively quiescent atmospheric conditions. First results show that, while the floes exhibited similar drift trajectories dominated by superimposed diurnal and semidiurnal oscillations, the evolution of key IOBL variables, such as stratification, melt rates, friction velocity and turbulent fluxes, varied considerably – both in time and among the occupied floes. We plan to assess how this observed variability relates to other measured properties of sea ice (e.g. ice roughness, ice thickness distribution, floe size distribution) and of the upper ocean (e.g. ice–ocean velocity shear, turbulence, surface waves, internal waves and tides) and their interaction, in order to put our preliminary findings into the broader context: ocean controls on sea ice melt in the marginal ice zone north of Fram Strait.
Employing data-science methods for mapping sea ice surface change on decadal time scales
Lena Happ, Stefan Hendricks, Andreas Gerndt, Lars Kaleschke, Riccardo Fellegara, Stephan Paul
Corresponding author: Lena Happ
Corresponding author e-mail: lena.happ@awi.de
Satellite radar altimeters provide information on processes of the polar oceans and its sea ice cover. Algorithms to discriminate sea ice and ocean surfaces are robust and widely used since they allow to estimate sea level, sea ice freeboard and ultimately sea ice thickness. The potential of using radar backscatter properties of different sea ice types is however only partly explored. Our goal is to develop new methods to quantify global changes of sea ice surface properties with all satellite radar altimeter data since the early 90s. The intended outcome is an improved sea ice mass climate data record and novel observational reference of sea ice dynamics and summer melt processes. In detail this will include an improved sea ice surface classification that resolves different sea ice types at high spatial resolution that will support range estimation and parametrization needed for the freeboard to thickness conversion. In general sea ice can be classified by age (e.g. multi year and first year ice), degree of deformation but also by melting processes (e.g. fully frozen, wet snow–ice, melt ponds). However, it is not clear up to which level sea ice classes can be distinguished based on the information contained in radar altimeter waveform data. It is state of the art to represent radar altimeter waveforms by a few parameters that give information about the shape of the curve (e.g. pulse peakiness, leading/trailing edge width) for further processing and there has to be a trade off between a reduced representation and information loss. Regarding the developments of an increase in computational power it is not clear if this is still the best representation for classification. Is it possible to find a representation that preserves more of the information contained in the original waveforms and is at the same time suitable as inputs for further processing? As a first step toward the overall goal of the project these questions are tackled by adapting advanced data science methods. These include the MAPPER algorithm from the field of topological data analysis for an exploratory data analysis in combination with dimensionality reduction techniques (e.g. auto encoders). While the first analysis is on Sentinel-3/SRAL data supported by OLCI and SLSTR as collocated visual and thermal reference, the selected methods need to be applicable to other satellite radar missions in order to reach the goal of a data record spanning several missions over the last 30 years.
The impacts of combined SAM and ENSO on seasonal Antarctic sea ice changes
Jinfei Wang, Hao Luo, Lejiang Yu, Xuewei Li, Paul Holland, Qinghua Yang
Corresponding author: Hao Luo
Corresponding author e-mail: luohao25@mail.sysu.edu.cn
Both the Southern Annular Mode (SAM) and the El Niño-Southern Oscillation (ENSO) are critical factors contributing to Antarctic sea ice variability on interannual time scales. However, their joint effects on sea ice are complex and remain unclear for each austral season. In this study, satellite sea ice concentration (SIC) observations and atmospheric reanalysis data are utilized to assess the impacts of combined SAM and ENSO on the seasonal Antarctic sea ice changes. The joint SAM-ENSO impacts on southern high-latitudes are principally controlled by the strength and position of the wave activity and associated atmospheric circulation anomalies affected by their interactions. In-phase events (La Niña/positive SAM and El Niño/negative SAM) are characterized with an SIC dipole located in the Weddell/Bellingshausen Seas and Amundsen/Ross Seas, while out-of-phase events (El Niño/positive SAM and La Niña/negative SAM) experience significant SIC anomalies in the Indian Ocean and western Pacific Ocean. Sea ice budget analyses are conducted to separate the dynamic and thermodynamic contributions inducing the sea ice intensification anomalies. The results show that in-phase intensification anomalies also display a pattern similar to the SIC dipole and are mainly driven by the direct thermodynamic forcing at the ice edge and thermodynamic responses to meridional sea ice drift in the inner pack, especially in autumn and winter. Dynamic processes caused by zonal sea ice drift also play an important role during out-of-phase conditions in addition to the same mechanisms during in-phase conditions.
Snow effects on Cryosat-2 waveform over sea ice in the Weddell Sea
Lu Zhou, Weixin Zhu, Rosemary Willatt
Corresponding author: Lu Zhou
Corresponding author e-mail: lu.zhou@gu.se
Snow over sea ice is one of the major uncertainties contributing to the altimeter remote sensing signature of sea ice, including delay correction due to the reduced speed of radar propagation in snow and the scattering of the radar waveform shape due to different snow morphology, surface roughness, and mixed surface types. To investigate the snow effects on Cryosat-2(CS-2) altimeter waveform signal in the Weddell Sea, we employ a waveform deconvolution model to CryoSat-2 and Ka-band altimeter to retrieve the snow surface and volume backscattering coefficients over the Weddell Sea and to compensate for the volume scattering effects in CryoSat-2 retrieval in the Antarctic region. CS-2 data are taken from the ESA baseline D level 1B and 2 SAR-mode data products, and Ka-band Karen altimeter products are adopted from level 1B CryoVEx/Karen 2017-18 campaign. To be free from lead and open water effects on the altimeter echo signal, SAR images from Sentinel-1 TOPSAR data in extra wide-swath (EW) mode are used to pick the clean floe ice area. We found that the convoluted parameters and total backscatter depend on the different surface roughness. The deconvolution analysis of these highly accurate and colocated measurements allows us to explore and emphasize their snow volume scattering effects and differences on radar echo in Ka- and Ku-band radar altimetry, which could be a basis for the development of future polar altimetric missions, i.e. CRISTAL dual band.
Polynya events in the Wandel Sea
Axel Schweiger, Mike Steele, Kent Moore, Jinlun Zhang, Kristin Laidre, Qinghua Ding
Corresponding author: Axel Schweiger
Corresponding author e-mail: schweig@uw.edu
The Arctic Ocean’s Wandel Sea is the easternmost sector of the Last Ice Area, where thick, old sea ice is expected to endure longer than elsewhere and potentially offer a refuge for ice dependent species. Two recent polynya events drew attention to this region and raised questions about this view. One occurred in February 2018, the other in August 2020. In this paper we compare and contrast these two events, examine their causes and put them into a longer-term past and future climate change perspective. We employ ice–ocean model simulations, satellite data, as well as coupled global climate model simulations.
Benjamin Rabe, Marcel Nicolaus, Thomas Krumpen, Mario Hoppmann, Wieslaw Maslowski, Tim Stanton, Ola Persson, Matthew Shupe, Ruibo Lei, Jennifer Hutchings, DN Team
Corresponding author: Benjamin Rabe
Corresponding author e-mail: benjamin.rabe@awi.de
The MOSAiC Distributed Network of autonomous ice-tethered systems (‘buoys’) aimed to resolve the variability across the MOSAiC observatory at a range of spatial and temporal scales. The system of different sites or nodes, set up radially around the central observatory, consisted of buoys of varying complexity, ranging from position-only drifters to systems aimed at fluxes of different variables through the ocean, the sea ice and snow, and the atmosphere just above the ice. The full set of buoys aimed to cover both feedbacks in the coupled system around the ocean–ice–atmosphere interface as well as three-dimensional processes, motivated by the limited horizontal resolution of state-of-the-art coupled climate models. This presentation briefly describes the setup and performance, then highlight the ability to observe different processes using example measurements from two selected time periods: one 30-day part spanning December and January, another the early-summer absence of Polarstern, during which no manual observations were carried out at the central observatory. Both purely physical as well as biologically and chemically relevant observations will be presented. The results will be presented in the context of other observations and numerical modelling.
Implementation of internal wave drag in the CICE model
Daniela Flocco, Daniel Feltham, David Schroeder, Michel Tsamados, Yevgeny Aksenov, Anthony Siahaan
Corresponding author: Daniela Flocco
Corresponding author e-mail: daniela.flocco@unina.it
As sea ice moves across a stratified ocean, surface roughness and keels can generate internal waves that propagate momentum and act to increase the drag coefficient at the ice–ocean interface. This source of drag is additional to form drag arising from the pressure jump across obstacles such as keels. The magnitude of the internal wave contribution to drag depends upon the mixed layer depth, buoyancy jump at the mixed layer bottom, stratification of the ocean beneath the mixed layer, and the geometry of the surface roughness. In this work, we take a model of internal wave drag developed by McPhee et al. (1989) and include it into a state-of-the-art sea ice model coupled to an ocean model (NEMO-CICE5). We present a series of simulations demonstrating the regional impact of internal wave drag on emergent Arctic sea ice characteristics such as thickness, motion and deformation. Internal wave drag particularly increases the total ice–ocean drag coefficient in the Canadian Arctic, showing a maximum increase of 30% in winter that is associated with an increase in ice thickness by up to 20 cm in winter. Sea ice concentration increases of up to 10% in the Central Arctic and in the Russian Arctic are found during the summer months.
An abrupt transition in the Antarctic sea ice–ocean system
F. Alexander Haumann, François Massonnet, Paul R. Holland, Mitchell Bushuk, Ted Maksym, Will Hobbs, Michael P. Meredith, Ivana Cerovečki, Thomas Lavergne, Walter N. Meier, Marilyn Raphael, Sharon Stammerjohn
Corresponding author: F. Alexander Haumann
Corresponding author e-mail: alexander.haumann@gmail.com
Over the past decade, Antarctic sea ice extent exhibited a sequence of record maxima, followed by a rapid decline in 2015/16, and record minima since. In this presentation, we show that this sudden and remarkable ice loss marks an abrupt transition from a high to a low ice state that cannot be explained by year-to-year variability. Instead, it is most likely associated with a longer term variability arising from ice–ocean feedbacks. The abrupt transition was preceded by an increase in persistence and variance of the sea ice anomalies, an increasing upper Southern Ocean density stratification, and an accumulation of heat at the subsurface; suggesting a decoupling of the surface from the subsurface ocean. During this period, the sea ice anomalies shifted from being structured predominantly regionally and seasonally to a largely circumpolar and interannual regime. In 2015/16, the upper ocean density stratification in the ice-covered region suddenly weakened, leading to a release of the heat from the subsurface, contributing to the sea ice decline during winter. Our analysis suggests that the sudden sea ice loss in 2015/16, and the persisting low ice conditions since, arose from a systematic change in the physical state of the coupled circumpolar ice–ocean system. This change will have wide implications for global climate, ecosystems and the Antarctic Ice Sheet.
Evolving relationship of Nares Strait ice arches and the North Water Polynya
Kent Moore, Steve Howell, Mike Brady
Corresponding author: Kent Moore
Corresponding author e-mail: gwk.moore@utoronto.ca
Nares Strait , the waterway that separates northwest Greenland from Ellesmere Island, is a major pathway along which sea ice leaves the Arctic, including the planet’s oldest and thickest sea ice, which is experiencing an accelerated loss. Ice arches that develop during the winter at the Strait’s northern or southern terminus can remain stable for extended periods during which the transport ceases. The Arctic’s most productive polynya, the North Water (NOW) or Pikialasorsuaq (West Greenlandic for ‘great upwelling’) forms at the Strait’s southern end in part due to the presence of a nearby southern arch. There is evidence that a warming climate and the concomitant thinning of Arctic sea ice is weakening the arches and it has been proposed that this may lead to detrimental changes to the NOW. Here we use examples from recent years to explore the impact that the absence of a southern arch has on the NOW. We find that winters with no southern ice arch are associated with a northward expansion of the NOW characterized by reduced and thinner ice cover as well as enhanced primary productivity. In these years, there is an acceleration of the winds along within Kennedy Channel and Smith Sound that assists in the expansion.
Sofia Muller, Odile Crabeck, Nicolas Cammue, Florian Deman, Jean-Louis Tison, Saïda El Amri, Lisa Ardoin, Bruno Delille, François Fripiat
Corresponding author: Sofia Muller
Corresponding author e-mail: sofia.muller@uliege.be
Observations over recent decades suggest that sea ice plays a significant role in global biogeochemical cycles, providing an active biogeochemical interface at the ocean–atmosphere boundary. However, a pressing need exists to perform methodological intercalibration experiments in sea ice in order to obtain reliable measurements of basic biogeochemical properties. This is the case for two potent greenhouse gases, methane (CH4) and nitrous oxide (N2O). Two methods are reported in the literature: the melting bags-equilibration method, inherited from the widely applied equilibration method in oceanography, and the melting–refreezing method, typically used on ice-core sciences for ancient air extraction. Concentrations of CH4 and N2O were measured at high-resolution (i.e. 5 cm resolution) on four cores collected in spring 2015 in Abatus Bay (Prydz Bay, Antarctica). In agreement with previous unpublished inter-comparison, the melting bags–equilibration method shows constantly higher concentrations for both CH4 and N2O than the melting–refreezing method. A series of tests have been performed on these two extraction methods to evaluate and understand these differences.
Philipp Anhaus, Christian Katlein, Ilkka Matero, Stefanie Arndt, Daniela Krampe, Benjamin A. Lange, Julia Regnery, Jan Rohde, Martin Schiller, Ran Tao, Marcel Nicolaus
Corresponding author: Philipp Anhaus
Corresponding author e-mail: philipp.anhaus@awi.de
Improving our understanding of the climate and ecosystem of the sea-ice covered Arctic Ocean is a key objective of recent research. We aim for a better understanding of the linkages of physical and biological processes at the interface between sea ice and ocean. To enhance the quantification of these linkages, combined observations of physical, biological and chemical parameters are needed. We deployed a remotely operated vehicle (ROV) equipped with an interdisciplinary sensor payload to simultaneously measure these parameters in the water underneath the Arctic sea ice. These observations were made synchronous in time and place to each other enabling a description of their spatial and temporal variability. Overall, we completed more than 130 surveys covering all seasons and various sea-ice and surface conditions in the Arctic between 2011 and 2020. We focused on optical parameters, sea-ice bottom topography, and upper ocean physical and biological oceanography. In addition, visual documentation of the under-ice environment was performed, nets for zooplankton were towed, and the ROV was used for instrument deployment and maintenance. Here, we present all ROV sensor data, allowing for a comprehensive picture of the under-ice environment. We are inviting discussions on further collaboration in data analyses and usage, in particular co-location and merging with other datasets and other (also future) projects.
The role of sea ice in the carbon budget of polar oceans, a decade of work
Odile Crabeck
Corresponding author: Odile Crabeck
Corresponding author e-mail: ocrabeck@uliege.be
The first measurment of CO2 fluxes over sea ice started in early two thousand. Since, we have monitored the carbonate system and recorded CO2 fluxes in both the Arctic and the Antarctic and at each season. The BEPSII working group recently gathered all these observations in a single database. This dataset exploits more than one thousand of measurements in the Arctic and in the Antarctic and allows for the first time to establish a yearly budget of sea ice CO2 fluxes based on observations. Sea ice seems to have a smaller impact on the CO2 budget than previously predicted mainly because the out-going CO2 fluxes during sea ice growth are counterbalanced by in-going CO2 fluxes during spring and summer.
Satoshi Kimura, Kikuchi Takashi, Amane Fujiwara
Corresponding author: Satoshi Kimura
Corresponding author e-mail: skimura@jamstec.go.jp
We deploy an ice-tethered buoy with six CTDs within 20 m of sea ice ~300 km offshore of Prudhoe Bay, Alaska, as a part of ICEX 2022 hosted by the US Navy in March 2022. The ocean measurements were complemented by tracking the surrounding sea-ice motions with 10 GPS and two cameras overlooking the top of the ice-tethered buoy. The transition of the sea-ice motions coincides with a formation of melt ponds around the ice-tethered buoy, which are detected by the daily images from the cameras. When the melt pond disappears from the daily images, we detect freshening of the water below the sea ice. The significant freshening is confined within 5 m of the water column. Our measurements suggest that the melt pond formation makes the sea ice fragile, and the melting of sea ice occurs as a burst of fresh water injected into the surface of the ocean.
Rob Massom, Phillip Reid
Corresponding author: Rob Massom
Corresponding author e-mail: Rob.Massom@aad.gov.au
Here, we introduce a new climate and environmental index and metric – based on the long satellite passive microwave sea-ice concentration record – that enables daily circumpolar mapping, quantification and monitoring (at 25 km resolution) of the amount (extent) of Antarctic coastline that is not protected by a sea ice ‘buffer’ i.e. is fully exposed to open-ocean conditions (including waves). This is ‘Coastal Exposure Length’. The time series reveals previously unknown climatological patterns of coastal exposure around Antarctica, and distinct regional and seasonal trends since 1979. The new findings fill a gap in our understanding of Antarctica’s vulnerable coastal environment, towards informing and improving modelling of its current/recent state and predictions of its likely future trajectory. Indeed, the new coastal-exposure index provides an important additional means of gauging the response of Antarctica to changing climatic conditions – to complement the widely used sea-ice concentration, extent and seasonality time series and analyses derived from the same base dataset. Change in coastal exposure has implications for the stability of floating ice-sheet margins, landfast sea ice, nearshore benthic ecosystems, and logistical operations. Examining its regional and temporal variability, particularly across East Antarctica, may also provide information on the influence of the Antarctic Coastal Current on sea-ice formation. We further present initial findings from a by-product of the index algorithm, namely coastal polynya size and distribution. This project was funded by the Australian Antarctic Division (for RM); the Australian Bureau of Meteorology (PR); the Australian Government’s Australian Antarctic Partnership Programme (PR and RM); and (for RM) the Australian Research Council Special Research Initiative Australian Centre for Excellence in Antarctic Science (Project Number SR200100008). It also contributes to AAS Project 4528.
Summer sea ice drift tracking and variation analysis in Fram Strait from 2011–20
Xue Wang, Yan Fang
Corresponding author: Xue Wang
Corresponding author e-mail: wangxue25@mail.sysu.edu.cn
Accurate sea ice drift information in Fram Strait plays important roles in quantifying the sea ice export through the Strait and reducing uncertainty of the Arctic sea ice loss estimation. Due to the limitations of data sources and algorithms, performance of the existing methods in summer sea ice drift retrieval is poor. In this study, a summer daily sea ice drift monitoring method based on time series MODIS data and the A-KAZE algorithm was proposed. Furthermore, daily sea ice motions in Fram Strait for April–September 2011–20 were retrieved based on the proposed method, and the characteristics of sea ice motion in Fram Strait for these 10 years were analyzed based on the tracking results. The proposed method was evaluated over a portion of the Strait from 29 April–5 May 2020. The results showed that the proposed method outperformed the classic MCC algorithm in sea ice drift retrieval, with velocity and direction RMSE decreases of 2.13 km d–1 (73%) and 10° (38%), respectively. Furthermore, it retrieved more sea ice drift vectors with larger spatial coverage than did the SIFT and SURF algorithms. Meanwhile, compared with the daily sea ice motion vectors generated with daily synthetic data, the motion vectors obtained by the proposed method using time series MODIS images covered more areas, with an average increase of 862.62 km2 (nearly 16 times), which demonstrated that the proposed method greatly reduced the cloud effect on optical data. Furthermore, it was found that the spatial distribution of sea ice velocity in Fram Strait for the last 10 years is relatively consistent: ice velocity in the south of the Strait is higher than that in the north, and the velocity away from the coast is higher than that near the shore. The annual average summer sea ice velocity in Fram Strait does not show a significant increase or decrease trend, but there is a downward trend from April to July and an upward trend from August to September. The proposed method provides new idea for daily sea ice drift monitoring in summer and the analysis of summer sea ice velocity in Fram Strait for the last 10 years is applicable to research such as rapid change of Arctic sea ice.
MacKenzie Jewell, Jennifer Hutchings
Corresponding author: MacKenzie Jewell
Corresponding author e-mail: jewellm@oregonstate.edu
Drift of the Beaufort Sea ice pack in winter is closely tied to opening of large-scale leads from coastlines bounding the winter pack. To improve representations of winter ice transport and its impacts on the Arctic sea ice mass balance in models, the drivers and ice drift associated with such deformation events must be well understood. We present observational analyses relating the synoptic atmospheric conditions that open leads along the Beaufort Sea’s Alaskan and Canadian coasts to patterns of sea ice motion across the Pacific Arctic. In agreement with previous studies, we find the position and structure of high-pressure atmospheric systems control the location of lead extension into the Beaufort ice pack. Leads separate portions of the ice pack from adjacent coasts, introducing spatiotemporal discontinuities in the dynamic ice response to winds. Lead activity is especially frequent at Point Barrow, a prominent headland marking the westernmost boundary of Alaska’s Beaufort coast. Lead opening from Point Barrow is most often driven by winds meeting the coast from the north or east-northeast. Despite equivalent wind speeds, ice in the Chukchi Sea drifts twice as fast as ice in the Beaufort Sea as Point Barrow leads extend northward into the ice pack, resulting in a zonally asymmetric contribution to the climatological Beaufort Gyre circulation. Increases in easterly wind forcing, usually associated with eastward migration of an atmospheric high, open additional leads along the Beaufort Sea’s southern and eastern coastal boundaries. Beaufort ice transport strengthens as the entire pack detaches from the coasts along these coastal leads. The findings in this analysis show that atmospheric control on patterns of sea ice transport across the Beaufort Sea is modulated by coastal geometry and the positions of transient lead patterns. Models should reproduce this behavior, and we present observational metrics for validating dynamic sea ice models. This will allow investigation of the sea ice mechanics underlying the processes observed during lead opening in the Beaufort Sea.
SAR-based sea ice drift and Lagrangian tracking for evaluating sea ice drift forecast models
Martin Bathmann, Anja Frost, Stefan Wiehle, Gunnar Spreen
Corresponding author: Martin Bathmann
Corresponding author e-mail: martin.bathmann@dlr.de
We use sea ice drift information obtained from Synthetic Aperture Radar (SAR) observations to assess the usability of sea ice drift forecast models for multi-day sea ice analysis. This work demonstrates the capabilities of a vector approach on a small case study of 20 analysed SAR-scene pairs in winter 2022/23 in Baffin Bay with 12.5 km and 0.5 km grid spacing. Finding optimal shipping routes through sea ice becomes increasingly important for navigation in polar regions. Sea ice drift forecasts such as TOPAZ4 and neXtSIM provide a prediction of the sea ice situation several days (up to 10) into the future. We apply an approach that combines methods from the interdisciplinary field of environmental physics, geoinformation technology and remote sensing. Sea ice drift vector fields are obtained from successive Sentinel-1 image pairs using the phase correlation technique applied in a hierarchical resolution pyramid. The derived drift is compared to historical multi-day sea ice drift forecast of TOPAZ4 and neXtSIM, provided in the EU CMEMS (Copernicus Marine Environment Monitoring Service) Arctic analysis and forecast products PHYS_002_001_a and PHY_ICE_002_011. The forecast model trajectories and SAR-based measurements are both calculated starting from a regular grid. This allows working either in a raster or a vector model. We use the vector model for data processing to benefit from high flexibility and floating-point number coordinate resolution. An object-oriented programming (OOP) approach, a topology, hashing and spatial indexing yield a computational performance that can compete with raster analysis. Forecast model trajectories are derived with Lagrangian tracking. The deformation parameters divergence, vorticity and shear are calculated by applying Sobel kernels. With this developed workflow, sea ice motion and deformation predicted by TOPAZ4 and neXtSIM can be evaluated by SAR-based drift measurements. The present work is realized in the context of the FAST-CAST 2 project, funded under grant 19F2192A by the German Federal Ministry for Digital and Transport’s mFUND programme.
Mapping of sea-ice melting and net freshwater flux by sea-ice growth/melt in the Southern Ocean
Mizuki Komatsu, Kay Ohshima, Vigan Mensah, Kazuki Nakata
Corresponding author: Mizuki Komatsu
Corresponding author e-mail: m_komatsu@ees.hokudai.ac.jp
Sea ice redistributes salt/freshwater via freezing, melting, and its transport, affecting the water mass formation. The Southern Ocean with the largest seasonal ice zone serves the major water mass formation associated with ice production/melt. Intermediate water of the Southern Ocean, which is affected by sea-ice melt via Ekman pumping, has shown a prominent freshening for recent several decades. Increase in northward freshwater transport by sea ice and its melt has been suggested as its cause. This freshening enhances the stratification and hampers the mixing of deeper, warmer and carbon-rich waters into the surface layer. Thus the sea-ice melt and its variation potentially impact on the climate change. However, estimation of ice-melt amount is very limited, because of the complexity of the melting process and large uncertainties of ice thickness. This study estimates sea-ice melt using spring salinity profiles from ship-based, Argo float, and elephant seals data, a total of nearly 25 000 data. The estimation is made by calculating the salinity deficit of the upper layer affected by sea-ice melt. The key point in the estimation is to find the top of the winter water, which is nearly at freezing point and not affected by warming and ice melting. We have developed an algorithm to detect the top of the winter water automatically by combined use of potential temperature and salinity profiles. Our results show that a large sea-ice melt (~1.5 m) occurs in the western side of the three gyres of the Weddell and Ross Seas and east of Kerguelen plateau, where sea-ice drifts offshore from the coast. A large melt also occurs around the Cape Darnley polynya. The total freshwater flux from sea-ice melt is calculated to be 17 200 Gt a–1. This value is six times larger than that of the total glacial melt (~2900 Gt a–1): the basal melt plus calving/iceberg melt. Our ice melt data set was used to clarify the net freshwater flux from sea ice, by combining the ice production data derived from the thin ice thickness algorithm of Nakata et al. (2021) and heat flux calculation. The distribution of the net freshwater flux by sea-ice shows a clear contrast: a large negative freshwater flux in the coastal regions, especially in coastal polynyas, and positive freshwater flux in the offshore regions. In addition, negative freshwater flux (production > melt) occurs along the sea-ice divergence zone.
Kay Ohshima, Masato Ito, Kazuki Nakata, Yasushi Fukamachi, Takeshi Tamura
Corresponding author: Kay Ohshima
Corresponding author e-mail: ohshima@lowtem.hokudai.ac.jp
Antarctic Bottom Water (AABW) originates as dense shelf water (DSW), which forms from brine rejection during sea-ice production. An important region of AABW formation has been identified off the Cape Darnley polynya (CDP). However, it remains unclear why and how high ice production leads to AABW formation. Using moored acoustic measurements and a satellite microwave algorithm, we reveal that underwater frazil ice dominates in the polynya. The most important finding of this study is the frequent occurrence of deep penetration of frazil ice down to 80 m or more in the CDP. As long as strong winds continue (typically >15 m s–1), underwater frazil ice formation persistently occurs and a mixture of frazil ice streaks and open water can be maintained at the surface without accumulation of heat-insulating thick ice. This creates an efficient ice production system in the polynyas. The high ice-production in the nearshore combined with longer residence times creates high-salinity DSW, leading to the AABW formation. Based on validation of the satellite algorithm for detecting active-frazil areas from our acoustic observations, we have developed a method in which deep frazil penetration is inferred from the combined information of the wind and satellite product. The map of the mean occurrence rate of deep frazil penetration over the entire Southern Ocean suggests that deep frazil is prominent particularly in the CDP. Sea ice production associated with deep frazil is also greatest at the CDP, which makes it a source area of AABW formation among the Antarctic coastal polynyas. On the other hand, the map suggests that a deep frazil also occurs in other polynyas. Considering recent observations of frequently occurring supercooled water in Antarctic coastal waters, it is likely that deep frazil penetration occasionally occurs in other Antarctic coastal polynyas. In addition to high ice production, deep-penetrating frazil ice potentially plays an important role in transport of materials. When it reaches the bottom or comes into contact with resuspended sediments, it can incorporate sediments or micronutrients such as iron, which are then transported by ice floes and released when the ice melts, possibly leading to high biological productivity. Alternatively, frazil ice could itself induce algal blooms as green frazil ice in major Antarctic polynyas. As such, dominant frazil ice could potentially contribute to high biological productivity in the Southern Ocean.
Sea ice concentration retrievals from microwave radiometry : a new algorithm for AMSR2
Jozef Rusin, Thomas Lavergne, K. Andrea Scott, Anthony P. Doulgeris
Corresponding author: Jozef Rusin
Corresponding author e-mail: jozefjr@met.no
Passive microwave (PMW) radiometers provide consistent measurement of sea ice concentration (SIC), an essential climate variable used in monitoring global and high latitude climatic change since the 1970s. The key advantage of PMW data is its sub-daily imaging capability of the Arctic attributed to its orbit type and large ground swath. This sub-daily imaging of the Arctic makes PMW SIC data essential for atmospheric and coupled models, sea ice forecasting, and monitoring the Arctic and Antarctic. Currently common methods for PMW SIC derivation employ a combination of 19/37 GHz frequencies (e.g. Comiso Bootstrap and NASA team algorithms) or purely 89 GHz (e.g. ASI algorithms). The algorithms based on 19/37 GHz provide accurate SIC measurements but produce a coarse SIC field (∼25 km when using the AMSR2), whereas 89 GHz algorithms provide a much higher spatial resolution of ∼5 km (when using the AMSR2) but also result in larger SIC uncertainties when compared to 19/37 GHz products. There is therefore a scientific need to try to obtain the benefits of both the accuracy of the 19/37 GHz algorithms and the high resolution of the 89GHz algorithms. Funded by the Norwegian Sustainable Development of the Arctic Ocean (SUDARCO) and Sea Ice Retrievals and Data Assimilation in Norway (SIRANO), this research validates the European Space Agency’s (ESA) Resolution Enhanced (RE) algorithm to generate a 5 km AMSR2 SIC product in the Barents Sea and Arctic Ocean. The RE algorithm, developed by the ESA CCI+ project to produce a 12.5 km SIC Climate Data Record, combines the accuracy of the 19/37 GHz algorithm with the high-resolution capabilities of the 89GHz SIC algorithm to produce a SIC product with improved ice details, such as the ice edge, with the aim of obtaining the benefits from both types of algorithm (high resolution and low measurement error). This new product is validated against a SIC produced from high resolution multispectral Landsat-8 data as well as known 0% & 100% SIC tie-points from the ESA Round Robin Data Package Phase 2 dataset. Overall the research aims to improve our PMW SIC measurement methodologies and assess the operational potential of the new RE SIC product. Additionally, the results will support the advancement of SIC algorithms for the upcoming ESA Copernicus Imaging Microwave Radiometer mission (CIMR), since its high-resolution and multi-frequency capabilities call for advancing our current methodologies of measuring SIC from PMW data.
A climate data record of global sea-ice drift from the EUMETSAT OSI SAF
Emily Down, Thomas Lavergne
Corresponding author: Emily Down
Corresponding author e-mail: emilyjd@met.no
Sea-ice drift is a key variable for understanding sea ice in a changing climate, and an essential climate variable (ECV) product for the Global Climate Observing System (GCOS). In the Arctic, sea ice has been reported to drift faster in recent years, associated with its reduction in area, thinning, and loss of multiyear ice. In the Antarctic, trends in sea-ice drift have been linked to trends in wind patterns. We present a new 30-year climate data record (CDR) of global, year-round sea-ice drift vectors covering 1991–2020. This uses the continuous maximum cross-correlation technique (CMCC) for measuring sea-ice drift from pairs of brightness temperature images of passive microwave satellite missions. During summer, this technique becomes less accurate due to surface melting and higher atmospheric humidity. We therefore employ a parametric free-drift model to fill the data gaps in the summer. This model calculates the ice drift based on wind vectors from the ERA5 reanalysis, under the assumption that the internal stresses of the ice can be ignored. We describe the algorithm baseline for the new CDR as well as results of validation against the sparse network of on-ice buoy trajectories. We finally describe the merits and known limitations of the new data record, and ideas for future improvement. This CDR was created in the context of the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) and is readily available at https://doi.org/10.15770/EUM_SAF_OSI_0012.
Late summer frazil ice formation with high chlorophyll off the Amery Ice Shelf and Cape Darnley
Kay Ohshima, Yoshihiko Machimura, Vigan Mensah, Kazuki Nakata, Masato Ito, Yasushi Fukamachi, Ryosuke Makabe, Shintaro Takao, Sohey Nihashi
Corresponding author: Kay Ohshima
Corresponding author e-mail: ohshima@lowtem.hokudai.ac.jp
The importance of frazil ice in Antarctic coastal polynyas has been increasingly recognized. Recently deep-reaching frazil ice has been observed in the Cape Darnley polynya. It has been shown that frazil ice occurs as green frazil ice in late summer in major Antarctic polynyas. These frazil ice-associated algal blooms may be a major phenomenon around Antarctica that is overlooked in regional carbon and ecosystem models. This study focuses on the offshore region of the Amery Ice Shelf, including the Cape Darnley polynya, to understand the process and cause of late summer frazil ice formation with high chlorophyll. We made combined analyses of advanced microwave scanning radiometer (AMSR) and moderate resolution imaging spectroradiometer (MODIS) during 2003–11. Active frazil area is detected by the AMSR algorithm that discriminates ice type. The Green Index defined by DeJong et al. (2018) is calculated from MODIS surface reflectance data to identify the green colored areas of high chlorophyll. It is clearly shown that areas of active frazil ice and high chlorophyll coincidentally occur both temporally and spatially in late summer. Both areas have a peak in their distributions at the same location, about 50 km offshore of the ice shelf. This also suggests an unknown frazil ice formation process distinctly different from a coastal polynya process. In the case of 2010, the active frazil ice area with high chlorophyll extended westward to the Cape Darnley polynya, where the moored acoustic measurement detected underwater frazil ice and biological activity. According to the CTD-tag seal data off the ice shelf in late summer, ice shelf water (ISW) that is supercooled exists at depths of 250–400 m. Surface water is heated by solar radiation in the region from the ice shelf front to 68.3° S, while in the region north of 68.2° S, the surface water stays at freezing point. We assume that the coincidental occurrence of frazil ice and high chlorophyll is caused by the following processes. First, ISW becomes supercooled during the outflow from the ice shelf cavity and frazil ice is generated. Next, generated frazil ice gradually rises toward the surface. Frazil ice can appear at the surface in the region north of 68.2° S, where the surface water remains at freezing point. Finally, frazil ice scavenges phytoplankton existing in the water column and carries it to the surface. Simultaneously, iron contained in ISW enhances biological production.
Léo Edel, Jiping Xie, Calliopé Danton Laloy, Julien Brajard, Laurent Bertino
Corresponding author: Léo Edel
Corresponding author e-mail: leo.edel@nersc.no
In the Arctic, the sea ice thickness (SIT) remains one of the most challenging parameters to estimate and generally present temporal and spatial discontinuity which is a major difficulty for climate studies. Since 2010, the combined product CS2SMOS enables more accurate SIT retrievals that significantly decrease the SIT errors when assimilated in models such as TOPAZ4. Can we extrapolate these benefits in the earlier period 2000–10? In this study, we train a machine learning algorithm to learn the systematic SIT errors between two versions of TOPAZ4 (with and without CS2SMOS assimilation) in 2010–20, in order to predict the SIT error and extrapolate the SIT prior to 2010. The ML algorithm relies on SIT coming from two versions of TOPAZ4, various oceanographic variables as well as atmospheric forcings from ERA5. The ML model demonstrates its ability to correct a significant part of the SIT error. We will discuss the sensitivity of the method to the input variables and to different types of ML models. The long Arctic ML-reconstructed SIT record (2000–0) is validated using in-situ data and earlier satellite data.
Recent advances and challenges in sea ice thickness research
Christian Haas, David Babb, Axel Schweigger
Corresponding author: Christian Haas
Corresponding author e-mail: chaas@awi.de
The thickness of sea ice is one of its most important properties and remains difficult to observe and predict. It depends not only on thermodynamic processes but also on deformation due to winds and currents which results in large small-scale and regional ice thickness variability. Here we provide a high-level summary of our views on recent advances and challenges in sea ice thickness observations, understanding and modeling. Numerous in-situ and airborne observation methods continue to provide invaluable information on local and regional level ice thicknesses including snow, and on the full ice thickness distributions. These include upward looking sonars, ice mass balance buoys, laser altimetry, and airborne electromagnetic induction sounding, most of which were also extensively used during the year-long Mosaic drift station in 2019/20. In-situ and airborne observations are also required for the validation of satellite data, and the end of NASA’s Operation Icebridge in 2019 has resulted in a noticeable reduction of large-scale validation data. However, with both the CryoSat-2 radar and IceSat-2 laser altimetry missions operating in tandem since 2019 and supplemented by SMOS, a new age of satellite ice thickness remote sensing has commenced which additionally can provide much needed snow thickness information due to different snow penetration of microwaves and laser photons. Compilation of public-domain ice thickness climate data records has provided easy and widespread access to the data products. However, reliable time series of ice thickness variability and trends since the first satellite altimetry missions in the 1990s remain elusive due to large uncertainties related to the snow cover on the ice, in particular in Antarctica. Much progress has been made with CryoSat-2 observations during summer which are hampered by melt ponds and with the high-resolution profiling of pressure ridges and melt ponds with IceSat-2. Ultimately, ice thickness data should be used to help interpret sea ice changes and to improve, validate and initialize models. Some modeling systems routinely assimilate satellite derived ice thickness data with some improvements of the results. Sea ice models move towards higher resolution and unstructured meshes, and new rheologies are introduced to better simulate ice deformation, lead opening and thickness redistribution.
Modelling snow and ice microwave emissions in the Arctic for a satellite-based water vapor retrieval
Janna Rückert, Marcus Huntemann, Gunnar Spreen
Corresponding author: Janna Rückert
Corresponding author e-mail: janna.rueckert@uni-bremen.de
The variability of sea ice emissions in the microwave regime is a crucial challenge for polar satellite remote sensing of atmospheric parameters. In order to retrieve those, assumptions about surface contributions to the overall brightness temperatures measured by space-born radiometers are necessary. The emitted radiation from the surface depends on a variety of parameters such as snow micro-structure or the brine content of the sea ice, which is related to the sea ice age. Here, we present a multi-parameter satellite retrieval based on inverting a physical forward model of both atmosphere and surface microwave emission under winter conditions. An optimal estimation method simultaneously retrieves integrated water vapor, snow depth and seven other geophysical parameters, including sea ice concentration, from passive microwave satellite radiometry (AMSR2, potentially SMOS sensors). One advantage compared to using several single-parameter retrievals is that all retrieved parameters are physically consistent, e.g. ice-type fractions add up to the total sea ice concentration. In addition the method provides uncertainty estimates for each parameter. It is based on a previously developed retrieval that combines an atmospheric model with empirical sea ice components to simulate brightness temperatures, TB. Now, the ice surface part is replaced by the sea ice version of the Microwave Emission Model of Layered Snowpacks (MEMLS) using an idealized model setup based on literature data. This allows the inclusion of additional surface parameters, such as snow depth. The setup is chosen to (i) cover the most important quantities influencing the brightness temperatures in order to simulate plausible brightness temperatures, polarization differences and their variabilities and (ii) reflect a realistic average Arctic snowpack including temperature gradients. To assess potential improvements of the physical model, the extensive datasets acquired during the year-long Arctic expedition MOSAiC are used as reference. Additionally, comparisons to reference datasets from the sea ice Round Robin Data Package, the Norwegian Young Sea Ice (N-ICE2015) expedition and NASA Operation Ice Bridge are performed. We show how the new model affects the modelled brightness temperatures as well as the retrieved parameters. Focusing on water vapor, we see an improved correlation and a reduction of the bias for integrated water vapor compared to the previously used empirical model.
Linking winds with sea ice changes in the Southern Ocean over the past centuries
Feba Francis, Jeanne Rezsöhazy, Quentin Dalaiden, Hughes Goosse, Liz Thomas
Corresponding author: Hugues Goosse
Corresponding author e-mail: hugues.goosse@uclouvain.be
The absence of a clear trend in Antarctic sea ice extent over the past 40 years remains one of the most intriguing features of recent climate change. One of the main limitations to our understanding of those recent variations and, more generally, of the dynamics of Antarctic sea ice variability at decadal to centennial timescales is the short instrumental time series. Even indirect reconstructions based on instrumental measurements only cover the 20th century. Here we propose a new reconstruction of winds and sea ice extent based on paleoclimate data assimilation covering past centuries. It uses several high-resolution proxies from ice cores in Antarctica (stable water isotopes, snow accumulation and sodium flux) as well as tree-ring width records from mid-latitudes. The reconstruction is highly skilful in the Weddell Sea, where it simulates a decrease in the ice extent during the 20th century following relatively stable values in the preceding centuries. The ice extent in the Ross Sea is generally in the opposite phase to the one in the Bellingshausen–Amundsen Sea. The variability of the winds associated with the Amundsen Sea Low appears to play a large role in those features. To analyze in more detail this potential role of the winds on sea ice extent, sensitivity experiments are performed with the NEMO ocean model and the EC-Earth Earth System Model, in which we force the model to follow observed (or reconstructed) winds through nudging. The first experiments cover the satellite era, as we have the most precise estimate of wind changes in this period. The second step is to nudge the models using the reconstructed winds covering the past centuries.
Jack Landy, Shiming Xu, Wenkai Guo, Engenii Salganik, Jianbin Huang, Malin Johansson, Polona Itkin, Anthony Doulgeris, Dmitry Divine, Sebastian Gerland, Arild Sundfjord, Long Lin, Lei Zhang
Corresponding author: Jack Landy
Corresponding author e-mail: jack.c.landy@uit.no
The high Arctic is feeling the effects of global climate warming like few other places on Earth. Encroaching Atlantic waters are pushing back the sea ice edge, transforming the regional climate, revealing opportunities for shipping along the northern sea route, and impacting Northern Hemisphere weather forecasting. However, satellite sensors have always struggled to accurately monitor sea ice trends in this dynamic and challenging region. The ice cover contains an ever-changing mix of older and younger ice types, a thick and variable snow load that obstructs ice thickness measurements, with an ice edge location that varies seasonally and between years. The INTERAAC project assembles a complimentary team of researchers from China and Norway to generate a reconciled multi-mission climate data record (CDR) of sea ice properties in the Atlantic Arctic. INTERAAC is one of the projects funded under a bilateral call on Arctic climate between the Norwegian and Chinese Polar Science Programs. Here we summarize the goals of the project, which is running from 2022–26. By integrating SAR, altimetry and field observations, we aim to eliminate the inter-mission biases currently preventing detection of climate-relevant trends in the Atlantic sector of the Arctic. Our new data will enable the investigation of coupled air–snow–ice–ocean processes driving sea ice retreat along the polar front in the Atlantic sector. Idealized sea ice–ocean model experiments, initialized with observations from the CDR, will target the teleconnections between Arctic sea ice conditions in the Atlantic sector and extreme winter weather and climate forcing over Eurasia.
Jack Landy, Claude de Rijke Thomas, Isolde Glissenaar, Isobel Lawrence, Alek Petty, Robbie Mallett, Carmen Nab, Michel Tsamados
Corresponding author: Jack Landy
Corresponding author e-mail: jack.c.landy@uit.no
The Copernicus Polar Ice and Snow Topography Altimeter (CRISTAL) mission, set to be launched in 2028, will measure and monitor polar sea-ice thickness, its overlying snow depth, and the elevation of the Earth’s ice sheets. Here, we investigate the radar and laser freeboards obtained from three ongoing polar-orbiting satellites to mimic the sensing configuration of CRISTAL over Arctic sea ice. We apply a physical model for the backscattered radar altimeter echo over sea ice to the ESA Ku-band mission CryoSat-2 operating in SAR mode and to the ISRO/CNES Ka-band mission AltiKa SARAL operating in pulse-limited (LRM) mode. Radar scattering theory indicates that the Ku-band sensor may detect the snow-sea ice interface and the Ka-band sensor may detect the air-snow interface under certain snow conditions. However, previous studies have suggested that the height of the radar’s maximum backscattering intensity, at both frequencies, can depend on variable snow properties such as the layering and basal salinity. Our physical model confirms the role of an additional variable: the roughness of the snow and sea ice surfaces, for identifying the principal backscattering height at both Ku- and Ka-band frequencies. The surface roughness controls the relative balance between diffuse and specular snow and sea-ice backscattering mechanisms. So, the roughness statistics must be properly represented in the altimeter echo model to accurately retrack the radar waveform, with the impact of roughness larger in LRM mode than in SAR mode. We fit the model simulations, which aim to account for the roughness bias, to observed CryoSat-2 and AltiKa waveforms over Arctic sea ice during winters 2018/19, 2019/20 and 2020/21 and compare the radar freeboards to coinciding laser freeboards from NASA’s ICESat-2. Differences between AltiKa/ICESat-2 freeboards and CryoSat-2 freeboards have been used previously as a first approximation for the pan-Arctic snow depth distribution. We will discuss these freeboard differences in the context of variable snow penetration depths and consider implications for the upcoming dual-frequency altimetry mission CRISTAL. This is a contribution to the ESA Polar+ Snow on Sea Ice Project.
The role of ocean heat transport from the Atlantic into the Arctic Ocean on sea ice variability
David Schroeder, Danny Feltham
Corresponding author: David Schroeder
Corresponding author e-mail: D.Schroeder@reading.ac.uk
The decrease of Arctic sea ice affects the future climate in the Arctic and beyond. Therefore, it is important to understand the drivers of sea ice variability and trend. Available observations of the Atlantic inflow to the Barents Sea show a strong negative correlation with sea ice area and extent in Barents Sea over the period 1997–2010. Several observational and model studies conclude that the ocean heat transport is the main driver for sea ice decrease and variability. In our study, we analyse a historical nine-member simulation with the UK Earth System Model (UKESM1) performed for CMIP6 from 1850–2014 and several ocean–sea ice simulations forced by atmospheric reanalysis data. Over the whole 165-year period, the UKESM simulation confirms previous findings showing that the ocean heat transport between Norway and Svalbard (Barents Sea opening; BSO) is strongly correlated with the winter sea ice extent in the Barents Sea. However, this correlation is only caused by decadal variability and there is no correlation in the shorter atmospheric-forced simulations. All simulations show a strong correlation between the annual mean incoming longwave radiation with winter sea ice extent and thickness. Composite analysis suggests that the atmospheric circulation is the main driver of sea ice winter variability: Southerly winds push sea ice northwards, advect warm and moist air into the Barents Sea, increase the incoming longwave radiation and the melting from top and, thus, cause a low sea ice extent.
On the retrieval of sea ice properties by means of ultrawide band microwave radiometer
Gaelle Parard, Giacomo de Carolis, Giovanni Macelloni, Anastase Charantonis, Marion Leduc-Leballeur
Corresponding author: Gaelle Parard
Corresponding author e-mail: parard.g@irea.cnr.it
CryoSat-2 provides an estimation of sea ice thickness with high accuracy for thick sea ice, and the L-band radiometer of SMOS can give more accurate sea ice thickness up to 1.5 m. Although the merging product from the two satellites provides a good sea ice thickness estimation, some uncertainties remain, mainly for the thin sea ice and in the range 0–1 m, which will become more and more relevant in forthcoming years because of the clear diminution of multi-year ice in the Arctic. Some studies and experimental data were collected both in Antarctica and Greenland highlighted the fact that 0.5–2 GHz microwave radiometry provides information to fill this gap. In the framework of the CryoRad-FO project funded by the Italian Space Agency, we developed a preliminary retrieval algorithm to estimate sea ice properties (ice salinity, ice temperature and sea ice thickness) in the Arctic from 0.5–2 GHz. The analysis was conducted by a microwave emission model (Snow Microwave Radiative Transfer) used to simulate brightness temperature. This is a multi-layer model where each layer is defined by temperature, liquid and solid water content, salinity and density. These parameters are provided by the 1-D thermodynamic Semi-Adaptive Multi-phase Sea-Ice Model (SAMSIM) forced by ERA-5 ECMWF reanalysis (precipitation, temperature at 2–m, short-wave and long-wave downward mean flux). Data over the Arctic from June 2017 to November 2021 are used to build a large dataset of realistic synthetic brightness temperature. Retrieval of sea ice properties is based on the artificial network approach with competitive learning called a self-organizing map. This method builds a classification that allows a particular set of sea ice properties (salinity, temperature and sea ice thickness) to be associated with a particular brightness temperature spectrum. Over a total of 16 000 locations, 70% of the available dataset is used to train the neural network, 20% for validation and 10% for testing. In this work, we will describe algorithm steps, retrieval results and sensitivity between brightness temperature and sea ice properties. These results show a link between brightness temperature and the mean sea ice parameters. This will be used to improve retrieval, giving more sea-ice details such as multi-year/first year, profiles, snow properties.
Regime shift in Arctic Ocean sea-ice thickness
Hiroshi Sumata, Laura de Steur, Dmitry Divine, Mats Granskog, Sebastian Gerland
Corresponding author: Hiroshi Sumata
Corresponding author e-mail: hiroshi.sumata@npolar.no
The Transpolar Drift Stream (TPD) carries sea ice formed in the Pacific and Siberian sectors of the Arctic Ocean to the central Arctic, and further toward the Atlantic sector of the Arctic. Ultimately, the ice exits the Arctic Ocean through the Fram Strait, located between northeastern Greenland and Svalbard. Since a major fraction of sea ice outflow from the Arctic Ocean to the Subarctic North Atlantic occurs through Fram Strait, sea ice properties in Fram Strait represent basin-wide characteristics of Arctic sea ice. The Fram Strait Arctic Outflow Observatory, maintained by the Norwegian Polar Institute, has been monitoring sea ice draft continuously with moored upward looking sonar instruments in the core of the outflow at a latitude of ~79° N since 1990. The ice thickness record from the observatory reveald a clear and distinct shift of sea-ice regime from thicker and deformed ice to thinner and more uniform ice cover. After the shift, the modal thickness reduced by approximately 1 m (2.7 m to 1.7 m), and the fraction of thick and deformed ice was reduced by about half and has not recovered to date. The uniformity of ice thickness (measured by fraction of ice in the mode) has also significantly increased (by 67%) after the shift. The timing of the shift follows a two-step drop in Arctic-wide sea-ice residence time in 2005 and 2007. The mean residence time of sea ice, from its formation to the arrival at Fram Strait, reduced by approximately 1.6 years (4.3 years to 2.7 years) after the shift. The reduction of the residence time is correlated with a reduction of summer sea ice concentration in areas of sea ice formation (Alaskan sector: r = 0.65, Siberian sector: r = 0.73). Significant reduction of summer sea ice concentration in these areas also occurred in 2005 and 2007. September sea ice concentration dropped from 46% to 26% in the Alaskan sector and from 57% to 26% in the Siberian sector. Concurrently, the September mean sea surface temperature in these areas has risen from below 0°C to 0.6°C. These changes made it difficult for ice formed during a previous winter to survive the summer melt (the mean residence time dropped from 15 months to 6 months) and resulted in a drop in Arctic-wide sea-ice residence time. We demonstrate that a simple model describing the stochastic process of dynamical sea-ice thickening can explain the observed changes of ice thickness distribution as a result of the reduced residence time.
Arctic sea ice drift in extended range forecasts
Ilona Välisuo, Steffen Tietsche
Corresponding author: Ilona Välisuo
Corresponding author e-mail: ilona.valisuo@fmi.fi
This study addresses sub-seasonal forecasts of sea ice drift speed in the Arctic in winter. Ice drift is a complex problem where atmosphere, ocean, and ice itself play critical roles. Sea ice motion is controlled by wind forcing, ocean forcing, ice rheology, Coriolis force and ocean surface tilt. The first three are usually the dominant terms of the ice momentum balance. The quality of the ice drift forecasts comes down to the model’s ability to represent the wind forcing, ocean forcing, and ice concentration and thickness. In sub-seasonal timescales the initial sea ice conditions and the atmospheric forecast are crucial for the drift speed forecast, and we assume the ocean condition to play a lesser role. Many sea ice forecast evaluations have focused on sea ice concentration, extent or volume. We aim to broaden our knowledge by analyzing the horizontal ice sea motion in forecasts. Ice motion is important in redistributing the multiyear ice, preconditioning the upcoming melt season, and transporting the ice to lower latitudes, where it is more vulnerable to melt. Ice drift is critical for navigation, as it may cause leads to open or close quickly. The two main large scale features of Arctic sea ice drift are the Beaufort Gyre (BG) and the Transpolar Drift Stream (TDS). The reduction of sea ice concentration and thickness has led to a more mobile ice pack in the Arctic at least since the 1980s. These points in mind, we analyze how the ECMWF extended range forecast reproduces the ice motion in the BG and the TDS. We use ensemble forecasts initialized in winters 2000–20, each covering a forecast time of 46 days. We present general statistics of the forecasts, and case studies for winters 2016/17 and 2020/21. Winter 2016/17 was characterized by increased cyclone activity, which led to the collapse of the Beaufort Sea high pressure and reversal of the BG. Winter 2020/21 was quite the opposite, with decreased cyclone activity and intense anticyclonic ice transport in the BG. We expect that the forecast model was able to capture these atmospheric anomalies and transfer their effect into the sea ice drift patterns. This project was funded by grant number 339409 from the Academy of Finland.
Estimating summer sea ice thickness from satellite passive microwave measurements
Sang-Moo Lee, Jong-Min Kim, Byung-Ju Sohn, Sang-Woo Kim, Hyun-Chul Kim, Hoyeon Shi, Andrey Pnyushkov
Corresponding author: Sang-Moo Lee
Corresponding author e-mail: sangmoolee@snu.ac.kr
Although summer sea ice thickness (SIT) is an important factor in weather/climate analysis and prediction, pan-Arctic observations of summer SIT have been a challenging problem. In order to solve this, this study proposes a method for retrieving Arctic basin-scale sea ice draft, defined as the depth of sea ice below sea level, using advanced microwave scanning radiometer (AMSR)-measured brightness temperatures (TBs). It is revealed that the time series of AMSR-observed TBs is highly correlated with the corresponding time series of ice drafts measured by an upward-looking sonar (ULS) over the Beaufort Sea during the ice melting period. Using this finding, the relationship between AMSR-measured TBs and ice drafts were investigated and thus an empirical model for estimating ice draft was developed. The developed model equation well depicts the general thinning process of Arctic sea ice during the summer of 2021. The estimated ice drafts from the developed model equation were validated with other ULS measurements, which were not used for constructing the model equation, demonstrating that the developed models can be useful to estimate summer sea ice drafts over the pan-Arctic area. Since approximately 90% of sea ice is located below sea level, the conversion of the estimated ice draft into sea ice thickness is less sensitive to the uncertainty of the snow depth input. Therefore, the ice draft can be accurately converted into sea ice thickness. The converted sea ice thickness was also compared with ice mass balance buoy-measured sea ice thickness, showing a good agreement between them. It is important to note that the proposed method can produce summer Arctic basin-scale sea ice thickness distributions on a daily basis, which is definitely helpful to assimilate summer sea ice distribution in the sea ice prediction model and/or numerical weather prediction model.
Time-series analysis of SAR backscatter from icebergs at L-and C-band
Laust Færch, Wolfgang Dierking, Nick Hughes, Anthony P. Doulgeris
Corresponding author: Laust Færch
Corresponding author e-mail: laust.farch@uit.no
Maritime traffic is expected to increase in the Arctic in the coming years, with an increasing number of vessels operating close to and within sea-ice-covered areas. Small icebergs embedded within sea ice pose a big risk for ships, and the detection and mapping of these are essential for maritime safety in these regions. Additionally, iceberg mapping is important for environmental research because melting icebergs represent a potential flux of fresh water to the ocean, impacting local salinity and circulation. In open water, icebergs are detected operationally using synthetic aperture radar (SAR) satellite missions, typically carrying C-band sensors. However, previous work focusing on C-band images has suggested that it is difficult to detect icebergs embedded in sea ice, especially if the sea ice is deformed. First studies indicate that L-band SAR such as the planned Copernicus mission ROSE-L may offer improved detectability of icebergs. Comparisons between C- and L-band data are still sparse. In this study, a time series of overlapping SAR images from Sentinel-1 (C-band) and ALOS-2 (L-band), covering a study area over Belgica Bank, northeast Greenland, was analyzed. Here, the location of over 1000 icebergs embedded in either level or deformed land-fast ice was verified using optical Sentinel-2 images. By investigating the backscatter contrast between the icebergs and the surrounding sea ice during a period covering spring and summer, the detectability of the icebergs could be derived, high contrast suggesting that the icebergs are easier to detect. The results of the investigation show that, while the C-band data offer sufficiently high contrast for most icebergs in level sea ice in spring under freezing conditions, low contrast is generally seen for icebergs in deformed sea ice. On the other hand, L-band images show high contrast for both level and deformed ice in the spring. The difference at both L- and C-band is low for both sea ice types in summer when temperatures rise above zero degrees. The results suggest that detecting icebergs in sea ice should preferably be carried out using L-band sensors. However, under melting conditions this remains very difficult even at L-band. The results of this study provide valuable information for improving mapping strategies for icebergs in sea ice, which will play a critical role in enhancing maritime safety in the Arctic.
Malin Johansson, Suman Singha, Randall Scharien, Torbjørn Eltoft, Stephen Howell, Gunnar Spreen
Corresponding author: Malin Johansson
Corresponding author e-mail: malin.johansson@uit.no
Automatic sea ice classifications struggle with some well-known ice type separations; multiyear ice (MYI) vs young ice (YI) and open water (OW) vs sea ice. Using SAR images from RADARSAT-2 (C-) and ALOS-2 (L-band) we show that the polarization difference (PD; VV-HH), can be used to separate YI types from the surroundings in both frequencies, provide good separability between high backscatter YI and MYI and between OW and sea ice. PD may also aid the separability of the new ice (NI) and YI. PD can be derived both from dual- (co-), quad-polarization and compact polarization images. Here we focus on changes in backscatter, scattering mechanisms, co-pol power ratio (VV/HH) and PD within the SAR images from the freeze-up to the melt onset, combined with in-situ data from MOSAiC, N-ICE2015, Nansen Legacy, Canadian Archipelago and Belgica Bank. In addition to different environmental conditions, data span a range of incidence angles and sea ice types. The co-pol power ratio has been shown to distinguish OW and NI from thicker sea ice but provide limited separability between thin ice and OW, PD can aid this separation and have a reduced sensitive to incidence angle variations and noise. Overall OW and NI have high positive PD values (VV > HH); as the ice grows from NI via YI to first-year ice (FYI) the PD values turn negative (HH > VV) but with a lower magnitude; and for thicker FYI and MYI the values stabilize around 0. The change in PD is probably dependent on the penetration depth, as during MOSAiC the change occurred later in time in the L-band than C-band data for the thin ice surrounding the MOSAiC floe and coincided with the thermodynamic sea ice growth. Scattering analyses indicate predominant surface scattering for these areas from October to December. PD varies with sea ice roughness where smooth (deformed) FYI and MYI sea ice has low (high) variability for both frequencies, and this can aid separation between the two. PD for L-band has a higher sensitivity to the melt onset compared to C-band and may be used to indicate melt onset. As such the two frequencies complemented one another. Upcoming L-band missions, e.g. NISAR,ALOS-4 and ROSE-L guarantee continued L-band sea ice data and can provide fully polarimetric acquisitions along with high ground coverage to achieve an optimal scenario for L-band SAR based sea ice monitoring. The Sentinel-1 and Radarsat Constellation missions will provide continuity in C-band data for the foreseeable future.
Sea-ice deformation in a new brittle rheology
Einar Ólason, Guillaume Boutin, Anton Korosov, Pierre Rampal, Timothy Williams, Madelen Kimmritz, Véronique Dansereau, Abdoulaye Samaké
Corresponding author: Einar Ólason
Corresponding author e-mail: einar.olason@nersc.no
We present a new brittle rheology for large-scale sea-ice modelling called the brittle Bingham–Maxwell rheology (BBM). BBM further develops the Maxwell–Elasto-Brittle (MEB) and Elasto-Brittle (EB) rheologies to simulate the ice cover on a decadal time scale or longer. This BBM adds to the MEB by demanding that the ice deforms under convergence in a purely elastic manner when internal stresses lie below a given compressive threshold. This prevents excessive convergence present in long simulations with the MEB. In this presentation, we briefly introduce the new rheology and then demonstrate its ability to reproduce observed sea-ice deformation patterns using an implementation of BBM into the neXtSIM sea-ice model. The neXtSIM results show that BBM gives results in good agreement with the observed spatial scaling, the probability density functions, and the spatial patterns of sea-ice deformation. The new rheology also provides good temporal evolution of the extreme deformation values (P90) of deformation.
Yuan Zhang, Wenjun Lu, Raed Lubbad, Sveinung Løset, Andrei Tsarau
Corresponding author: Wenjun Lu
Corresponding author e-mail: wenjun.lu@ntnu.no
Sea ice deformation is concentrated on linear kinematic features (LKFs) such as ridges and leads. The ridging and leads opening processes are highly related to fracture of sea ice. In ice dynamics studies, various ice rheology models have been proposed and applied in modelling such localized ice deformation scenarios. However, most of the approaches adopted are based on continuum mechanics (i.e. no explicit fracture). All the detailed fracturing processes are either characterized by visco-plastic deformation (e.g. the Elastic/Visco-Plastic (E/VP) model and its derivatives) or a damage-number-induced material weakening (e.g. the Maxwell–Elastic-Brittle (MEB) model and its derivatives). These ice rheology models have been successfully applied in various scenarios, primarily at large scales. However, there are emerging needs for: 1) a more physically informed parameterization towards upper-scale models; and 2) even higher resolution ice deformation modelling. Hence, we take a dive into the detailed fracturing processes and the formation processes of LKFs at floe scale (i.e. 10 m–10 km). In pursuing this objective, we explored the potential of applying a promising mesh-free numerical method, peridynamics (PD), in modelling floe-scale ice fractures. PD offers a physically and mathematically consistent theory through which spontaneous emergence and propagation of cracks can be achieved. The integral nature of the governing equations in PD remains valid even if a crack appears. We investigated in this paper the tensile fracture (e.g. leads opening) of an elastic heterogenous ice floe. The modelling results were compared with published numerical results obtained by another numerical method. The pros and cons of PD and its potential in this application are discussed.
Nicholas Williams, Danny Feltham, Peter Jan van Leeuwen, Nicholas Byrne, Ross Bannister, David Schroeder
Corresponding author: Danny Feltham
Corresponding author e-mail: d.l.feltham@reading.ac.uk
In the last decade, there has been significant undertaking to produce new observations of the Arctic sea ice cover, with improved spatiotemporal coverage, allowing researchers to better understand the state of the Arctic sea ice system in new detail. In this work we use the recently developed sea ice data assimilation system, CICE-PDAF, to reanalyse the Arctic sea ice cover over the satellite era. We assimilate (in various combinations) several sea ice observations, including a year-round sea ice thickness product and a sub-grid scale sea ice thickness distribution product, alongside observations of sea ice concentration. The assimilation of year-round sea ice thickness provides substantial improvements to the modelled sea ice thickness in comparison to independent observations. The assimilation also has significant consequences on the modelled distribution of the ice thickness across the Arctic, particularly in regions of multi-year ice, and reduces regional model biases.
Sergei Kirillov, Igor Dmitrenko, David Babb, Jens Ehn, Nikolay Koldunov, Soeren Rysgaard
Corresponding author: Sergei Kirillov
Corresponding author e-mail: sergei.kirillov@umanitoba.ca
The ice bridge in Nares Strait is a well-known phenomenon that affects the liquid and solid freshwater flux from the Arctic Ocean through the strait and controls the downstream North Water polynya in northern Baffin Bay. Recently, the ice bridge has been in a state of decline, either breaking up earlier in the year or not forming at all, and thus increasing sea ice export out of the Arctic Ocean. The decline of the ice bridge has been ascribed to thinner and therefore weaker ice from the Arctic Ocean entering Nares Strait, but local forcing also affects the state of the ice bridge and thus influences when it breaks up. Using remotely sensed data, we highlight negative ice thickness anomalies of up to 15–20 cm along the northern and western coasts of Kane Basin and attribute them to the heat from warmer subsurface waters of Atlantic and Pacific origin, respectively. The impact of oceanic heat on ice growth within the ice bridge is best exemplified by the recurrent formation of a sensible heat polynya within the ice bridge near Cape Jackson in northwest Greenland. We suggest that the enhanced heat transfer in that area is controlled by tidally driven upwelling and vertical mixing resulting in a localized heat flux of 70 W m–2, although this value might be overestimated. Both the areas of thinner sea ice and the polynya at Cape Jackson are suggested to weaken the ice bridge and thus promote its earlier collapse. We further investigate oceanic impact on ice growth in Nares Strait using the sea ice–ocean model FESOM2. Specifically, we investigate the impact of hundreds of grounded icebergs, which originated from the Humboldt glacier, on the vertical heat exchange in eastern Kane Basin. All those icebergs are located within the region with pronounced negative anomalies of ice thickness and, therefore, could be responsible for their formation. We used four different model setups (with and without icebergs, with and without tide) to find out if the grounded icebergs do considerably alter the vertical heat fluxes within the considered region.
Under-ice PAR levels during polar night recorded by autonomous profilers
Lisa Matthes, Philippe Massicotte, Edouard Leymarie, Achim Randelhoff, Claudie Marec, Mathieu Ardyna, Hervé Claustre, Marcel Babin
Corresponding author: Lisa Matthes
Corresponding author e-mail: lisa.matthes@takuvik.ulaval.ca
The rapidly shrinking sea ice cover, a result of the warming climate, is impacting all levels of the Arctic marine food web. However, model predictions about the future of the sea-ice-associated ecosystems (sympagic and pelagic) are hampered by the logistical challenges to collect large spatial and/or temporal datasets in this remote region, especially from November to April when the seasonal Arctic ice cover expands and reaches its maximum extent. The deployment of autonomous sampling platforms, such as ice-avoiding biogeochemical (BGC) Argo floats, has widely expanded our capabilities to monitor the seasonal dynamics of Arctic phytoplankton blooms in the presence of sea ice and during polar night. Still, measuring algal growth at extremely low light intensities remains challenging due to levels of photosynthetically available radiation (PAR, 400–700 nm) that can be much lower than the noise threshold of frequently used irradiance sensors. In this poster, we present novel measurements of extremely low PAR below sea ice during polar night in winter 2021 and 2022, which were recorded by BGC-Argo floats equipped with novel irradiance MPE-PAR sensors (Biospherical Instruments Inc.) in Baffin Bay. Under-ice PAR data were collected every 3 days throughout the ice-covered winter period, reaching a profile depth below 100 m until the sensor noise threshold of 6.9×10–7 μmol photons m–2 s–1 was surpassed. Recorded PAR at 10 m at the float location ranged between 0.2×10–4 and 0.6 μmol photons m–2 s–1 during polar night with a sun elevation below zero degrees. Ultimately, these data represent an important contribution to the ongoing investigation of previously observed mid-winter phytoplankton growth.
Suman Singha, Fabrizio Baordo, André Emil Jensen, Gorm Dybkjær, Rasmus Tonboe
Corresponding author: Suman Singha
Corresponding author e-mail: ssi@dmi.dk
The dynamic nature of snow-covered sea ice in the Polar regions presents significant challenges for accurately simulating its surface properties, particularly in relation to the absorption, emission and scattering of microwave frequencies. This high degree of complexity makes it difficult to incorporate realistic representations of snow and ice behavior into large-scale models. As a result, it poses a challenge in developing an observation operator that can generate realistic simulations of brightness temperatures over the sea ice. Having accurate simulations of brightness temperatures would be extremely useful for validating sea ice models, incorporating real-time data, and gathering atmospheric information. In this regard, within the framework of the OSI SAF and Arctic Passion project, we are conducting sensitivity studies to gain a deeper understanding of snow and ice properties. This will aid in the further development of forward modeling at microwave frequencies, with the aim of constructing a reliable observation operator for sea ice. We employed the in-house DMI HYCOM-CICE ocean sea ice coupled model, which includes information on skin temperature, ice thickness, and snow depth, to simulate brightness temperature using the SMRT model (https://github.com/smrt-model). Our initial simulation took into account multiple, non-uniform layers of snow and sea ice. Model parameters, such as snow salinity and density, were derived from in-situ measurements and existing literature. We compared the simulated brightness temperatures at different frequency bands with observed brightness temperatures from AMSR-2 level 1 swath data. Our presentation will focus on the results of our initial sensitivity studies, which were based on adjusting SMRT model parameters and varying physical sea ice parameters. We are also investigating effects of different ocean sea ice coupled model from different met offices as input to our model setup. This work has been partially funded by the European Union’s Horizon 2020 research and innovation programme through the project Arctic PASSION under grant agreement No. 101003472.
A simple method for estimating the effective thermal conductivity of snow on Arctic sea ice
Ian Raphael, Donald Perovich, Christopher Polashenski, David Clemens-Sewall
Corresponding author: Ian Raphael
Corresponding author e-mail: ian.a.raphael.th@dartmouth.edu
Snow is an excellent thermal insulator, on the order of ten times less conductive than sea ice. Thus, despite its thin average depth on Arctic sea ice, snow plays an important role in controlling heat fluxes out of the ice cover. Here, we present a simple method to determine the effective thermal conductivity of snow (ks*). This parameter combines the effects of conduction through the snow crystal lattice, water vapor advection, and air convection in interstitial spaces in the snow, all assumed to be one-dimensional in the vertical. We assume continuity of heat fluxes through the ice and snow and use Fourier’s law of heat conduction with linear temperature gradients to solve for ks*. We show that time-averaged estimates of ks* using linear gradients are insensitive to nonlinearities in the true temperature gradients when estimates are averaged over an adequate time period.
Mareike Bach, Hauke Flores, Ilka Peeken, Anton. P. van de Putte, Jacqueline Stefels
Corresponding author: Mareike Bach
Corresponding author e-mail: m.g.bach@rug.nl
Arctic and Antarctic pack ice are a unique habitat for ice-associated microalgae, which provide the basis of the food web through primary production and carbon transfer to higher trophic levels. Additionally, various ice-algal species can produce the secondary metabolite dimethylsulfoniopropionate (DMSP). This sulphur compound is a precursor of the climate-active gas dimethylsulfide (DMS). Several physiological functions of DMSP have been suggested, including functions in stress response such as cryoprotectant or osmolyte. In addition, DMSP functions as a chemical signalling compound for higher trophic levels. However, the concrete physiological role of DMSP is still elusive and it is uncertain how microalgae will adapt to changing conditions in terms of DMSP production. In order to predict higher or lower production of DMSP in the oceans in the future it is important to quantify the production of DMSP relative to growth in ambient communities of sea ice. There have been limited studies investigating combined DMSP and carbon production in sea ice and especially newly formed sea ice in autumn season has been under-sampled. We present results from newly formed sea ice sampled on the RV Polarstern expedition PS129 in March/April 2022 through the Weddell Sea. Biomass, chlorophyll a content and species composition were analysed in ice cores from pancake ice, first year ice, under-ice water and an autumn pancake ice bloom. Incubation experiments at a range of light intensities (photosynthesis-irradiance curve), to which a set of stable isotopes were added, were used to quantify DMSP production, DMSP uptake rates and primary production in the bottom sea ice communities. This comprehensive data set will be used to provide new insights into the Southern Ocean sulphur cycle and phytoplankton dynamics during an atmospherically relevant season, the autumn.
A new structure for the sea ice essential climate variables of the global climate observing system
Thomas Lavergne, Stefan Kern, Signe Aaboe
Corresponding author: Thomas Lavergne
Corresponding author e-mail: thomasl@met.no
Climate observations inform about the past and present state of the climate system. They underpin climate science, feed into policies for adaptation and mitigation, and increase awareness of the impacts of climate change. The Global Climate Observing System (GCOS), a body of the World Meteorological Organization (WMO) assesses the maturity of the required observing system and gives guidance for its development. The essential climate variables (ECVs) are central to GCOS and the global community must monitor them with the highest standards in the form of climate data records (CDR). Today, a single ECV – the sea ice ECV – encapsulates all aspects of the sea-ice environment. In the early 1990s, it was a single variable (sea-ice concentration), later it became an umbrella ECV for four variables (adding thickness, edge/extent, and drift). Since the GCOS Implementation Plan 2022, the sea ice ECV has grown even more and holds seven variables. In this contribution, we will present a joint effort in the global sea-ice community to suggest a new structure for the sea-ice ECV. We argue that GCOS should consider a set of seven ECVs (sea-ice concentration, thickness, snow-depth, surface temperature, surface albedo, age, and drift) rather than squeezing these variables under a single ECV. These seven ECVs are critical and cost-effective to monitor with existing satellite Earth Observation capability. Such a change will also reconcile the way sea-ice variables are handled by GCOS with the practice in other ECV domains. A full list of contributors is found in the published BAMS paper: https://doi.org/10.1175/BAMS-D-21-0227.1
Henrik Fisser, Anthony Paul Doulgeris, Knut Vilhelm Høyland
Corresponding author: Henrik Fisser
Corresponding author e-mail: henrik.fisser@uit.no
The glaciers of the archipelagoes Svalbard, Franz Josef Land, and Novaya Zemlya produce most icebergs in the Barents Sea. These icebergs are usually shorter than 100 m, which is at the scale of the resolution of the operational Sentinel-1 extra-wide-swath (EW) synthetic aperture radar (SAR) data, and this impedes detecting and characterizing them using these SAR observations. We aim at obtaining iceberg statistics over multiple years and across the Barents Sea. To understand the quality of the iceberg detection in space and time, we have verified a Sentinel-1 iceberg detector in the Barents Sea. In the first phase of this study, we investigated the size and shape agreement of detections obtained from Sentinel-1 EW data and matches found in co-located Sentinel-2 acquisitions. The Sentinel-2 reference icebergs were automatically identified using an outlier detection applied on the visual and near-infrared bands. In addition, we propose a new method for refining the Sentinel-2 reference icebergs at the sub-pixel level by employing a spectral unmixing method at the detection edges. The reference iceberg counts, sizes and shapes were verified in selected areas, using PlanetScope data, which provides eight measurements per Sentinel-2 measurement. For detecting icebergs in the Sentinel-1 EW data, we applied the constant-false-alarm-rate algorithm, which delineates outliers based on local statistics of the sea clutter. To compare Sentinel-1 and Sentinel-2 detections, we matched icebergs manually as they are subject to drift. In agreement with other studies, we found an overestimation of the iceberg area estimates in the SAR data. No meaningful linear relationship was evident between the area estimates of Sentinel-2 and Sentinel-1. However, we obtained a strong correlation between the summed HH backscatter intensities by detection, and the corresponding area estimates of the Sentinel-2 detections. This may imply that better area estimates can be deduced from the summed backscatter of an iceberg detection rather than its area. Possible variations of this relationship depending on incidence angle, wind speed, air temperature and seasons will be investigated. The Sentinel-1 iceberg area estimates and counts will be compared statistically with the Sentinel-2 reference icebergs on a gridded area to understand the spatio-temporal agreement across the Barents Sea.
Understanding the role of mechanical break-up in determining sea ice floe size
Adam Bateson, Daniel Feltham, David Schröder, Scott Durski, Jennifer Hutchings, Yanan Wang, Byongjun Hwang
Corresponding author: Adam Bateson
Corresponding author e-mail: a.bateson@reading.ac.uk
Traditionally continuum sea ice models have assumed that sea ice is made up of floes of a uniform size, if they include an explicit treatment of floe size at all. There have been several recent efforts to develop a floe size distribution (FSD) model for use in continuum sea ice models. These FSD models include several processes that have been observed to influence floe size including lateral melting, welding, and wave-induced breakup of floes. FSD models have not yet included a physically derived treatment of in-plane breakup of floes by brittle fracture under high convergent stresses, or breakup of floes by melting in existing cracks or other weaknesses. It is challenging to fully characterize such floe breakup processes due to limited availability of in-situ observations, however discrete element models (DEM) offer the potential to create a virtual laboratory of sea ice to explore sea ice fragmentation, and the resulting FSD sensitivity to relevant factors such as wind forcing and the spatial distribution in sea ice thickness. Using the CICE continuum sea ice model we show that the inclusion of a simplified representation of brittle fracture derived processes improves model performance in simulating the shape of the FSD for floes of intermediate size, motivating the need for a physically derived parameterization of these processes. We discuss how we can combine in-situ observations of sea ice and results from simulations using a sea ice DEM to develop parameterizations of in-plane breakup of floes for subsequent application in continuum models. Finally, we will use a sea ice DEM to simulate the fracture of sea ice under different forcing conditions and with varying sea ice states to identify important sea ice parameters and processes in determining the size of the floes that form from in-plane breakup events.
Mara Neudert, Stefan Hendricks, Christian Haas
Corresponding author: Mara Neudert
Corresponding author e-mail: mneudert@awi.de
The porosity of sea ice strongly controls its physical, ecological and biogeochemical properties. Porosity is subject to seasonal variations and spatial variability, related to ice type and developmental history, and affecting sea ice strength and permeability. As sea ice porosity can be derived from electrical conductivity, a direct method that can be applied on the ground or from airborne platforms is electromagnetic (EM) induction sounding. During the year-long MOSAiC campaign extensive sea ice profile data with the Geophex Ltd GEM-2 multifrequency conductivity sounder were obtained. We present advancements in calibration and inversion procedures. For adaptable inversion, we modified the Phyton EMagPy API for multilayer inversion of sea ice surveys. This study was based on the hypothesis that multifrequency EM data allow to retrieve the increase in brine volume fraction as the ice warms in spring, the macro-scale porosity of rotten ice in summer, and the salinity and depth of overlying melt ponds. The porosity evolution could be reproduced with varying success, but the multilayer inversion improved the ice thickness representation compared to a single-layer subsurface model, which has implications for the ice mass balance.
Mara Neudert, Stefanie Arndt, Markus Schulze, Stefan Hendricks, Mario Hoppmann, Christian Haas
Corresponding author: Mara Neudert
Corresponding author e-mail: mneudert@awi.de
We present maps of the sub-ice platelet layer (SIPL) thickness and ice volume fraction beneath the landfast sea ice in Atka Bay adjacent to the Ekström Ice Shelf (southeastern Weddell Sea, Antarctica). The widespread SIPL beneath Antarctic fast ice is indicative of basal melt of nearby ice shelves, contributes to the sea ice mass balance and provides a unique ecological habitat. Where plumes of supercooled ice shelf water (ISW) rise to the surface, rapid formation of platelet ice can lead to the presence of a semi-consolidated SIPL beneath consolidated fast ice. Here we present data from extensive electromagnetic (EM) induction surveying with the multi-frequency EM sounder GEM-2 between May and December, 2022. It includes monthly survey data along a fixed transect line across Atka Bay between May and October, as well as comprehensive mapping across the entire bay in November and December. The GEM-2 surveys were supplemented by drill hole thickness measurements, ice coring and CTD profiles. A new data processing and inversion scheme was successfully applied to over 1000 km of EM profiles with a horizontal resolution of one meter. We obtained layer thicknesses of the consolidated ice plus snow layer, the SIPL, and the respective layer conductivities. The latter were used to derive SIPL ice volume fraction and an indicator for flooding at the snow–ice interface. The robustness of the method was validated by drill hole transects and CTD profiles. Our results support conclusions about the spatial variability of the ocean heat flux linked to outflow of ISW from beneath the ice shelf cavity. Temporally, we found that the end of SIPL growth and the onset of its thinning in summer can be linked to the disappearance of supercooled water in the upper water column.
Lasse Jensen, Eva Kjærgaard, Maria Cifarelli, Rossella DiPompeo, Martina D’Agostino, Jennie Schmidt, Corina Wieber, Jane Skønager, Dorte Søgaard, Bernadette Rosati, Merete Bilde, Lars Lund-Hansen, Kai Finster, Tina Šantl-Temkiv
Corresponding author: Lasse Jensen
Corresponding author e-mail: lassejensen@bio.au.dk
The Arctic is warming faster than the rest of the world, making it particularly vulnerable to the impacts of climate change. One consequence of this warming is a decline in multiyear sea ice cover, which results in an increasing open-ocean surface with a much lower albedo therefore leading to positive feedback and enhanced warming. Another factor that plays a role in regulating the temperature in the Arctic is the type and extent of cloud cover. Aerosols that can serve as cloud condensation nuclei or ice nucleating particles (INPs) are key for cloud formation. Some microorganisms are known to produce INPs, but it is not well understood which microorganisms are responsible, which environments they inhabit, and how active they are. In this study, we set out to investigate the partitioning of INPs between the Arctic marine and atmospheric environment by combining in situ measurements with laboratory experiments. First, we used a modified ice-finger to grow sea ice using natural samples from West Greenland and found that INPs concentrate into the ice fraction during sea-ice formation, and that these INPs typically are associated with microorganisms. Next, we wanted to understand the temporal and spatial dynamics of INPs in Arctic sea ice. We collected sea ice cores from the Arctic before and during the spring sea ice phytoplankton bloom and analysed them using cold-stage INP measurements, flow-cytometry, and amplicon sequencing. The results showed that there are between <105∙L–1 (at the top) and >106∙L–1 (at the bottom) INP-10 present in the Arctic sea ice. Finally, we wanted to determine the potential contribution of sea ice to the atmospheric INP pool in the Arctic. We introduced natural samples of sea ice from Nuuk into a temperature-controlled sea spray simulation chamber and quantified the microorganisms and INPs present in the bulk water and air before and after aerosolization. The preliminary results suggests that the highly active INPs are efficiently aerosolized into the atmosphere during bubble-bursting where they may contribute to the formation of ice in clouds. Overall, this study provides new insight into the role of Arctic sea ice as a reservoir for INPs and the microorganisms that produce them, as well as the mechanisms by which INPs are released into the Arctic atmosphere. This information is important for understanding the impact of climate change on the Arctic region and the potential consequences for the rest of the world.
Modelling the evolution of Arctic multiyear sea ice over 2000–18
Heather Regan, Pierre Rampal, Einar Olason, Guillaume Boutin, Anton Korosov
Corresponding author: Heather Regan
Corresponding author e-mail: heather.regan@nersc.no
Multiyear sea ice (MYI) cover in the Arctic has been monitored for decades using increasingly sophisticated remote sensing techniques, and these have documented a significant decline in MYI over time. However, such techniques are unable to differentiate between the processes affecting the evolution of the MYI. Further, estimating the thickness, and thus the volume of MYI remains challenging. Here we use the neXtSIM sea ice model, coupled to the ocean component of NEMO, to investigate the changes to MYI over the period 2000–18. We exploit the Lagrangian framework of the sea ice model to introduce a new method of tracking MYI area and volume, which is based on identifying MYI during freeze onset each autumn. We use the ice type climate data record from C3S to (i) discuss the optimal MYI fraction threshold used to distinguish sea ice type in the model and (ii) evaluate the modelled MYI extent. The model is found to successfully reproduce the spatial distribution and evolution of observed MYI extent. We discuss the balance of the processes (melt, ridging, export, and replenishment) linked to the general decline in MYI cover. The model suggests that rather than one process dominating the losses, there is an episodic imbalance between the different sources and sinks of MYI. We identify those key to the significant observed declines of 2007 and 2012; while melt and replenishment are important in 2012, sea ice dynamics play a significant role in 2007. Notably, the model suggests that convergence of the ice, through ridging, can result in large reductions of MYI area without a corresponding loss of MYI volume. This highlights the benefit of using models alongside satellite observations to aid interpretation of the observed MYI evolution in the Arctic.
Improving year-round sea ice observations by combining satellite altimeters and novel techniques
Rachel Tilling, Alejandro Egido, Nathan Kurtz, Andy Ridout, Andrew Shepherd, Mia Vanderwilt, Donghui Yi, Dexin Zhang
Corresponding author: Rachel Tilling
Corresponding author e-mail: rachel.l.tilling@nasa.gov
Continuous advancements in satellite technology are improving the resolution of sea ice altimetry from space. Since October 2010, the European Space Agency (ESA) CryoSat-2 (CS2) radar altimeter has surveyed the Arctic Ocean up to 88° N. The synthetic aperture radar (SAR) altimeter on-board CS2 has a footprint along the flight direction of ~300 m, which is an order of magnitude improvement compared with conventional radar altimeters. A novel data processing technique for SAR altimeters known as fully-focused SAR (FF-SAR) processing further improves the along-track resolution of CS2, down to just a few tens of meters. NASA’s ICESat-2 (IS2) laser altimeter was launched in September 2018. IS2 provides observations of the polar regions with the same latitudinal coverage as CS2, and has an ~11 m pulse footprint. In 2020, ESA shifted the orbit of CS2 to periodically align with IS2 and provide near-coincident data as part of the ongoing Cryo2Ice campaign. To accurately reconcile altimetry estimates of key climate variables such as sea ice thickness, the sampling differences (geophysical and radiometric) between different datasets and missions need to be accounted for. Here we map Arctic sea ice topography (lead density, floe density and floe length) using the different satellite datasets to better understand how each ‘sees’ the sea ice surface, and potential biases associated with their retrieval techniques. Data from the Cryo2Ice campaign will be used to intercompare the same parameters along individual satellite tracks. Finally, we present preliminary results from NASA’s summer 2022 IS2 sea ice validation campaign, with a focus on IS2 and airborne lidar performance over melt ponds.
David Babb, Ryan Galley, Sergei Kirillov, Jack Landy, Stephen Howell, Julienne Stroeve, Walter Meier, Jens Ehn, David Barber
Corresponding author: David Babb
Corresponding author e-mail: david.babb@umanitoba.ca
Multiyear sea ice (MYI) is the thickest and most resilient component of the Arctic ice pack. Historically, MYI covered a majority of the Arctic Ocean and was conserved through the Beaufort Gyre, however MYI area has declined and the Arctic ice pack has transitioned to a predominantly seasonal ice cover. The area of MYI depends on the balance of MYI export, melt and replenishment, with the latter being the sole source of new MYI. Here, we quantify these three terms from 1984–21 and examine their variability and contribution to the MYI budget of the Arctic Ocean. MYI export primarily occurs through Fram Strait, and while export is highly variable there is no long term trend. Less MYI is lost to melt than export, however MYI melt has significantly increased over the study period with a substantial increase in the Beaufort Sea, which has interrupted MYI transport through the Beaufort Gyre. The budget demonstrates that previous estimates of MYI replenishment have been underestimated, with our new time series revealing a significant increasing trend in replenishment over the 38-year record. This has been enabled by MYI loss opening a greater area of the central Arctic to seasonal ice that is able to persist through summer at higher latitudes. Overall, MYI area in the Arctic Ocean has declined at 77 000 km2 a–1 since 1984. However, underlying this trend are two notable stepwise reductions around 1989 and 2007. The first reduction was due to a change in the Arctic Oscillation which flushed MYI out of the Arctic Ocean. The second reduction was due to a confluence of anomalously high melt and export, and low replenishment, between 2006 and 2008. Following this latter reduction, MYI consolidated in the central Arctic, reducing MYI export through Fram Strait and encouraging a period of stability in MYI area. However, continued observations of MYI thinning, coupled with the transition to younger MYI and signs of dynamic weakening within the MYI pack lead us to speculate that this stability may soon be disrupted and MYI may undergo another reduction. Using the MYI budget we speculate as to what role each term will play in the future loss of MYI as the Arctic moves towards being seasonally ice-free and therefore free of MYI.
Jeff Ridley, Edward Blockley, Mark Ringer
Corresponding author: Jeff Ridley
Corresponding author e-mail: jeff.ridley@metoffice.gov.uk
Polar amplification arises due to the albedo feedback and changes to clouds and water vapour. We investigate the surface exchange of water, as Arctic becomes completely ice free by the end of an idealized global warming scenario using the CMIP6 climate model HadGEM3-GC3.1-LL. The model shows a clear seasonality in the Arctic of total column water vapour (TCWV) across the transition to an ice-free state. When a month becomes almost ice-free the rate of increase in TCWV with warming transitions to a new state. In autumn and winter the surface evaporation increases rapidly under sea ice decline and consequently the atmosphere becomes more convective. Sea ice decline in spring and summer has less impact on surface evaporation which is constrained by a stratified boundary layer and weak surface to atmosphere temperature gradients.
Progress towards a single-column model (icepack) case study for the MOSAiC expedition
David Clemens-Sewall, Marika Holland, Angela Bliss, Christopher Cox, Michael Gallagher, Jennifer Hutchings, Bonnie Light, Donald Perovich, Chris Polashenski, Kirstin Schulz, Madison Smith, Melinda Webster
Corresponding author: David Clemens-Sewall
Corresponding author e-mail: dcsewall@ucar.edu
To improve the representation of sea ice thermodynamics in Earth system models (ESMs), we seek to compare model simulations with observations. However, direct comparison between models and in‐situ observations is challenging because the sea ice components of ESMs typically simulate vastly larger spatial scales (e.g. 100×100 km) than the footprint of in‐situ observations (e.g. 1×1 km). Additionally, standalone sea ice simulations are typically forced with reanalysis data, which have considerable biases and uncertainties. To address these challenges, we are developing a MOSAiC‐based forcing package to conduct a case study of the Icepack model. We simulate the evolution of snow and sea ice on a Lagrangian, drifting parcel following the Central Observatory from October to July. The model is initialized from ice conditions observed in autumn and forced with observed fluxes from the atmosphere and ocean. We present progress towards this case study, including the compilation of the initial conditions and forcing, and preliminary comparisons of the simulated snow and ice thicknesses and albedo evolution with observations. We discuss the challenges introduced by ice dynamics, lateral boundary conditions, and measurement gaps. Anticipated applications of this case study include improved parameterizations of melt ponds, snow and albedo processes.
Wenkai Guo, Anthony Paul Doulgeris, Malin Johansson, Polona Itkin, Torbjorn Eltoft, Jack Christopher Landy
Corresponding author: Wenkai Guo
Corresponding author e-mail: wenkai.guo@uit.no
We present an ongoing work to derive a classified time series of sea ice types over the Atlantic Sector of the Arctic Ocean for the winter season from 2002 to present based on wide-swath synthetic aperture radar (SAR) data. This region is characterized by highly variable and dynamic sea ice conditions, with strong and increasing presence of winter storms. Temporally consistent, large-scale monitoring of sea ice parameters is crucial for the understanding of ice-atmosphere interactions governing the transfer of wind forcing to ice dynamics. Sea ice type, which is among the most basic sea ice parameters, is retrieved using SAR data from a combination of C-band sensors with similar central frequency and spatial resolution including Sentinel-1, RADARSAT-2, and Envisat ASAR. We use a sea ice classifier incorporating per-class incidence angle (IA) dependencies to correct for systematic radar backscatter changes in the wide IA range associated with the large SAR dataset. The classified time series will enable us to assess seasonal and inter-annual sea ice type variations, especially the variability in new ice formation which strongly influences physical and biogeochemical processes across the ocean–ice–atmosphere interface. We further use separately derived sea ice deformation from SAR to evaluate the ability of the classification to capture sea ice deformation. The classification can serve as a basic dataset contributing to future physical sea ice studies and modelling work involving the Atlantic Arctic Ocean. This study is part of the collaborative project INTERAAC (air–snow–ice–ocean INTERactions transforming Atlantic Arctic Climate) between Norway and China, which aims at generating a reconciled multi-mission climate data record for Atlantic Arctic sea ice.
A mushy model of gas transport in porous sea ice
Joe Fishlock, Andrew Wells, Christopher MacMinn
Corresponding author: Andrew Wells
Corresponding author e-mail: andrew.wells@physics.ox.ac.uk
Chemical transport through porous sea ice is an important factor in sea-ice biogeochemical processes. The porous mixture of ice crystals and liquid brine allows multiple transport pathways for gas forming species, which can dissolve in the liquid brine or nucleate into buoyant gas bubbles. The flow of gas bubbles provides a key physical uncertainty. We develop a model of gas transport in sea ice treated as an evolving three-phase porous medium of solid ice, liquid brine and gas bubbles. We extend the so-called mushy-layer theory for porous ice and saltwater systems, and include a gaseous phase. A phenomenological model is developed for gas bubble rise through liquid channels within the porous ice, including the physics of viscous drag on the pore walls and bubble trapping. The model dynamics are illustrated in simplified case studies including seasonal ice growth and melt. The size ratio of gas bubbles versus pores provides an important control on gas bubble dynamics and the seasonal evolution of gas fluxes to the atmosphere.
Kedong Zhang, Feiyue Wang
Corresponding author: Feiyue Wang
Corresponding author e-mail: feiyue.wang@umanitoba.ca
Microplastics (MPs) in the ocean have been raised as a global environmental concern. In recent years, sea ice has been recognized as an effective temporary reservoir for MPs in polar oceans. Since sea ice serves as a carrier of MPs, seasonal melting and release of MPs has become a new environmental concern in large areas of the Arctic. Furthermore, the weathering processes in the ocean and sea ice environment change the physical and chemical properties of MPs, thereby changing their capability of accumulating contaminants. Here we report a year-long mesocosm experiment with a focus on the weathering and metal accumulating processes of MPs in the sea ice and ocean environment. The experiment was carried out at the Sea-ice Environmental Research Facility (SERF) in Winnipeg, Canada. Three types of microplastics (polyethylene (PE), polypropylene (PP), and polystyrene(PS)) with different sizes and colors were put into 15 microcosms, at a concentration of 100 pcs L–1, in the outdoor pool filled with artificial seawater. The experiment lasted for 18 months during which the pool went through several cycles including open water, sea ice formation, sea ice melting and open water stages. Microplastics in seawater and sea ice were sampled at various temporal intervals to study their weathering processes and metal accumulating capacities. The results showed that the weathering processes changed the surface roughness and chemical structures (e.g. increase of carbonyl and hydroxyl groups) of PE and PP, and that the accumulation of mercury (Hg) by MPs was correlated with the degree of the weathering extent. The PS employed in this experiment with higher density than water was less affected by the weathering due to sinking at bottom of the microcosms. Additionally, dark-colored MPs were observed to accelerate the melting of surface sea ice. These results suggest that sea ice serves as an effective carrier of not only MPs pollution but also other contaminants, which needs to be further monitored and assessed for their impact on the Arctic marine ecosystem and human health.
Melinda Webster, Marika Holland, Chris Polashenski, Hannah Chapman-Dutton
Corresponding author: Melinda Webster
Corresponding author e-mail: melindaw@uw.edu
Melt ponds on sea ice play an important role in the Arctic climate system. Their presence alters the partitioning of solar radiation: decreasing reflection, increasing absorption and transmission to the ice and ocean, and enhancing ice melt. The spatio-temporal properties of melt ponds thus modify ice albedo feedbacks and the mass balance of Arctic sea ice. In this work, we combine climate modeling, Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) observations and satellite products to investigate key impacts and atmospheric drivers of the temporal variability in melt pond coverage and associated albedo change. The analysis begins with an inter-comparison between two configurations of Version 2 of the Community Earth System Model (CESM2): one with and one without tuned parameterizations of snow albedo and melt onset temperature. The tuned version was optimized for improved realism of the mean sea-ice state. We investigate how the sensitivity of the sea ice surface response to summer snowfall events and cold air outbreaks differs between model configurations, and assess potential model biases using local scale MOSAiC observations and pan-Arctic scale satellite observations. The scaling, synthesis and intercomparison of model and observational results are used to pinpoint atmosphere–ice processes that warrant improved representation, which, in turn, can aid accurate simulations of albedo feedbacks in a warming climate.
Mallik Mahmud, Ben Holt, John Yackel
Corresponding author: Mallik Mahmud
Corresponding author e-mail: msmahmud@ucalgary.ca
The utility of low-frequency SAR, such as L-band imagery, has attracted renewed interest in sea ice applications, given its advantages over C-band frequency in the new sea ice regime. Several studies suggested that L-band SAR is optimal for year-round sea ice monitoring. In light of this, more L-band SAR missions are operational, pending or approved. The upcoming NASA-ISRO’s NISAR mission will acquire L-band SAR images over sea ice in polar regions starting in early 2024. One of the cryosphere requirements of the NISAR mission is to provide high-resolution sea ice products. Therefore, the NISAR mission provides an unprecedented opportunity in polar regions to research and facilitate the development of operational sea ice products. Compared to other frequencies, research gaps exist on L-band SAR utility for sea ice geophysics, rheology and kinematics studies. The ISRO L- & S-band airborne SAR (ASAR) instrument was a testbed for the NISAR mission. NASA and ISRO collaborated to conduct a simultaneous collection of L- & S-band (24 and 9 cm wavelengths) synthetic aperture radar (SAR) imagery over selected regions of interest for developing and refining algorithms in advance of the NISAR mission. This study utilizes the high-resolution L- and S-band SAR imagery over snow-covered sea ice in the Beaufort Sea in December 2019. Here we investigate the backscatter variability from fully polarimetric L- and S-band over various sea ice classes. This work is the first look at fully polarimetric S-band SAR images before the NISAR mission becomes operational next year. We also performed a machine learning approach to produce sea ice classification maps from L- and S-band. Finally, this work demonstrates the utility of the upcoming NISAR mission for operational sea ice monitoring in polar regions.
John Yackel, Mallik Mahmud, Torsten Geldsetzer, Karl Kortum, Suman Singha, Vishnu Nandan, Amy Macfarlane, Stefanie Arndt, Robert Ricker
Corresponding author: John Yackel
Corresponding author e-mail: yackel@ucalgary.ca
Our understanding of snow distributions on sea ice in the polar regions is severely restricted owing to its heterogeneity, both in space and time. Previous synthetic aperture radar (SAR) and surface-based scatterometer studies of snow-covered first-year sea ice (FYI) have provided the electrothermo-physical basis for development of active microwave-based snow thickness retrievals. These studies have shown that changes in snow temperature on FYI are manifest as changes in total backscatter with most of this backscatter change occurring for snow temperatures between –10 and –2&dec;C, when snow brine volumes change rapidly with temperature. However, direct inversion of snow thickness must contend with complexities arising from competing scattering mechanisms within the snow volume and at the snow–ice interface. These complexities are a result of varying dielectric properties which are dominated by the presence of brine, primarily in the basal snow layer, as a function of snow salinity, density, and temperature. A high temporal resolution X-, C- and L-band SAR dataset was collected during MOSAiC in support its of science objectives, coincident with extensive on ice meteorological and in situ snow thickness data. Our study period between 1 April and 10 May 2020, with an air temperature range from –33 to +1°C, was characterized by weekly-scale cycles of air temperature; in once instance, warming more than 30°C in less than 3 days. We exploit this air temperature cycling to investigate the microwave scattering characteristics of various sea ice types near to the central observatory at snow temperatures well below freezing. Here, we are principally interested in how the snow thickness and snow volume temperature indirectly controls microwave backscatter through its control on basal layer snow brine volume and snow dielectrics as a function of ice type. We find that backscatter change, regardless of frequency, is significantly smaller for non-saline, older ice types (i.e. multiyear sea ice), for a given change in air temperature, compared to younger and saline ice types (i.e. FYI). We also find the backscatter change larger for the higher frequency X- and C-band SAR compared to L-band for a given change in air temperature and for comparable snow thicknesses and ice types. We conclude by discussing the potential of multi-frequency SAR for estimating snow thickness distributions during late winter periods when such temperature cycling is present.
The effects of late spring and summer snowfall on Arctic sea ice radiative forcing
Hannah Chapman-Dutton, Melinda Webster
Corresponding author: Hannah Chapman-Dutton
Corresponding author e-mail: hrchapmandutton@alaska.edu
The decline in Arctic sea ice has had major impacts on the climate system, particularly relating to the ice-albedo feedback. Since fresh snow on top of bare or melting sea ice increases the surface albedo on local scales, the impact of summer snow events can have a negative radiative forcing effect, which could inhibit sea ice surface melt. In this study, we compared snow depth and meteorological data from buoys and satellite retrievals of surface and atmospheric conditions to identify and characterize summer snow accumulation case studies across the Arctic from 1993 to 2017. CERES retrievals were used to quantify the changes in surface albedo before and after the snow accumulation events. Information from these case studies was then scaled up to find similar events on a pan-Arctic scale using a Lagrangian sea ice parcel database. In this way, we characterized the frequency, magnitude, and duration of summer snow accumulation events similar to those observed by buoys. Finally, a simple radiative transfer model was used to quantify the impact of summer snowfall events on the surface and top-of-atmosphere radiative forcing over the entire Arctic region. This study provides new information on observed snow accumulation events in summer by combining multiple sources of in situ, satellite, and modeled data. Such results will be particularly useful in understanding the impacts of ephemeral summer weather on surface albedo and their propagating effects on the radiative forcing over Arctic sea ice.
Snow depth on landfast sea ice in the Canadian Arctic from ICESat-2 and CryoSat-2 and SAR imagery
Hoi Ming Lam, Torsten Geldsetzer, John Yackel, Stephen Howell, Monojit Saha, Julienne Stroeve, Vishnu Nandan
Corresponding author: Hoi Ming Lam
Corresponding author e-mail: hoiming.lam@ucalgary.ca
Following the orbital alignment of CryoSat-2 with ICESat-2 in July 2020, also known as the CRYO2ICE campaign, near-simultaneous radar and lidar measurements over polar areas are available at approximately every 31 hours. This enables the retrieval of snow depth on sea ice by differencing measurements from the two altimeters, albeit at either coarse spatial resolutions or monthly scales. Due to the presence of land masses and intersecting waterways, the approach used for the Arctic Ocean cannot be applied to many areas in the Canadian Arctic because of mixed altimetric signals that may partially originate from land. This study integrates decametre-resolution synthetic aperture radar (SAR) imagery with CRYO2ICE measurements to estimate near-shore winter snow depth on landfast sea ice in the Canadian Arctic. Preliminary results indicate correspondence between the altimetric surface heights and SAR backscatter coefficient. During a field campaign, snow depth and sea ice properties were collected on landfast first-year sea ice in Dease Strait near Cambridge Bay, Nunavut, in spring 2022. These measurements are used to validate outputs from algorithmic snow depth estimates. Based on the first-order assumption that rougher sea ice, which is signified by higher SAR backscatter, would entrap thicker snow, a machine learning algorithm is being developed to estimate winter snow depth on landfast sea ice in the Canadian Arctic. The algorithm will learn snow depth for predefined SAR backscatter classes on landfast first-year ice and multiyear ice at near-coincident CRYO2ICE tracks. The ice classes where CRYO2ICE tracks are located are used as a training set to derive an instantaneous model needed to estimate near-shore snow depth on sea ice of that ice class. The ice types within the SAR scene are obtained operational ice charts published by the Canadian Ice Service. Our SAR-ML approach can improve the temporal resolution of snow depth estimates from CRYO2ICE. For the best case, at Alert, Nunavut (82.5° N), there are about five cross-tracks per month, with substantially less for sites further south. This provides greater spatial coverage for the estimates, effectively increasing the temporal frequency for many areas. The use of alternative satellite data sources such as SARAL/AltiKa for snow surface height and Sentinel-3-SRAL for sea ice height for retrieving snow depth is explored to increase the number of cross-tracks within the Canadian Arctic
Niels Fuchs
Corresponding author: Niels Fuchs
Corresponding author e-mail: niels.fuchs@uni-hamburg.de
The onset of melt pond formation on Arctic sea ice leads to a large reduction in surface albedo. After a time period of a couple of days to weeks, increasing permeability of the underlying ice triggers the pond drainage event, giving rise to a transient recuperation of the ice albedo to pre-pond states. Central to our hitherto understanding of this drainage event is a rigid sea-ice topography, in which the pond water level equalizes to sea level. I present observations of pond bathymetries on the MOSAiC floe that oppose a rigid topography. I hypothesize that pond drainage can also be driven by a lift of the pond bottom as a deformation induced by buoyancy and flexibility of the ice, even when the pond level itself is already in or close to hydrostatic equilibrium with the ocean. In addition, the ice at the bottom of the pond may bend downward under the load of the pond water during formation, and the weight of pond water could increase permeability when reaching a crack load. The observed evolution of the pond bottom was determined using a newly developed pond bathymetry retrieval method from aerial image data. I compare those observations to thin plate mechanical descriptions of the ice cover and heat budget estimates for a first assessment of the connected processes, proving that pond bottoms deformed, and that pond extent significantly impacts the probability of pond bottom deformation. It thus advances our current understanding of melt pond processes impacting time scales and dynamics of summer melt pond evolution and sea ice albedo.
The path of light through the Arctic sea ice cover
Niels Fuchs, Leif Riemenschneider, Dirk Notz, Steven Fons, Christian Katlein, Bonnie Light, Marc Oggier, Maddie Smith, Ran Tao
Corresponding author: Niels Fuchs
Corresponding author e-mail: niels.fuchs@uni-hamburg.de
Measurements of light partitioning in the sea ice cover are scarce, yet important to quantify the vertical distribution of solar radiation that contributes to the energy budget of the sea ice system and stimulates biological activity. During MOSAiC, we successfully deployed the newly developed lightharp system. We thus obtained in-ice light intensity measurements from multiple depths along the vertical transmission path of the light, observed from polar night to the end of July 2020 (Leg 2-4). We present profile time series of derived optical properties in the ice with respect to the observed and simulated evolution of sea ice properties, indicating key drivers and influential layers within the ice. Combining the lightharp data with co-deployed sensors closes the radiative transfer from the snow surface to the ice–ocean interface. The budget shows exemplarily that below the snow cover, light attenuation in the ice contributed only 1% to the total attenuation in the snow and ice layer. We confirm with the non-destructive in situ measurements that internal scattering layers lose their reflectivity with the onset of snow and ice melt. We aim to inform radiative transfer model development with these unique observations of in-ice light properties. The project was funded by the BMBF grant nr. 03F0867A
Late summer sea ice extent primary driver of summer season coastal erosion rates in Arctic Alaska
Alice Bradley, Galen Cassidy, Kennedy Lange, Matthew Wiseman
Corresponding author: Alice Bradley
Corresponding author e-mail: alice.c.bradley@williams.edu
Erosion along the coastline of the Alaskan Arctic poses an existential threat to local communities. Rising air temperatures have been implicated in accelerating erosion rates via permafrost thaw, increasing wave energy, and shortening the duration of a shore-fast ice buffer, processes that drive block collapse on permafrost coastlines. However, the resolution of available satellite imagery has historically been too low to allow the quantification of seasonal erosion rates across large areas of the Arctic, and studies comparing these mechanisms have been inconclusive. This study uses PlanetScope high-resolution satellite imagery to calculate seasonal (ice-free summer versus mostly ice-covered winter) erosion rates in the Alaskan Arctic. Erosion rates as high as 9.5 m month–1 were observed using semiannual images from 2017–22 for two stretches of Alaska’s Beaufort Sea coast (Drew Point and Cape Halkett). Erosion is significantly higher (>5 m month–1) in summer than in winter (<2 m month–1). Summer erosion rates were then compared against a number of environmental factors, including reanalysis meteorological conditions and passive microwave sea ice retrievals for both local pixels and the broader region. We found that summer erosion rates are highly correlated with regional ice extent in August–October, and there is little evidence of correlation with wind speeds, air temperature, number of stormy days, or sea ice extent/concentration at other times of the year. This suggests that increased water temperature coupled with larger fetch areas are driving accelerations in coastal erosion.
Ocean-sourced snow on Arctic sea ice
Amy R. Macfarlane, Moein Mellat, Hanno Meyer, Camilla Brunello, Ruzica Dadic, Martin Werner, Martin Schneebeli
Corresponding author: Amy R. Macfarlane
Corresponding author e-mail: amyrmacfarlane@gmail.com
The role of snow on Arctic sea ice is vast; it insulates and decreases sea ice growth in winter, reduces surface sea ice melt due to its high albedo, provides fresh water in summer, is a source of ions and sea salt aerosols, and currently causes a 70% uncertainty in sea ice thickness estimations from altimetry methods. Despite its importance, snow on sea ice is relatively understudied due to the inaccessibility of the central Arctic. In this study we use stable water isotope and salinity analysis of the winter snow cover in the high Arctic to find that sublimation of the sea ice surface is directly producing snow at the snow–ice interface. We call this ‘ocean-sourced’ snow. This is a result of the high-temperature gradients in the snowpack producing large water vapour fluxes in the Arctic snowpack. We found that sublimation of the sea ice surface contributes to up to 28% of the snowpack. This has major implications when comparing precipitation estimates to in situ snow depth measurements, the chemical composition of sea ice, and salinity distributions within the snow cover.
Elise Droste, Dorothee C. E. Bakker, Hugh J. Venables, Elizabeth Jones, Mario Hoppema, Giorgio Dall’Olmo, Bastien Queste, Oliver Legge, Michael Meredith, Gareth Lee
Corresponding author: Elise Droste
Corresponding author e-mail: e.droste@uea.ac.uk
The sea-air CO2 exchange estimates and variability for the Arctic and Southern Oceans have high uncertainties due to many unknowns related to the role of sea ice. These uncertainties are largely due to paucity of year-round data, hindering a complete picture of interacting processes and representation in ocean-climate models. The Rothera Time Series (RaTS) has almost a decade of year-round dissolved inorganic carbon (DIC) and total alkalinity data collected between 2010 and 2020 in Ryder Bay, along the West Antarctic Peninsula (WAP). Based on this unique dataset, we see that the duration of sea ice cover regulates wintertime fugacity of CO2 (fCO2) in the seawater and the CO2 flux through its preconditioning of water column stratification. Winters with short sea ice duration have higher mean seawater fCO2 than winters with a long duration of sea ice cover, because it allows more DIC from subsurface water to mix into the surface layer. However, sea ice meltwater input from the previous melting season may change this relationship, indicating inter-seasonal dependencies. The mean wintertime seawater fCO2 explains a large part of the annual means of fCO2 and sea-air CO2 flux, despite sea ice cover restricting direct sea-air CO2 gas exchange for large periods of the winter season. By affecting the onset, duration, and retreat of sea ice, large-scale atmospheric circulation, such as the Southern Annular Mode and the El Niño Southern Oscillation, either enhance or weaken the annual CO2 uptake in Ryder Bay. Small-scale ice–ocean biogeochemical interactions further complicate the intra-seasonal and interannual variability. The variability in wintertime marine carbonate chemistry in sea ice covered regions is underrepresented in our current understanding due to a general lack of wintertime in situ observations in the Southern Ocean. This work highlights the importance of wintertime processes in the interannual variability of CO2 uptake along the WAP, which can provide insights to larger regional studies in polar oceans. This work was funded by the Natural Environment Research Council (NERC) through the EnvEast Doctoral Training Partnership (NE/L002582/1).
High-resolution sea ice concentration budget analysis in the Arctic’s Last Ice Area
Gillian Cheong, Michel Tsamados, Stephen Howell, Jack Landy, Harry Heorton
Corresponding author: Gillian Cheong
Corresponding author e-mail: gilliancheongyuyan@gmail.com
Recent decades have shown a rapid decline in Arctic sea ice as a result of anthropogenic climate change. The historically oldest and thickest Arctic sea ice located in the region of the central Arctic Ocean north of the Canadian Archipelago and Greenland is known as the Last Ice Area (LIA), and is expected to be the most stable and last the longest against climate change. However, recent behaviour of the ice pack indicates that the LIA may be less resilient than expected. This study combines satellite-derived observations of sea ice drift and concentration, to present the first high- resolution wintertime observed sea ice concentration budget in the LIA. The decomposition of the concentration budget (i.e. 5 km) into thermodynamic and dynamic (advection and divergence) terms indicate that ice gain in the LIA is dominated by thermodynamic growth via freezing of ice, with small contributions of advection and convergence. Ice loss is driven by divergence and small contribution of mechanical redistribution via ridging. Ridging is found to occur in convergence zones along the coastlines of Ellesmere Island and Greenland, and may be a prominent ice concentration sink. Future work should focus on validating the budget introduced here against auxiliary products and existing studies, as well as quantifying the volume of ice lost to ridging.
Arttu Jutila, Nils Hutter, Stefan Hendricks, Robert Ricker, Luisa von Albedyll, Gerit Birnbaum, Christian Haas
Corresponding author: Arttu Jutila
Corresponding author e-mail: arttu.jutila@awi.de
Between September 2019 and September 2020, we conducted a total of 35 floe grid and 29 transect flights over the MOSAiC Central Observatories and surrounding sea ice with the airborne laser scanner to map changes of the sea-ice surface during the full annual cycle at high spatial resolution and coverage. In this work, we take advantage of the large and unique data set to take a look at the evolution and variability of sea-ice surface roughness in the Central Observatory and within the Distributed Network. Sea-ice surface roughness has been identified as an important influencing factor for e.g. melt ponds, remote sensing applications, numerous processes acting at the ocean–ice–atmosphere interface, and maritime operations. Here, we calculate sea-ice surface roughness from the point cloud data as the standard deviation of across-swath surface elevation on a per scan-line basis. First results indicate sea-ice surface roughness distributions that are similar both in the Central Observatory and within the surrounding Distributed Network during the analysed first part of the MOSAiC drift from October 2019 to July 2020.
Challenges and opportunities in a new generation of synthetic aperture radar observations of sea ice
Randall Scharien, Steven E.L. Howell, Alex Komarov
Corresponding author: Randall Scharien
Corresponding author e-mail: randy@uvic.ca
The successes of Sentinel-1 and RADARSAT Constellation Mission, and pending launch of new synthetic aperture radar (SAR) missions such as the NASA-ISRO SAR Mission (NISAR) in early 2024, herald a new era in sea ice remote sensing. Though the capabilities of SAR to provide detailed, metre-scale, information about sea ice geophysical properties and ice dynamics have long been known, the recent and projected volumes of SAR data available for research have introduced the need to develop new strategies to most effectively meet cross-disciplinary observational requirements. SAR constellations, consistent acquisitions over polar oceans, and open data policies, are all favorable factors for the implementation of SAR as a key tool for addressing science objectives related to sea ice and climate in both polar regions. This paper will address opportunities for utilizing SAR for scale-appropriate monitoring of sea ice properties and atmosphere–ice–ocean interactions for climate and biophysical research, as well as climate modelling and prediction. Challenges associated with the development of consistent, high-quality, SAR-based sea ice data products are outlined. SAR measured backscatter and phase components are affected by a myriad of complexities due to the interplay between radar system parameters, such as polarization, frequency, and incidence angle, and seasonally and spatially varying sea ice properties. A framework is provided for overcoming these challenges, including using SAR as a scaling tool to link surface-based observations to airborne and satellite for improved understanding. Overall, the expanded usership of SAR by the sea ice research community, as a complement to more commonly used passive microwave- and altimetry-based data products, will be supported by such a framework.
Randall Scharien, Lim Sangwon, Rebecca Segal
Corresponding author: Randall Scharien
Corresponding author e-mail: randy@uvic.ca
The sea ice phenology explorer tool is an interactive and publicly accessible application that is based on an algorithm that utilizes the Google Earth Engine cloud-based platform for the processing and time series analysis of satellite data. The algorithm currently extracts a cloud-filtered, optical reflectance time series from 20+ years of images from moderate resolution imaging spectroradiometer (MODIS) and Landsat program archives. It is initiated by the selection of a point location on a map, or input of geographic coordinates, and produces a set of sea ice indicators linked to physically based reflectance behaviors and selection criteria: freeze-up, melt onset, ice break-up and open water. Interannual variability and trends in these indicators can be plotted or downloaded and assessed in climate, biogeochemical, and sea ice usage/safety contexts. The tool has the advantage of fine spatial scale (500 m grid), enabling users to identify seasonal and inter-annual changes and trends in indicators such as melt onset and ice break-up of local relevance. Users are able to assess specific locations such as bays, hunting grounds and ice trails to understand current conditions (e.g. elapsed time since freeze-up or melt onset), compare different years, and visualize trends in ways that promote making connections to lived experiences and other observed changes such as availability of food and access to hunting grounds. The tool is commensurate with a demonstrated willingness by Arctic residents in Canada to embrace geospatial technology for informed decision-making, is accessible and user-friendly, adaptable by the so-inclined, scalable, and does not prescribe questions or outcomes. Since it is a tool for engagement and visualization, it is not limited to a specific set of sea-ice-related problems and holds potential for being highly impactful in making Arctic marine knowledge available. In this presentation the tool is described, assessments of time series outputs are made and best approaches for potential or realized utilization by Arctic communities are given. Finally, the scaling potential of the application in the context of safe land and sea ice utilization, and livelihood preservation by Inuit, is discussed.
Antarctic landfast sea ice: physical, biogeochemical and ecological significance
Alexander Fraser, Pat Wongpan, Pat Langhorne, Andrew Klekociuk, Kazuya Kusahara, Delphine Lannuzel, Robert Massom, Klaus Meiners, Kerrie Swadling, Daniel Atwater, Gemma Brett, Matthew Corkill, Laura Dalman, Sonya Fiddes, Antonia Granata, Letterio Guglielmo, Petra Heil
Corresponding author: Alexander Fraser
Corresponding author e-mail: adfraser@utas.edu.au
Antarctic landfast sea ice (fast ice) is stationary sea ice that is attached to icebergs grounded in waters up to ~450 m deep and the coast – including ice shelves and other protrusions on the continental shelf, e.g. glacier tongues. Fast ice forms in narrow (up to 200 km wide) bands, and can be up to tens of metres in thickness. In most regions, it forms in autumn, persists through the winter and melts in spring/summer, but may remain throughout the summer in particular locations. Despite its relatively limited horizontal coverage (comprising about 4–13% of overall sea ice extent), its presence, variability and seasonality are drivers of a wide range of physical, biological and biogeochemical processes, with both local and far-ranging ramifications for various key parts of the Earth system. Antarctic fast ice has, until quite recently, been overlooked in many studies, probably due to insufficient knowledge of its characteristics, leading to its reputation as a ‘missing piece of the Antarctic puzzle.’ In this poster we give a synopsis of the current state of knowledge of the physical, biogeochemical and biological aspects of fast ice, focusing on identifying and suggesting ways to address the gaps in our knowledge. We also consider the potential state of Antarctic fast ice at the end of the 21st century, underpinned by Coupled Model Intercomparison Project projections.
The Emperor’s Smooth Floes; or why Emperor penguins care about Antarctic fast ice roughness
Alexander Fraser, Mariapina Vomero, Thomas Johnson, Michel Tsamados, Rebecca Segal, Jan Lieser, Michel Tsamados, Andrew Tedstone, Andrew Klekociuk, Sara Labrousse, Barbara Wienecke
Corresponding author: Alexander Fraser
Corresponding author e-mail: adfraser@utas.edu.au
The Emperor penguin (Aptenodytes forsteri) is the only warm-blooded species to breed during the harsh polar winter at the edge of the Antarctic continent. The vast majority of colonies are located on landfast sea ice (fast ice). The penguins return to their traditional breeding grounds once the fast ice is solid enough, usually during April. From this time until fledging in December, parents alternate between caring for the chick and foraging in the water at the edge of the fast ice. Earlier work focused on the Pointe Géologie colony, Adélie Land, has shown a close relationship between breeding success and the horizontal extent of fast ice surrounding the colony (i.e. higher breeding success occurs when the distance from the colony to the ice edge is shorter, facilitating more frequent foraging trips), but this relationship is not apparent in other East Antarctic colonies (e.g. the Taylor Glacier colony, Mawson Coast) where environmental factors influencing breeding success are poorly understood. Using remote sensing-based datasets of fast-ice roughness acquired from synthetic aperture radar and the multi-angle imaging spectroradiometer in conjunction with recently published maps of fast ice extent, we investigate the hypothesis that fast-ice roughness is a further crucial determinant of breeding success in some regions, in addition to the distance from the colony to the fast ice edge, indicating that traversing a rough surface is more energetically expensive and/or time-consuming. This work underscores the importance of better physical characterization of this crucial element of the coastal Antarctica icescape, and contributes to our understanding of the resilience of this iconic species in the face of projected major environmental changes.
Remotely sensing the wave-affected Antarctic marginal ice zone using pulse-limited radar altimeters
Alexander Fraser, Zhaohui Wang, Takenobu Toyota, Jill Brouwer, Christopher Horvat, Petra Heil, Richard Coleman
Corresponding author: Alexander Fraser
Corresponding author e-mail: adfraser@utas.edu.au
The wave-affected marginal ice zone (MIZ), a zone hundreds of kilometres wide lying between consolidated pack ice and the open ocean, has been implicated as both a region of crucial ocean–sea-ice–atmosphere interaction and a major missing process in coupled ocean–sea-ice models. Our ability to understand the roles of the Antarctic MIZ in the climate system is currently limited by a lack of large-scale, reliable and historical observations of waves propagating through sea ice, and the associated rate of wave attenuation. Although recent work has shown breakthroughs in large-scale MIZ remote sensing from spaceborne laser altimetry, laser-based techniques are at the mercy of a notoriously cloudy Southern Ocean. Reliable radar altimeter-based studies of waves propagating through sea ice, which are indifferent to cloud cover, have been demonstrated as far back as 1984, but these techniques have not been carried forward to more recent (and capable) radar altimeters. Here we present first results of using the modern pulse-limited radar altimeter AltiKa for the purposes of retrieving both significant wave height and MIZ extent in Antarctic sea ice. We show that both wave height and MIZ extent can be retrieved in an automated fashion using a new, simple waveform retracker algorithm focusing solely on retrieving these quantities, and discuss validation to support this assertion. This work indicates the suitability of pulse-limited radar altimeters for MIZ property retrieval back to 2013 using AltiKa, and ultimately back to the late 1970s using other pulse-limited radar platforms, potentially providing critical information for understanding of the Antarctic MIZ.
Julia Martin, Ruzica Dadic, Roberta Pirazzini, Lauren Vargo, Oliver Wigmore, Martin Schneebeli, Brian Anderson, Henna-Reetta Hannula, Huw Horgan
Corresponding author: Julia Martin
Corresponding author e-mail: julia.martin@vuw.ac.nz
Antarctic sea ice is a key parameter for Earth’s energy balance. The snow cover dominates the variability of sea ice’s thermal and optical properties and is essential to understanding sea ice growth and decay. It governs the energy and mass fluxes between the ocean and the atmosphere, sea ice thickness, bottom water formation, and ocean circulation. The current lack of data on the physical properties of the snow and its effect on sea ice leads to large uncertainties in the coupling of climate feedback and results in significant biases in model representations of the sea ice cover. To increase our understanding of the snow-sea ice – interactions, we quantitatively investigated the physical properties of snow on Antarctic sea ice (McMurdo Sound, October–December 2022) using a wide range of ground-based and airborne instrumentation. Here, we present a drone-based method and results for infrared mapping of the snow surface temperature combined with ground surveys of snow depth and sea ice thickness. We used a DJI Matrice 30T drone to simultaneously take RGB and infrared images of the surface and ice of five different 200×200 m measurement fields with different freezing histories. One of the measurement fields is located in a transition zone between sea ice of two different ages (March 2022 and August 2022, respectively) with different snow-thickness distributions. We georeference the drone imagery using ground targets and a mobile DGPS system to account for the vertical tidal displacement. We perform a correction of the temporal temperature changes during the flight using hot ground targets and mobile infrared sensors positioned within the drone footprint. We then explore the link between surface temperatures and the spatial variability of snow depth and ice thickness. This multiparameter 2-D approach allows us to study the influence of the spatial distribution of snow on surface energy balance of the snow-sea ice–ocean system and on sea ice evolution.
Kutalmis Saylam, Aaron Averett, John Andrews, Shelby Short, Mert Ugurhan
Corresponding author: Kutalmis Saylam
Corresponding author e-mail: kutalmis.saylam@beg.utexas.edu
In 2022, the Bureau of Economic Geology (BEG) at the University of Texas at Austin (UT Austin) responded to the US National Aeronautics and Space Agency (NASA) inquiry to participate in an airborne data acquisition campaign over coincident Arctic Sea locations in northwestern Greenland and northeastern Canada. The proposed validation/calibration campaign provides NASA and all other involved scientists with highly accurate airborne lidar data sets to evaluate the accuracy of sea ice surface heights as measured by ICESat-2 ATLAS (Ice, Cloud and Land Elevation Satellite, Advanced Topographic Laser Altimeter System). Further, the study is attempting to quantify depth of sea ice melt ponds using airborne lidar with two distinct wavelengths (green-515 nm and NIR-1064 nm). For these purposes, a Leica Chiroptera-4x airborne lidar system was installed in a Gulfstream-V aircraft with a glass viewport alongside NASA’s Land, Vegetation and Ice Sensor (LVIS). In July 2022, UT Austin and NASA researchers acquired sea ice data during a series of airborne missions, flown from Thule Air Base in Greenland. Despite constraints such as the low flight altitude requirements of Chiroptera, local weather conditions, and other logistical challenges, coincident measurements were collected during two missions. In total, 138 minutes of airborne lidar and high-resolution 4-band imaging data were collected at an altitude of 500 m over the Arctic Sea. The NIR scanner achieved 1 m average point spacing, and the green-wavelength scanner averaged 1.54 m point spacing. Approximately 11 000 km2 of sea ice was mapped by each of Chiroptera’s scanners. Preliminary results indicate robust correspondence (mean difference of 7-8 cm, RMSE is 20 cm) between the Chiroptera NIR and ATLAS-07 sensors for measuring sea ice surface heights. Ongoing efforts will quantify surface height accuracies using green-wavelength data, determine melt pond depths, and apply machine learning methods to predict sea ice surface heights where coincident data were not available.
Donghui Yi, Alejandro Egido, Laurence Connor, Sinéad Farrell, Dexin Zhang, John Kuhn
Corresponding author: Donghui Yi
Corresponding author e-mail: donghui.yi@noaa.gov
The European Space Agency’s Cryosat-2, launched in April 2010, provides the longest record of sea ice freeboard from satellite altimeter observations to date. Its operation overlaps with NASA’s Operation IceBridge (OIB) Airborne Topographic Mapper (ATM) (2009–19) and ICESat-2 (September 2018–present). Various techniques, including the ESA standard algorithm and the Alfred Wegener Institute (AWI) algorithm, are used to produce sea-ice freeboard from Cryosat-2 data. The fully focused SAR (FF-SAR) sea-ice freeboard is from a novel data processing technique developed at NOAA’s Laboratory for Satellite Altimeter. It uses phase information from the standard SAR data to focus echoes along the satellite track, which allows for a better representation of ground radar backscatter variation and improved discrimination of leads and floes over sea ice and will provide improved freeboard estimates compared to the traditional data processing techniques. This study compares Cryosat-2 FF-SAR sea-ice freeboard with the freeboards from the ESA and AWI algorithms, as well as with freeboards from OIB/ATM and ICESat-2. The comparison of data from these sources is complicated by differences in geophysical corrections and spatial and temporal scales. To account for these differences, the study averages the data from OIB/ATM and ICESat-2 to the Cryosat-2 footprints and compares the results to the Cryosat-2 FF-SAR freeboard. The study also compares the Cryosat-2 and ICESat-2 freeboards using their coincident ground-track data and monthly maps. The intercomparison of these freeboards will aid in the calibration and validation of Cryosat-2 FF-SAR freeboard.
Mansi Joshi, Stephen Ackley, Alberto Mestas-Nuñez, Stefanie Arndt, Grant Macdonald, Christian Haas
Corresponding author: Mansi Joshi
Corresponding author e-mail: mansi.joshi@my.utsa.edu
Sea ice formation in the Weddell Sea accounts for 5–10% of annual ice production around Antarctica. The associated brine rejection is key to the formation of Antarctic Bottom Water (AABW), and therefore the global thermohaline and climate system. Sea-ice extent in the Weddell Sea exhibited an increasing trend from the beginning of the satellite period in 1978 until 2016 but has since been decreasing. However, water mass transformation is driven by ice growth and changes in thickness over the continental shelf, rather than changes in overall extent. Therefore, it is important to quantify and understand variations in ice thickness as well as extent. The launch of ICESat-2 in 2018 creates new opportunities to analyze variations in Antarctic sea-ice thickness. In this study, we analyze seasonal and interannual variations in sea ice thickness using ICESat-2 laser altimetry data over the eastern Weddell Sea for 2019–22. Sea-ice thickness is calculated from the ATL10 ICESat-2 freeboard product using the Worby one-layer method. We find that the mean sea-ice thickness decreases in the summer with minimum thickness observed during Jan–Mar and increases towards the winter (Jul–Nov) in the Weddell Sea. The results from the western Weddell region are compared with thickness data obtained by an electromagnetic induction instrument (EM) during the ‘Endurance 22’ expedition, between 15 February and 8 March 2022. We find good agreement between the mean ice thickness obtained from ICESat-2 (1.58 m) and EM surveys (1.67 m). Further study will involve determining the thermodynamic and dynamic components of ice growth.
Josephine Rapp, Thomas Krumpen, Alex Matveev, Warwick Vincent, Connie Lovejoy
Corresponding author: Josephine Rapp
Corresponding author e-mail: josephine.rapp.1@ulaval.ca
The volume and extent of sea ice that survives more than one melt season is declining in the Arctic. The oldest and thickest remaining sea ice can be found along the northern edges of Canada and Greenland where drifting pack ice accumulates and forms a thick perennial ice cover composed primarily of multi-year ice. This region is referred to as the Last Ice Area (LIA) as it is predicted to retain sea ice even when the rest of the Arctic Ocean becomes ice-free in the summer. Depending on its age, sea ice can differ substantially in its physicochemical properties and sustains distinct microbial communities. Habitable space for microbes in ice is present within liquid subzero, hypersaline brines, which form during the freezing process of seawater. Inside these brines, cells and viruses are concentrated, resulting in elevated cell-to-cell and cell-to-virus encounter rates relative to seawater. Sea-ice brines are thus interesting habitats to study the role of virus–host interactions in shaping community dynamics and ecosystem processes, as well as co-evolution under extreme conditions. Here, we compare microbial communities from first-year sea ice (FYI) sampled in the Beaufort Gyre to communities in >5-year-old multi-year ice (MYI) sampled in the LIA. Drift trajectory reconstruction suggests a common source area for both ice types in the Beaufort Gyre. First analyses highlight direct extracts of hypersaline brines from MYI as notably distinct from both the surrounding ice matrix and the seawater. Here, elevated contractions of multiple chemical compounds coincided with higher numbers of microbes and viruses, as well as higher virus-to-microbe ratios than in FYI. We propose that different degrees of transience and environmental stability in FYI versus MYI promotes the establishment of distinct metabolic strategies and microbial interactions. To test this, we are using metagenomic and metatranscriptomic analyses to reconstruct diversity, community structure and individual metabolisms, to establish predominant types of cell-cell and cell-virus interactions. Specifically, we hope to identify signatures of co-evolutionary processes by which microbes and viruses withstand the extreme conditions experienced in subzero brines, as well as the key players driving nutrient cycles in sea ice. Results from this work will contribute to a better understanding of ecosystem functioning in an Arctic Ocean that is rapidly transitioning towards a younger and thinner ice sheet.
Sea ice response to volcanic eruptions in model large ensembles
Andrew G. Pauling, Mitchell Bushuk, Cecilia M. Bitz
Corresponding author: Andrew G. Pauling
Corresponding author e-mail: andrew.pauling@otago.ac.nz
Large volcanic eruptions have a substantial short-term impact on climate due to the injection of sulfate aerosols into the stratosphere. These aerosols cool the troposphere and warm the lower stratosphere over their lifetime. The spatial distribution of the aerosols and their associated climate impacts depend strongly on the location of the eruption, due to the transport of aerosols in the stratosphere by the Brewer–Dobson circulation. A further consideration is how shortwave radiative feedbacks depend on the time of year of the short-term volcanic aerosol forcing. Previous work had shown an asymmetric high latitude response to volcanoes in single models. However, multiple model large ensembles are needed to determine whether the asymmetry is model-dependent or a feature of the local response of the climate system. In this work we make use of the large collection of model large ensembles of fully coupled historical simulations from both CMIP5- and CMIP6-generation models to investigate the impact of historical volcanic eruptions on polar regions. We analyze the response to the Agung, El Chichon and Pinatubo eruptions, which have volcanic aerosol distributions that are Southern-Hemisphere-focused, Northern-Hemisphere-focused and approximately symmetrical, respectively. We find that, for the eruptions confined to one hemisphere, the sea ice expands most in that (same) hemisphere. However, the expansion is greater in the Arctic than in the Antarctic for the Pinatubo eruption. There is a delay of approximately 1 year between the eruption and the peak sea ice response, allowing for volcanic aerosols to reach the pole and the cumulative decrease in absorbed shortwave radiation by the sea ice. In the Arctic, the response peaks in September, while the timing of the peak response in the Antarctic is inconsistent among models. Antarctic sea ice expands more and the Southern Ocean cools more in models of the CMIP5 generation than the CMIP6 generation. We draw two major conclusions from our results. First, the interannual predictability of Arctic sea ice may increase following large volcanic eruptions from which the aerosols propagate into the Northern Hemisphere. Second, the weak response of Antarctic sea ice in CMIP6 models is an inherent feature of the high-latitude Southern Ocean in models under both volcanic and CO2 forcing.
Sea ice and climate impacts from Antarctic ice-mass loss in a multi-model experiment
Andrew G. Pauling, Max Thomas, Inga J. Smith, Jeff Ridley, Torge Martin
Corresponding author: Andrew G. Pauling
Corresponding author e-mail: andrew.pauling@otago.ac.nz
Antarctic ice-mass loss from ice sheets and ice shelves is increasing and is projected to increase further as the climate warms. The fresh water entering the Southern Ocean due to this ice-mass loss has been proposed as a mechanism responsible for the lack of decline in Antarctic sea ice area, in contrast to the sea-ice loss seen in the Arctic. The fresh water impacts sea ice by increasing the density gradient between the near-surface waters and deeper waters around the Antarctic continent, which inhibits vertical transport of warmer, deeper water to the surface. This results in surface cooling and increased sea ice growth, as has been shown in multiple previous studies. Though this increased Antarctic ice-mass loss is expected to impact climate it is absent from almost all models in the current Coupled Model Intercomparison Project (CMIP6), which typically enforce that the continent remain in perpetual mass balance, with no gain or loss of mass over time. Further, previous non-CMIP6 model experiments that include changing Antarctic ice-mass loss suggest that the climate response depends on the model used, and that the reasons for this model dependence are not clear. We use the HadGEM3-GC3.1 model to contribute model experiments to the Southern Ocean Freshwater Release Model Experiments Initiative (SOFIA), an international model intercomparison, in which freshwater is added to the ocean surrounding Antarctica to simulate the otherwise missing ice-sheet mass loss. This unique suite of models will allow us to evaluate HadGEM3-GC3.1 against several other climate models, identify reasons for model discrepancies, and quantify the potential impact of the absence of increasing Antarctic ice-mass loss on Antarctic sea ice and climate. We will give an overview of the SOFIA project including the experiment design and participating models. We will also present preliminary results from the ‘antwater’ experiment outlined in the SOFIA protocol in which a constant freshwater input of 0.1 Sv is distributed evenly around the Antarctic continent at the ocean surface in an experiment with pre-industrial forcing. We will show the response of Antarctic sea ice and the local and global climate to this freshwater forcing.
Nilas: a Southern Ocean mapping platform
Sean Chua, Anton Steketee, Petra Heil
Corresponding author: Sean Chua
Corresponding author e-mail: sean.chua@aad.gov.au
Nilas is a south ocean mapping platform (https://nilas.org) that focuses on remote-sensing products in the sea ice zone. This mapping tool (beta) has been developed by the Australian Antarctic Division for the Antarctic sea-ice zone to support their research and operational activities. Nilas displays multiple layers of physical and biogeochemical variables. These variables are primarily derived from remotely sensed products and updated as source data become available. It can be configured to display other Antarctic related geospatial products including raster and vector data. Nilas is highly accessible, it is run from a web browser and has an intuitive and simple user interface. This is highly valuable for rapid investigations, education and outreach to non-scientific experts. It is also data agnostic in the sense that it combines best-in-field sea ice related remote sensing datasets chosen through consultation with experts. For instance this allows you to combine products from different satellite missions and countries without any downloading or processing. The source code is well documented with both readme files and inline comments. This application is written primarily in Javascript and was developed using Node.js, vite and a small amount of vue. The Nilas platform is based on the Leaflet open source library and we endeveaour to pass on our solutions to web mapping time-series polar projected data to the broader scientific community.
Katharine Andrea Scott, Ray Valencia, Armina Soleymani, Xinwei Chen
Corresponding author: Katharine Andrea Scott
Corresponding author e-mail: ka3scott@uwaterloo.ca
There are numerous approaches to retrieve sea ice concentration (SIC) from satellite data, but few quantify uncertainty in these SIC retrievals. For climate data records this is important because uncertainty is a piece of integrating data into probabilistic projections as well as risk assessment. There are also increasing quantities of data, which allows the possibility to use a data-driven approach for sea ice concentration estimation. One method to obtain an uncertainty estimate in a data driven problem (such as SIC retrieval from satellite data) is through a Bayesian neural network (BNN). In this talk we will present results from recent experiments training and evaluating a BNN approach to estimate SIC over a full year in two regions i) Baffin Bay and ii) Beaufort Sea. The method uses passive microwave brightness temperatures and features from reanalysis as input data. The role of the input features and possibility of data leakage will also be discussed in the context of current and future implementations, which could also consider other data sources. Results indicate the daily mean model error and uncertainty increase significantly during melt onset and at times may be correlated with significant wind events or atmospheric moisture. The uncertainty is further decomposed into epistemic uncertainty (related to the model parameters) and aleatoric uncertainty (related to the data). Consistent with previous studies, the aleatoric uncertainty is much larger than the epistemic uncertainty. The ratio between these two will be discussed in the context of; where more data are needed for robust model results, where more features are needed for to reduce overlapping signatures, and how the uncertainty measures can be used to identify erroneous retrievals.
A new sea ice drift product for optical remote sensing imagery
Monica Wilhelmus, Daniel Watkins, Minki Kim, Ellen Buckley
Corresponding author: Monica Wilhelmus
Corresponding author e-mail: mmwilhelmus@brown.edu
Satellite records of sea ice extent have consistently shown a decrease in summer sea ice cover linked to warming temperatures. Nevertheless, our ability to understand and accurately model sea ice dynamics has not been fully developed. The focus in developing next-generation sea ice models and observing systems is shifting from a continuum-based approach towards resolving the mechanical and thermodynamical atmosphere–ice–ocean interactions at the scales of individual ice plates (known as floes). I present new advances for the automatic identification and tracking of ice floes in optical satellite imagery that provides a unique record of ice floe shapes and sizes, trajectories, drift velocities and rotational characteristics. These new observations allow us to examine the dynamic structure of the sea ice field in marginal ice zones at unprecedented spatial resolution and temporal coverage. The observed close link between free-drifting ice plates and the eddy field underneath provides a new avenue for characterizing ocean eddy dynamics within the mesoscale-submesoscale range in regions where traditional remote sensing observations have high uncertainty. Finally, our ability to retrieve daily observations from a long-term satellite record of high-resolution sea ice images provides a road map to understand the dynamics of critical momentum and heat transfer processes in the Arctic Ocean.
ICESat-2 mission status and sea ice product updates
Nathan Kurtz, Marco Bagnardi, Jeremy Harbeck, Thomas Neumann, Rachel Tilling, Jesse Wimert
Corresponding author: Nathan Kurtz
Corresponding author e-mail: nathan.t.kurtz@nasa.gov
NASA’s Ice, Cloud, and Land Elevation Satellite-2 was launched in September 2018 and has been providing near-continuous laser altimetry measurements of Arctic and Antarctic sea ice for more than 4 years. ICESat-2’s laser is split into six beams with a footprint size of ~11 m on the ground; to date ICESat-2 has emitted over 1.3 trillion laser pulses, providing extremely high-resolution measurements and extensive mapping of polar sea ice surface height characteristics. In 2022, ICESat-2 ended its prime mission phase and entered the extended mission portion of the mission. We will give an overview of the status of ICESat-2 into this new phase of the mission including laser lifetime estimates and energy changes over the course of the mission, ongoing challenges with inter-beam biases, and uncertainty estimates of freeboard retrievals to demonstrate that the mission is presently meeting the science requirements set forth for prior to launch. We will also discuss ongoing research to improve the standard sea ice surface height and freeboard products produced by the mission. These include the use of new fitting functions and photon aggregations to improve the sea ice height and freeboard retrievals as well as the introduction of new uncorrected height fields and their potential for retrievals of near-coastal sea ice freeboard. Lastly, we will discuss data and results from the ICESat-2 summer sea ice airborne validation campaign conducted in July 2022 which provide insight to the quality of ICESat-2 freeboard retrievals during melt conditions and the potential capability to provide new parameters containing information on melt ponds from the data.
Mesoscale aggregation of sea ice floes in the marginal ice zone
Mukund Gupta, Andrew Thompson, Patrice Klein
Corresponding author: Mukund Gupta
Corresponding author e-mail: guptam@caltech.edu
Marginal ice zones are typically characterized by the presence of loose sea ice floes, which interact both mechanically and thermodynamically with surrounding turbulent ocean currents. The dynamics of these moving floes remain poorly constrained, due to the difficulty of resolving sub-mesoscale processes and modelling the discrete behavior of sea ice in traditional climate models. In particular, the fine-scale ice/ocean exchanges of momentum, heat and salinity associated with the life cycle of these floes can have important effects on upper-ocean energetics, under-ice tracer mixing and the melt rate of the pack. Here, we use large eddy simulations coupled to idealized disk-shaped sea ice floes to understand interactions between loose pieces of ice and underlying ocean mesoscale currents during summer conditions. In experiments varying the sea ice concentration and floe size distribution, we find that floes aggregate into mesoscale clusters around coherent eddies, and subsequently fuel the mesoscale field by maintaining melt-induced buoyancy gradients at the surface. The baroclinic conversion of potential to kinetic energy is counteracted by damping from ice/ocean friction, which plays a significant role in the upper ocean’s eddy kinetic energy budget, even when the sea ice concentration is as low as 40%. The clustering of sea ice floes by the strain field also reduces the floe size dependency in melt rate, by shielding smaller floes from warm ocean filaments. These results highlight the need to parameterize floe-scale sea ice dynamics, including the coupling to ocean meso- and submesoscale turbulence, in global climate models.
A novel probe to sample trace-metal concentrations in sea ice at high vertical resolution
Matthew Corkill, Takenobu Toyota, Daiki Nomura, Klaus M. Meiners, Pat Wongpan, Trevor Corkill, Delphine Lannuzel
Corresponding author: Matthew Corkill
Corresponding author e-mail: matthew.corkill@utas.edu.au
Inside sea ice impermeable layers trap material as well as highly porous layers full of ice algae. These features can be smaller than a few centimetres but are important for understanding biogeochemical cycles in sea ice. Traditionally, sea-ice samples are collected from ice cores cut into sections to obtain a vertical profile. However, drawbacks to this method include difficulty cutting sections smaller than a few centimetres thick and contamination of the samples during high-resolution sectioning. Brines may also drain out and be lost, meaning that important environments in sea ice may be overlooked or misrepresented. To address this, we developed a sea-ice melt probe that bores into sea ice and collects high-resolution samples without extracting and cutting ice cores. The melt-probe’s capability was tested during February–March 2023 at Saroma-ko Lagoon, Japan. Experiments consisted of testing the effect of the melt-probe set temperature, its high-resolution capability, and ability to be deployed on snow-covered sea ice. Complimentary laboratory-based experiments included testing how well the melt-probe delineates layers by introducing a fluorescent layer to artificial sea ice. This proof-of-concept study hopes to provide an alternative method of sampling sea ice with the ability to support new research into the fine-scale structure of sea ice, with applications spanning challenging fields of research such as trace metal, microplastics and gas.
The three-dimensional life cycle of sea ice floes in the Weddell Sea
Mukund Gupta, Heather Reagan, YoungHyun Koo, Sean Chua, Xueke Li, Petra Heil
Corresponding author: Mukund Gupta
Corresponding author e-mail: guptam@caltech.edu
Sea ice is a granular material composed of individual ice floes whose geometry evolves in response to conditions in the surrounding ocean and atmosphere. At synoptic scales, the influence of these floe dynamics remains uncertain, notably in the perennial sea ice pack, where floe properties are highly heterogeneous. This study leverages satellite altimetry (ICESat-2) and imagery (Sentinel-2) to characterize the coupling between the life cycle of sea ice floes and the large-scale dynamics of the Weddell Sea. At the basin level, the age and thickness of ice generally increases along the clockwise path of the gyre. The seasonality in ice thickness distribution inferred from altimetry is mirrored between the southern and western regions of the basin, revealing significant thickness redistribution by the gyral circulation. On the other hand, the seasonality of the floe chord distribution is spatially uniform, and maps onto the asymmetric melt/freeze cycle of the pack. At the floe scale, along-track freeboard measurements from ICESat-2 show that floes have a dome-like thickness distribution, with smaller floes (100–500 m) displaying a rounder vertical profile than larger floes (1–50 km). These dome-shaped profiles explain a positive correlation between mean floe size and freeboard thickness, and highlight distinct erosive processes occurring over the season. Optical images reveal that the winter-to-summer transition is characterized by a drastic increase in the isotropy of the pack, notably in floe size, shape, thickness and orientation, with implications for its basin-wide rheological properties. These inferences emphasize the importance of monitoring the three-dimensional properties of floes, as the sea ice pack continues to evolve due to global climate change.
Nils Hutter, Arttu Jutila, Stefan Hendricks, Robert Ricker, Luisa von Albedyl, Gerit Birnbaum, Christian Haas
Corresponding author: Nils Hutter
Corresponding author e-mail: nhutter@uw.edu
During the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition an airborne laser scannerwas used to map the sea-ice surface at sub-meter resolution. We conducted 64 flights over the Arctic sea ice between September 2019 and September 2020 to measure sea-ice surface elevation during the full annual cycle at high spatial resolution and coverage. The flights ranged from repeated, local-scale 5×5 km2 floe grid surveys to regional-scale transects more than 100 km long. In this presentation, we give an overview of the first version of the released data with illustrative examples. The data products include point cloud segments, gridded segments, and gridded merged maps of elevation and freeboard with a spatial resolution of 0.5 m. The latter product is corrected for atmospheric backscatter, sea-ice drift, and offset in elevation due to degraded INS/GPS solutions >85° N. For floe grid surveys, all data are combined to merged two-dimensional elevation maps. We present a comprehensive validation of the data quality achieved with the corrections and highlight both potentials and resulting limits of the data for different use cases. The presented data offer a unique possibility to study the temporal evolution, spatial distribution, and variability of the snow and sea-ice surface and their properties in addition to validating satellite products, of which we will highlight first applications.
Modeling the sea ice and snow heat conduction through the lens of the MOSAiC dataset
Lorenzo Zampieri, Nils Hutter, Marika Holland
Corresponding author: Lorenzo Zampieri
Corresponding author e-mail: zampieri@ucar.edu
The parameterization of the heat conduction through sea ice and snow remains simple in state-of-the-art models. Specifically, it relies on prescribed conductivity parameters constant in time and space, therefore neglecting the substantial heterogeneity of these mediums down to the unresolved subgrid scale. This assumption clashes with robust observational evidence, which indicates that snow and ice conductivities can vary greatly depending on the environmental conditions and the history of the sea ice. The winter observations collected during the MOSAiC expedition are unique tools for advancing the quantitative understanding of heat conduction in sea ice and improving the realism of the thermodynamic parameterizations in models. Our investigation utilizes gridded helicopter-borne thermal infrared imaging, laser scanner elevation observations, and meteorological measurements to assess the model bias and diagnose the importance of unresolved processes and topographic heterogeneity on heat conduction. We evidence different heat conduction regimes depending on the ice thickness, type (i.e. ridged or level ice), and snow patchiness. In the light of these results, we discuss strategies for an effective parametrization of these unresolved processes in sea ice models, and their harmonization with the preexisting model infrastructure. Furthermore, we comment on the potential of emerging data-driven analysis techniques and machine learning in facilitating the formulation of parameterization at different stages of the development process.
Yoshihiro Nakayama, Pat Wongpan, Jamin S. Greenbaum, Kaihe Yamazaki, Tomohide Noguchi, Daisuke Simizu, Haruhiko Kashiwase, Donald D. Blankenship, Takeshi Tamura, Shigeru Aoki
Corresponding author: Pat Wongpan
Corresponding author e-mail: pat.wongpan@utas.edu.au
Rapid climate change affects the physical, chemical and biological aspects of ice-covered oceans. The recent discovery of warm ocean water near the Totten Ice Shelf (TIS) has drawn attention to the Sabrina Coast in East Antarctica. To understand the pathways and mechanisms of warm water inflow, ocean observations for entire continental shelf regions are necessary. This has historically not been possible due to intense sea ice and icebergs in the region.We report the result of 6-day helicopter-based observations using AXCTD (Airborne eXpendable Conductivity, Temperature, and Depth) and AXBT (Airborne Bathy-Thermograph) including the deployment through landfast sea ice (fast ice) cracks (~15–540 m). The observations conducted during the 61st Japanese Antarctic Research Expedition (JARE61) revealed warm ocean water (0.5–1°C) occupying a large previously unsampled area of the Sabrina Coast (116.5–120° E) below 550–600 m. Along the TIS front, we observe modified Circumpolar Deep Water (mCDW) well above freezing (~–0.7°C), consistent with previous work. We identify glacial meltwater outflow from the TIS cavity west of 116° E. No signs of mCDW intrusions towards the Moscow University Ice Shelf cavity were observed; however, those observations were limited to only two shallow (~330 m) profiles. During our flight observations, we attempted to conduct four east-west hydrographic sections and were able to complete all these sections by finding small sea ice cracks although most of the area was almost 100% covered by sea ice. At the time when helicopter-based measurements were conducted, existing observations were limited to the area close to the coast and inside the Dalton Polynya; the helicopter-based measurements discussed here allow us to obtain large-scale hydrographic features of the continental shelf region, despite intense sea ice and iceberg conditions at the time. We also highlight the advantages of helicopter-based observations for accessibility, speed, maneuverability and cost-efficiency. The combination of ship- and helicopter-based observations using the JARE61 approach will increase the potential of future polar oceanographic observations.
Nils Hutter, Cecilia Bitz, Luisa von Albedyl
Corresponding author: Nils Hutter
Corresponding author e-mail: nhutter@uw.edu
Arctic sea ice is a mosaic of ice floes whose distribution and thicknesses greatly impact the interaction of sea ice with the atmosphere and the ocean. However, we are still lacking knowledge of the physics to describe the complex interplay of ice floes that are a key characteristic of sea ice. In our contribution, we outline a framework to characterize sea-ice deformation at the floe-scale from observational data by studying the mechanical interaction of multiple identifiable floes. We use Sentinel SAR imagery and ICESat-2 data acquired during the MOSAiC expedition to map ice floes and their thickness in the larger area around Polarstern. This combination of data products allows us to describe the floe-size distribution of floe diameters from hundreds of kilometers down to tens of meters. With the repeated coverage of SAR imagery, ice motion is tracked and deformation estimates are derived. By combining both floe-size estimates and deformation rates we provide insights into how the floe composition changes in regions that were exposed to deformation. Finally, we present a parameterization of this relationship between floe sizes and mechanical redistribution for large-scale continuum sea-ice models.
Snow and ice thickness derived from sea ice mass balance buoys in the transpolar drift system
Andreas Preußer, Thomas Krumpen, Marcel Nicolaus
Corresponding author: Andreas Preußer
Corresponding author e-mail: andreas.preusser@awi.de
Sea ice controls and is influenced by the exchange of energy, moisture and momentum between the underlying ocean and the lower atmospheric boundary layer. The physical properties of sea ice play a critical role in modulating these interactions. Of particular importance is the temporal evolution of the thickness of the ice and snow layers, both of which are a result of seasonally and spatially highly variable growth and decay processes. To investigate whether large-scale changes in the Arctic sea ice cover such as a general thinning and increased drift speeds are also imprinted on long term data sets from autonomous drifting platforms, we present an analysis of sea ice properties derived from sea ice mass balance buoys deployed in the transpolar drift system between 2012 and 2023, thus including the period of the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) experiment in 2019/20. In particular, we aim to assess whether the observed variations in sea ice mass balance by ice growth and melt in recent years are significantly different from previous years, or whether they remain consistent on an interannual time scale. To achieve this, a uniform processing scheme is developed and applied to large set of buoys with the aim to minimize methodological ambiguities in the derivation of snow–ice–ocean interfaces. We also present comparisons with external factors (both thermodynamic and dynamical) derived from satellite data and atmospheric reanalysis that influence the local sea ice mass balance observed by the buoys during their drift towards Fram Strait and adjacent seas.
Andreas Preußer, Günther Heinemann, Lukas Schefczyk, Sascha Willmes
Corresponding author: Andreas Preußer
Corresponding author e-mail: andreas.preusser@awi.de
Knowledge of winter sea ice production in Arctic polynyas is an important prerequisite for estimating the dense water formation that drives vertical mixing in the upper ocean. Satellite techniques using relatively high-resolution thermal infrared data from MODIS in combination with atmospheric reanalysis data have proved to be a powerful tool for monitoring large and regularly forming polynyas and for resolving narrow thin ice areas (i.e. leads) along shelf breaks and across the Arctic Ocean. However, the selection of atmospheric data sets has a strong influence on the derived polynya characteristics, as it affects the calculation of heat loss to the atmosphere, which is determined by the local thin-ice thickness. To overcome this methodological ambiguity, we present a temperature adjustment algorithm that provides corrections to the 2&thinspl;m air temperature through MODIS ice surface temperatures. It thus reduces the differences in calculated surface heat fluxes that can result from the use of varying atmospheric input data sets. The adjustment algorithm itself is based on atmospheric model simulations. We focus on the Laptev Sea region for detailed case studies of the developed algorithm and present time series of polynya characteristics in the winter season of 2019/20, which in general was characterized by a particularly strong polar vortex and inherent effects on sea ice dynamics. It becomes apparent that the application of the empirically derived correction significantly reduces the difference between the different atmospheric products used from 49% to 23%. We apply additional filtering strategies that aim to increase the ability to include leads in the quasi-daily and persistence-filtered thin-ice thickness composites.
Bonnie Light, Madison Smith, Erin Firth, Laura Reed, Kaila Frazer
Corresponding author: Bonnie Light
Corresponding author e-mail: bonlight@uw.edu
While in situ observation of natural sea ice is indispensable, the ability to isolate certain small-scale sea ice processes in the laboratory for targeted study holds significant potential. Nature rarely submits to prescribed forcing, seldom permits sample amendment, and typically does not supply a stable control case. Such conditions, however, may be desirable for the investigation of specific small-scale processes. Laboratory grown sea ice offers unique opportunities for these studies. The APL Laboratory for Cryospheric Science (ALECS) has been developing techniques to overcome these obstacles and build an ‘ice farm’. Here, individual ice-core sized (10 cm diameter) samples are grown, in replicate, with sample amendment and variable forcing conditions. To circumvent the effects of horizontal inhomogeneity imposed by finite size growing canisters and heat conduction via container walls, we use clear polycarbonate cylindrical canisters submersed in a temperature-controlled bath inside a walk-in freezer. Ice growth rate is regulated by variable air temperature (between –2 and –20°C) and bath temperature (between 0 and –3°C). Currently, replication is achieved by simultaneous growth of four cores under identical forcing. Results indicate production of columnar ice with distributed brine and gas inclusions commensurate with the range of distributions observed in nature. Studies are under way to investigate the entrainment of pollutants at the ice/ocean interface using this laboratory technique.
Rosemary Willatt, Vishnu Nandan, Julienne Stroeve, Robbie Mallett, Thomas Newman, Stefan Hendricks, Robert Ricker, James Mead, Polona Itkin, Rasmus Tonboe, David Wagner, Gunnar Spreen, Glen Liston, Martin Schneebeli, Daniela Krampe, Michel Tsamados, Oguz Demir
Corresponding author: Rosemary Willatt
Corresponding author e-mail: r.willatt@ucl.ac.uk
Sea ice thickness is a WMO-recognized essential climate variable, necessitating retrievals over the Arctic Ocean on spatiotemporal scales only feasible via satellite observations. Snow cover plays key roles in the growth, melt and evolution of sea ice, e.g. via insulation, albedo and drag properties. Snow is also a major source of uncertainty in satellite retrievals of sea ice thickness from satellite altimetry. Effective remote sensing of snow can therefore provide a step-change in the accuracy of sea ice thickness observations. Spatially and temporally variable snow properties such as density, layering and microstructure make development of snow depth products a challenge, and limited availability of in situ datasets drive reliance upon other remotely sensed datasets such as from airborne instruments. Investigations into how electromagnetic (EM) radiation interacts with sea ice and its snow cover are therefore central to progress. We present novel dual-polarization techniques for snow depth retrieval using data from deployment of the ‘KuKa’ surface-based Ku- and Ka-band radar during MOSAiC. Our snow depth estimations are accurate to 1 cm and with r2 up to 0.78 when compared with independent MagnaProbe snow depth measurements. We discuss the potential for application of the technique on airborne and satellite scales, using data from existing satellite instruments to examine feasibility of upscaling. We also find that the waveform shape techniques can provide r2 up to 0.73, indicating that satellite radar altimeters aboard missions such as CryoSat-2, Sentinels 3 and 6, and CRISTAL may provide information on snow depth over Arctic sea ice even using a single-frequency approach. Lastly we discuss dual-frequency snow depth retrievals using KuKa data and compare to results from satellite instruments. We also outline insights from other types of satellite instruments to contextualize our results.
What’s next for the NOAA /NSIDC passive microwave-based sea ice concentration climate data record
Florence Fetterer, Ann Windnagel, Walt Meier, J. Scott Stewart, Trey Stafford
Corresponding author: Florence Fetterer
Corresponding author e-mail: fetterer@colorado.edu
Since 2011, a climate data record of daily 25 km sea ice concentration (SIC) fields created from the DMSP SSM/I and SSMIS suite of instruments has been available from NOAA@NSIDC. In its present Version 4 form, spatial and temporal gaps have been filled, melt onset day has been added, and other improvements have been made. A near-real-time companion product was released in 2017. We are now developing a prototype AMSR2 SIC product that uses the original CDR product method of combining NASA Team and NASA Bootstrap algorithm output to arrive at each day’s SIC field. This higher resolution 12.5 km AMSR2 product will be the keystone of a new version of the current CDR. It will begin with SMMR in 1978, be on a 12.5 km grid throughout the series, and in its final iteration will use AMSR series data beginning with AMSR-E in 2002. We are now engaged in adjusting for differences in spatial resolution to create consistent concentration, extent, and area estimates across the series, using the AMSR2 product as the standard. In ‘A new structure for the sea ice essential climate variables of the global climate observing system’ (2022), Lavergne et al. point out some research needs that the coming NOAA/NSIDC SIC CDR addresses, namely improving resolution (beginning with AMSR-E) and securing long term sensor inter-consistency. Bias and uncertainty in summer melt season SICs will be addressed in part by making sea ice area in the older data consistent with that derived using AMSR2. We are validating the AMSR2 SIC estimates via comparisons with VIIRS concentration estimates and with operational ice analyses.
Statistically classifying the pan-Antarctic marginal ice zone with CICE6
Noah Day, Luke Bennetts, Siobhan O’Farrell, Alberto Alberello
Corresponding author: Noah Day
Corresponding author e-mail: noah.day@adelaide.edu.au
The Antarctic marginal ice xone (MIZ) is generally described as the area of sea ice affected by ocean surface waves and acts as an interface between the open Southern Ocean and the consolidated inner pack. Standalone CICE6 (with atmospheric, oceanic and wave forcing) was used to create a dataset consisting of variables describing the ice cover (sea ice concentration, age, thickness, etc.) as well as the dynamic and thermodynamic processes. An unsupervised statistical method classified over a decade of data into distinct the sea ice regions (including the MIZ). Spatial and temporal variance of the respective dominant physical processes was quantified, and the impact of wave attenuation on the MIZ extent was tested and validated with recent altimetry observations. Floe size was found to enhance our MIZ classification to include high concentration pancake fields, which form over winter in the presence of waves. These results support the inclusion of floe size within sea ice modelling, and the importance of multivariate approaches to describe sea ice.
Sven Bollmann, Dominik Hanke, Falk Pätzold, Lutz Bretschneider, Konrad Bärfuss, Jesper Sandgaard, Ulf Bestmann, Astrid Lampert
Corresponding author: Sven Bollmann
Corresponding author e-mail: s.bollmann@tu-braunschweig.de
During the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition in 2019/20 the helicopter-borne measurement system HELiPOD was deployed in the Central Arctic. The system was equipped with around 60 sensors for studying the atmospheric boundary layer, radiation and surface properties. As surface roughness and open water fractions in sea ice are key properties related to the exchange processes between surface and the atmosphere, a laser scanner was used to provide a three-dimensional point cloud representation of the surrounding environment. The acquired point cloud was transformed into the body-fixed coordinate system of the HELiPOD. After fusion with highly resolved position and attitude data from an integrated GNSS/INS navigation system, a digital elevation model of the overflown sea ice area could be calculated. Images from an onboard fish eye camera were used to validate the elevation model. The surface roughness can eventually be derived from the elevation data. Based on a previous examination of the statistical properties of the sea ice surface, several methods are currently being applied to the elevation data and their suitability for the data set is being discussed.
Inge Deschepper, Tim Papakyriakou, Diane Lavoie, Paul Myers, Fréderic Maps
Corresponding author: Inge Deschepper
Corresponding author e-mail: inge.deschepper.1@ulaval.ca
The use of modelling tools to simulate the Arctic environment, which is very difficult to observe year-round, is required to fill spatial and temporal gaps critical to understand physical, chemical and biological variables. Models can be used to provide input into areas of interest for future studies by understanding the physical drivers of the present or identifying interesting features that can be modelled and would otherwise not be observed without costly large-scale observational efforts. Still, few biogeochemical models include processes specific to the flora and fauna associated with the sea ice (sympagic ecosystem) in the Arctic, which is covered in sea ice for a large portion of the year. In recent observational studies of the Arctic, sympagic communities have been shown to contribute a significant fraction of overall biomass and production in various high-latitude ecosystems. We coupled an improved version of the Sibert et al. 2011 biogeochemical model BioGeoChemical Ice Incorporated Model (BiGCIIM), which includes both pelagic and sympagic components of the ecosystem, to the general ocean circulation model Nucleus for European Modeling of the Ocean version 3.6 (NEMO v3.6), and sea-ice model Louvain de la Neuvre version 2 (LIM2). We compared the simulated chlorophyll-a concentrations to observed satellite-derived data to evaluate the model’s performance in terms of primary production phenology (timing), amplitude and spatial distribution within the complex system of Hudson Bay in Canada. Then, using empirical orthogonal functions, we investigate the modes of variability of the chlorophyll-a concentration and assess which physical forcings could drive primary production dynamics in this region that is currently undergoing an unprecedented rate of change.
Four decades of sea ice observed from space: sea ice type and hemispheric distribution
Signe Aaboe
Corresponding author: Signe Aaboe
Corresponding author e-mail: signe.aaboe@met.no
At any time of year, the global sea ice covers 17–8 million km2. Of this global cover, the Antarctic sea ice contributes more than half (at maximum conditions). With satellite monitoring, we get a full overview of the sea ice in both hemispheres, on a daily basis and continuously back to the 1970s. Observations have shown decreasing and thinning sea ice in the Arctic, and highly variable and unpredictable sea ice in the Antarctic with large regional differences. The sea-ice type can roughly be divided into two age categories: seasonal ice that formed since last summer, and multiyear ice that has survived the summer melt. Due to brine rejection over time, multiyear ice is characterized by containing less salt but more air bubbles than seasonal ice, which is making older ice more rigid and solid. In addition to changing the physical properties, these differences lead to distinct emissivity and backscatter signatures that allow classification by satellite remote sensing. More than four decades of satellite monitoring of the Arctic shows that the sea ice is becoming rapidly younger, going towards a more seasonal ice cover. The situation of the Antarctic sea ice is more complex with no clear long-term trends of the multiyear ice extent but maybe rather a trend towards larger variability of the sea ice and the presence of multiyear ice. In this contribution, the long-term picture of the sea ice in both hemispheres will be presented with a focus on the sea-ice type. The results are based on products partly from the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) which has provided operational near-real-time global sea-ice products since 2005, and partly the climate data records developed through the Copernicus Climate Change Service (C3S).
Retreating sea ice in the Barents Sea – the Arctic hotspot region
Signe Aaboe, Ketil Isaksen
Corresponding author: Signe Aaboe
Corresponding author e-mail: signe.aaboe@met.no
The Barents Sea is known for hosting some of the largest changes in the climate system seen in recent decades. It stands out as a significant hotspot region with the most dramatic sea-ice loss and with warming rates of up to eight times the global average. The reduced ice cover with close to ice-free conditions during summer is seen to have a crucial role in destabilizing the upper ocean stratification: The loss of sea ice removes the insulator between the ocean and atmosphere, reduces the freshwater input, and the protection of the Arctic cold halocline is lost. With a weakened upper halocline, we expect more heat flux from the Atlantic Water towards the surface which will prevent or postpone sea ice from forming in autumn. Recently, results based on surface air temperature data show that the annual warming in the Barents Sea is as high as 2.7°C per decade, with a maximum in autumn of up to 4.0°C per decade – a warming trend much higher than hitherto known in this region, or the Arctic in general. The warming pattern is largely consistent with reductions in sea-ice cover and confirms the general spatial and temporal patterns represented by reanalyses over the Barents Area. More recent trends also find that the surface air temperature no longer accelerates in the western part of the Barents area (since this region has become more or less ice-free), but that the warming now intensifies in the east (where the sea ice is still dense, but melting at a high pace). Although it remains unclear whether and to what degree the air temperature increase is driving the sea ice decrease, or vice-versa, our study highlights that the recent warming was punctuated by increasing intensity of abrupt warming events, with peaks in 2006, 2012 and 2016. There will probably be a new peak during 2023, but it is still uncertain whether it will be higher than the previous peaks.
An ensemble-based data assimilation system for the Southern Ocean
Qinghua Yang, Hao Luo, Dake Chen, Matthew Mazloff
Corresponding author: Qinghua Yang
Corresponding author e-mail: yangqh25@mail.sysu.edu.cn
To improve Antarctic sea-ice simulations and estimations, an ensemble-based data assimilation system for the Southern Ocean (DASSO) was developed based on a regional sea-ice–ocean coupled implementation of MITgcm and the parallel data assimilation framework (PDAF), which assimilates sea-ice thickness (SIT) together with sea-ice concentration (SIC) derived from satellites. The result of experiments conducted from 15 April to 14 October 2016 shows that assimilating SIC and SIT can suppress the overestimation of sea ice in the model-free run. However, a covariance inflation procedure is required in data assimilation to improve the simulation of Antarctic sea ice, partially due to the underestimation of atmospheric uncertainties. Thus, a multivariate balanced atmospheric ensemble forcing is further developed for DASSO based on the high-resolution ERA5 reanalysis, which considers the relationship between different variables and adjacent times. The model-free run of 2016 shows that this newly generated atmospheric ensemble forcing can suppress model errors of SIC and produce better estimates of simulation uncertainties. Further analysis reveals the improvement stems from a better representation of atmosphere–ocean and sea-ice–ocean thermodynamic processes in the model. This makes it possible to improve the background error estimate of DASSO. Based on this improvement, the observation error estimate and the localization scheme are further optimized for DASSO. The preliminary result of the long-term data assimilation experiments shows that compared with our initial configuration, optimized DASSO can better reproduce the condition of Antarctic sea ice and decrease reliance on the covariance inflation procedure significantly. Along with more Antarctic sea ice observations due to be released soon, the prospects look bright for reconstructing long-term Antarctic sea ice conditions, especially SIT and volume, through sea-ice data assimilation.
Monitoring of landfast sea ice at Storfjorden, Svalbard
Sebastian Gerland, Dmitry Divine
Corresponding author: Sebastian Gerland
Corresponding author e-mail: gerland@npolar.no
Monitoring of landfast Arctic sea ice, with focus especially on in situ measurements of ice thickness, snow thickness and freeboard, has been performed at Inglefieldbukta in Storfjorden, Svalbard, since 2006. Originally started as an international scientific study within the International Polar Year 2007/08, the monitoring is now part of the Norwegian Polar Institute’s Svalbard sea ice monitoring program. Inglefieldbukta is a bay at the western coast of Storfjorden, with landfast sea ice forming and present in winter and spring months. The observations are complementing monitoring in Kongsfjorden at the west coast of Svalbard and at the island of Hopen in the Barents Sea, with sea ice conditions that are often different from the two other locations. In the first years of the monitoring, measurements were aided by the wintering sailboat Vagabond and its crew, while later on two light huts have been serving and serve as infrastructure of this site, which is reached via a 100 km long snow machine trip over land and fast ice, or by helicopter or ship. Beyond full season monitoring in the first years, the monitoring consists of one to three visits by scientists between March and May every year for measuring thicknesses and additional physical sea ice and snow properties. The monitoring shows that the sea ice seasons are in general longer at Storfjorden than at the west coast of Svalbard, that sea ice grows thicker, and that snow amounts are larger. Substantial snow deposition has been observed leading to negative freeboard and consecutive snow ice formation and/or superimposed ice formation, adding sea ice volume to the sea ice growth at the bottom of the ice – processes also known from the pack ice area north of Svalbard, and from Antarctic sea ice. Sea ice thickness was observed in spring often to be within a range of around 80 cm, with snow thicknesses around 40 cm, together resulting often in negative freeboard of several cm. Clear long-term trends are not visible, but data show interannual variability, with individual years for example exceeding ice thicknesses above 1 m. We will give an overview on the monitoring results so far, and also discuss linkages of the monitoring to interdisciplinary studies, such as ecosystem research, and environmental management.
Clément Soriot, Catherine Prigent, Carlos Jimenez, Martin Vancoppenolle
Corresponding author: Clément Soriot
Corresponding author e-mail: clement.soriot@observatoiredeparis.psl.eu
Satellite remote sensing of the Arctic sea ice began in the late 1970s with sea ice concentration (SIC) retrieval: the passive microwave estimate of SIC is one of the longest satellite-derived time records (IPCC). Many other sea ice parameter retrievals using satellite microwave observations have been developed since, such as sea ice thickness (SIT), sea ice type/age, snow depth and sea ice surface roughness. In particular, SIT and sea ice volume (SIV) have triggered a lot of interest lately, with microwave altimeters as the primary instruments for estimating SIT, helped by L-band (1.4 GHz) radiometer observations for the thin ice thickness (below 50 cm). So far, very few studies have tried to estimate SIT from passive microwave radiometers only, from thin to thick ice. In particular, the methodology described in Soriot et al. (2022) has been specifically developed to exploit the multi-frequency availability of radiometer. It is based on a simple and yet efficient statistical approach that relies on a neural network trained to learn the mapping between the ICESat-2 SIT product of the Arctic polar year 2018/19, and the brightness temperature from the soil moisture active passive (SMAP) instrument (1.4 GHz) and from the advanced microwave scanning radiometer 2 (AMSR2) (6, 10, 18, and 36 GHz). The method has shown good performance (compared to campaign measurements or to microwave altimeter estimates), even when using only the two frequencies 18 and 36 GHz. Here, we will recap the methodology and extend the work from this article with the production of a SIT data record, applying the SIT retrieval with the 18 and 36 GHz channels on the special sensor microwave/imager (SSM/I) and the special sensor microwave imager sounder (SSMIS) measurements, since the early 90s. The associated SIV is then computed using the SIC from the ocean sea and ice satellite application facilities (OSI-SAF) for the same time period. Results have shown good performance in reproducing trends and interannual variability when compared to other independent estimation such as PIOMAS or submarine measurements. The methodology presented here paves the way for 30 years of SIT and SIV, the longest time series of these crucial sea ice geophysical parameters.
Dmitry Divine, Adam Steer, Sebastian Gerland, Anca Cristea, Elizabeth Jones, Agneta Fransson, Mats A. Granskog, Bonnie Raffel, Polona Itkin, Melissa Chierici
Corresponding author: Dmitry Divine
Corresponding author e-mail: dmitry.divine@npolar.no
The northern Barents Sea is experiencing rapid changes manifested in a number of observable variables with receding sea ice being one of the major indicators of the ongoing warming. Both the northern Barents Sea and adjacent Arctic Basin have been in the focus of the Norwegian national project Nansen Legacy – a novel and holistic Arctic research project providing integrated scientific knowledge on the rapidly changing marine climate and ecosystem required to facilitate a sustainable management of the area through the 21st century. Throughout a series of research cruises conducted in 2018–22 a dedicated interdisciplinary dataset on climate and ecosystem of the area representing entire seasonal cycle has been collected. This includes a large collection of data covering various aspects of the physics of sea ice for the range of spatial scales, from in situ acquired during on-ice station work to regional scales, based on helicopter-borne sea ice surveys and remote sensing. This dataset is presently being systematized and analyzed both for future dedicated publications on northern Barents Sea sea ice, as well as for aiding studies on regional ecosystem and biogeochemical cycles. We will present an overview of some of the first results summarized so far, and discuss interdisciplinary linkages of the Nansen Legacy sea ice physics work to studies such as ecosystem research and environmental management.
Sivuqaq sea ice changes: regional remote sensing and local St Lawrence Island Yupik perspectives
Kitrea Pacifica Takata-Glushkoff, Eddie Ungott, Travis Peken Kaningok Sr, Andy Mahoney, Shauna BurnSilver
Corresponding author: Kitrea Pacifica Takata-Glushkoff
Corresponding author e-mail: pltakataglushkoff@alaska.edu
As Alaska and Russian communities along the Bering and Chukchi seas experience changing sea ice environments, Indigenous community members and governing entities have made clear the need for more intentionally holistic engagement from the research community. Here we bring together the expertise of St Lawrence Island Yupik hunters, geophysicists and social scientists to better understand the interplay between a locally changing sea ice environment and cultural subsistence practices. We characterize these changes around St Lawrence Island using a regional lens of remote-sensing-derived spatial patterns, alongside local perspectives in near-daily ice observations and community interviews in Gambell, Alaska, USA (Sivuqaq). We first compare passive microwave based annual sea ice concentration cycles off the coast of Bering and Chukchi Sea villages and identify where communities further south have experienced changes we could expect to see into the future further north. Remote sensing of sea ice concentration near Gambell suggest that a new type of winter is currently emerging, characterized by greater variability in sea ice coverage. In partnership with the Native Village of Gambell Tribal Council, a local steering committee, and St Lawrence Island Yupik community research leads, we synthesize local Yupik experiences and traditional knowledge of ongoing sea ice change, implications and adaptation strategies in Gambell. In doing so we aim to develop a knowledge resource that Gambell hunters and sea ice users can use into the future, not only to capture the long term scale of change, but also to apply adaptation and safety strategies in the sea ice environment. Further, we highlight how specific indices of local shifting sea ice conditions lead to changes and adaptations in subsistence hunting and safety practices. Examples of such indices include timing of stable shorefast ice formation, arrival of pack ice from the Gulf of Anadyr, and persistence of wind direction, among others. Understanding these connections between the variable sea ice environment and local ice use will further hone our remote sensing analysis techniques to be more locally relevant for Gambell residents. Ultimately by connecting the insights offered by local ice observations, community-based Yupik expertise, and remote sensing regional patterns, we aim to illustrate a fuller picture of the rapid changes and their implications in this sea ice environment.
Jonathan W. Rheinlænder, Heather Regan, Einar Ólason, Pierre Rampal
Corresponding author: Jonathan W. Rheinlænder
Corresponding author e-mail: jonathan.rheinlaender@nersc.no
Since the 2000s, the Beaufort Sea has experienced a dramatic decline in sea ice coverage, thickness and age. Thicker multi-year ice (MYI) is being replaced by weaker and thinner first-year ice, which could make the Beaufort ice cover more vulnerable to breakup with implications for sea ice and ocean circulation in the Arctic. Using a new coupled ocean-sea-ice model we investigate how this regime shift in the Beaufort Sea has impacted the frequency of large sea-ice breakup events and wintertime lead formation over the period 2000–18. The model simulates an increasing trend in Beaufort Sea lead fraction during winter (4% per decade), with a transition around 2007. This is linked to decreasing ice thickness and mechanical weakening of the ice cover. More leads in winter promotes a significant growth of new, thin ice within the Beaufort Sea (increasing from 28% to 42% relative to the total growth). We find that years with more winter breakup also result in enhanced ice transport out of the Beaufort Sea. The export offsets the ice growth and results in negative regional volume anomalies compared to years without breakup and preconditions a thinner and weaker ice cover at the start of the melting season. In some years, this can increase the flushing of MYI through the Beaufort Sea and contribute to accelerated MYI loss in the Arctic. As the sea-ice cover thins lead formation is likely to play an increasingly important role for the sea-ice volume budget. The ability for ocean–sea-ice models to simulate leads also has potential implications for water mass properties and circulation in the Arctic Ocean. This highlights the urgent need to represent these processes in global-scale climate models to improve projections of the Arctic.
Using a rotatable mirror for ship-based microwave radiometer measurements of surface emissivity
Janna Rückert, Andreas Walbröl, Kerstin Ebell, Mario Mech, Gunnar Spreen
Corresponding author: Janna Rückert
Corresponding author e-mail: janna.rueckert@uni-bremen.de
Passive microwave measurements of Arctic sea ice have been conducted over the last 50 years during space-borne, airborne, ship-based and ground-based measurement campaigns. The different radiometric signatures of distinct surface types have led to satellite retrievals of, e.g., sea ice concentration. On the other hand, ground-based upward-facing radiometers measure radiation emitted from the atmosphere and can be used to retrieve atmospheric variables such as integrated water vapor, cloud liquid water path as well as temperature and humidity profiles in the Arctic. Here, we present first results from a ship-based microwave radiometer measurement setup with a mirror construction fixed to the stand of the radiometers to allow atmosphere and surface measurements. This addition of a mirror to microwave radiometers, usually used for sensing the atmosphere, enabled surface scans during the cruise ATWAICE/WALSEMA in the marginal sea ice zone on the research vessel Polarstern in summer 2022. During the campaign, two microwave radiometers were installed on Polarstern’s deck: MiRAC-P (Microwave Radiometer for Arctic Clouds – Passive) observing at high-frequencies (six channels around 183.31 GHz and two window channels centered at 243 and 340 GHz) and HATPRO (Humidity and Temperature Profiler), with seven channels each at K-band and V-band. Most of the time the radiometers pointed in zenith direction. However, the mirror construction allowed ‘looking’ at the surface at different incidence angles. These surface observations were done on a regular basis each hour. The data shows clear signatures in the measured brightness temperatures TB of different surface types in the marginal ice zone, including open ocean, sea ice and melt ponds and proves the principal concept of the setup. However, the strong spatial heterogeneity of the marginal ice zone complicates the analysis. A visual and an infrared camera which were complementing the microwave measurements provide help for the interpretation of the data. Additionally, on-ice measurements of the ice and surface conditions conducted during ice stations and modelled downwelling radiation computed by using the atmospheric measurements are available. When deriving emissivity values defined as e = (TB–TB(sky))/(Ts–TB(sky)), the additional quantities TB(sky), which is the downwelling brightness temperature, and the surface temperature Ts are required and can be estimated by these auxiliary observations.
Jutta Wollenburg, Clara Flintrop, Hauke Flores, Morten Iversen, Christian Hass, Christian Katlein, Mara Neudert, Scarlett Trimborn, Ilka Peeken
Corresponding author: Clara Flintrop
Corresponding author e-mail: clara.flintrop@mail.huji.ac.il
Recent studies have shown that a constant rain of cryogenic gypsum is released under melting sea-ice during spring in the Arctic Ocean. The released cryogenic crystals have a ballasting effect when they are incorporated into settling aggregates formed from under-ice or pelagic algae. Intriguingly, these crystals even ballasted Phaeocystis and enabled these neutrally buoyant organisms to sink to the deep seafloor. Using a chemical–thermodynamic model (FREZCHEM) to quantify aqueous electrolyte properties at sub-zero temperatures, we found support for the precipitation of minerals in high-salinity brines of Antarctic-sea ice. In ice-cores and in settling aggregates formed from under ice and pelagic algae in the Weddell Sea, Antarctica, showed presence of several cryogenic minerals including gypsum, ikaite and mirabilite. While all minerals are frequently found in the aggregates, they were more difficult to detect in the ice cores. All cryogenic minerals contain large quantities of water and the detection and isolation of specific cryogenic minerals is strongly dependent on the sample treatment. Cryogenic gypsum dissolves rapidly with increasing temperatures in undersaturated solutions, ikaite is semi-stable and mirabilite unstable at atmospheric conditions. Thus, sampling strategies on larger volume samples result in the selective preservation of one or the other cryogenic mineral, and only in small samples, rapidly filtered and investigated wet and dry, all minerals can be observed. The absence of cryogenic ballasting minerals in published studies on algae aggregates, and trap samples from under-ice locations may simply be due to the lack of preservation, whereas, such minerals may have nonetheless aided in ballasting organic matter to the deep sea floor and thus play an important role in the biogeochemical cycles of the sea ice covered oceans.
Fracturing ice floes by percussion in a granular model
Dang Toai Phan, Stéphane Labbé
Corresponding author: Stéphane Labbé
Corresponding author e-mail: stephane.labbe@sorbonne-universite.fr
Drift ice, a thin layer of ice that covers the polar seas, is a complex geophysical object that constantly fractures under the effect of winds and ocean currents. In winter and in the central Arctic, it is an almost continuous and damageable solid while in the melting season and in particular in the marginal seas of the Arctic, it takes the form of an aggregate of ice panes (called floes) whose mechanical behavior is dominated by collisions and friction between panes. Capturing the mechanical transition (spatial and temporal) between these two states in continuous drift ice models used for operational and climate study purposes is essential for the adequate representation of rapid and long-term variations in its extent and thickness. This work will include a part of modeling and mathematical analysis of the notion of percussion in order to initialize fractures in ice floes. This direction is part of an international research project on sea ice modeling called SASIP (Scale-Aware Sea Ice Project) In 2015, a new granular model that takes into account the collision of floes and their interactions with the ocean and atmosphere was proposed by M. Rabatel, S. Labbé and J. Weiss. In this model, ice floes are considered as undeformable rigid bodies. Five years later, D. Balasoiu proposed an efficient fracture model in which a floe is assimilated to a hyperelastic, homogeneous and isotropic material. Based on the variational problem proposed by Francfort and Marigo, this model describes the evolution of the fracture in the form of a competition between the elastic and surface energy of the fracture. The path that the fracture takes is characterized only by a condition at the Dirichlet boundary. Balasoiu also proved that the mechanical behavior of a sheet of ice is similar to a system of masses linked by different types of springs. This modeling therefore makes it possible to deduce more information about the Dirichlet’s border during the collision between two floes. This project is supported by Schmidt Futures – a philanthropic initiative that seeks to improve societal outcomes through the development of emerging science and technologies.
LoRa on Ice: live sea ice monitoring with open-source technology
Jan Rohde, Maximilian Betz, Daniel Helms, Mara Neudert, Stefanie Arndt, Anna Förster, Christian Haas
Corresponding author: Jan Rohde
Corresponding author e-mail: jan.rohde@awi.de
To understand processes in sea ice, the atmosphere, or in the ocean, many different parameters need to be measured on different spatial and temporal scales. Data collection and sensor behavior monitoring of single sensor platforms are usually carried out with satellite communication links. When deploying many (100+) sensors over a smaller area (radius <30 km), research stations and ships can serve as a central hub where the data are centrally collected, eliminating the need for satellite links for each sensor. To offer a network that allows easy integration of sensors, we successfully implemented a long range wide area network (LoRaWAN) at the Neumayer III station in Antarctica, providing near-real-time access to sea ice parameters around the station. The network currently includes two LoRa gateways receiving data from multiple sensors and a software stack enabling the data flow to Bremerhaven, including database synchronization and data visualization. As a first application, we built and deployed an energy-efficient autonomous data acquisition unit that collects data from an EM31 conductivity meter and transmits the results via the network. Additionally, we deployed test sensors around the station. The network and the sensors only use low-cost hardware and open-source software from the field of the Internet of Things (IoT). Here we summarize the results from the first implementation of the sensor network and give an outlook on the potential of this technology for the sea ice research. In the future the network will be used to easily integrate new sensors to measure various environmental parameters without the need for a satellite communication for every single sensor and still be able to monitor the data worldwide, if one central satellite link is available. Besides lower costs and easy data handling, the near real-time access and visualization allows a fast response to system failures and increases the sensor development speed. We are aiming towards a scalable system that can either be installed permanently at a research station, or set up temporarily at newly established measurement sites. We are excited to share the hardware and software with potential collaborators to improve the way we study the polar regions.
Arctic thin ice detection using AMSR2 and FY-3C MWRI radiometer data
Marko Mäkynen, Lijian Shi, Xi Zhang
Corresponding author: Marko Mäkynen
Corresponding author e-mail: marko.makynen@fmi.fi
In the Arctic Ocean thin sea ice occurs in winter within polynyas and leads in pack ice, at the ice edge, and during sea ice freeze-up season over large areas in the marginal ice zone. Recently, a thin ice (thickness <0.2 m) detection algorithm for the AMSR2 radiometer data was developed using MODIS ice thickness swath charts over the Barents and Kara Seas. Successful detection of thin ice over the whole Arctic Ocean was also demonstrated. The thin ice detection is based on the classification of 36 GHz polarization ratio and H-polarization 89–36 GHz gradient ratio (GR) signatures with linear discrimination analysis, and thick ice restoration with GR3610H. Thin ice detection is conducted only when sea ice concentration (SIC) >70% and air temperature ≤ –5°C to decrease misclassification of thick ice as thin ice. Thin ice detection is conducted with the AMSR2 L1R brightness temperature (Tb) data, and the results are combined to a daily thin ice chart. For the Tb data an atmospheric correction is applied following an EUMETSAT OSI SAF correction scheme in SIC retrieval algorithms. The daily thin ice chart was validated using MODIS ice thickness daily charts over the Barents and Kara Seas. The average probability for misclassification of thick ice as thin ice in the daily chart was 8.7%, and vice versa 37.0%. Here we investigate Arctic thin ice detection also with FY-3C microwave radiation imager (MWRI) data, which has somewhat coarser resolution than AMSR2, and modify the Tb atmospheric correction to compensate for variation of the sea ice effective temperature. The MWRI thin ice detection algorithm is also trained using the MODIS ice thickness charts. The AMSR2 and MWRI daily thin ice charts are calculated for one winter, and their statistical similarities and differences are investigated. They are also compared against the SMOS ice thickness data. First results for one month (Dec 2016) showed that the AMSR2 thin detection algorithm can be applied successfully to coarser resolution MWRI data. The AMSR2 and MWRI daily thin ice charts are targeted to be used together with SAR imagery (e.g. Sentinel-1) for various sea ice classifications. For SIC and snow depth retrieval algorithms the charts could indicate presence of thin ice either for pixel flagging or corrective actions. This work is part of the Dragon5 project ‘Synergistic Monitoring of Arctic Sea Ice from Multi-Satellite-Sensors’.
Wiebke Margitta Kolbe, Gorm Dybkjær, Rasmus Tage Tonboe, Steinar Eastwood, Pia Nielsen-Englyst, Jacob Høyer, André Toft Jensen
Corresponding author: Wiebke Margitta Kolbe
Corresponding author e-mail: wmako@space.dtu.dk
40 years of the sea ice surface temperature (IST) essential climate variables (ECV) have been collected in a single Level 3 IST product by the Copernicus Climate Change Service (C3S). The C3S IST record v1 consists of the IST climate data record (ISTCDR v1) of the Arctic and Antarctic surface temperature from thermal infrared satellite sensors (AASTI v2.1), a brokered level 3 dataset from DMI and MET covering the period 1982 to June 2019, and a temporal extension in the form of the C3S IST Interim CDR (ICDR v1) covering July 2019 to June 2022. This CDR and ICDR also include the sea surface temperature (SST) ECV, providing a consistent surface temperature field for the Arctic and Antarctic, covering sea, sea ice, as well as land ice with mean and max-min daily temperatures poleward of 50° N and S, based on an algorithm, which is a combination of algorithms specifically tuned for high latitude open water, sea ice and the marginal ice zone (MIZ). Each algorithm is tuned specifically for each of the AVHRR instruments in the record, using ECMWF atmospheric reanalysis surface and atmosphere data and simulated top of the atmosphere (TOA) brightness temperatures (Tbs). Simulated TOA Tbs are computed using the community radiative transfer model, RTTOV. When sea ice in the MIZ melts because of warm temperatures it leaves behind cold water. On interannual timescales cold water is still warmer than sea ice surfaces and it is therefore complicated to derive climate surface temperature trends in the marginal ice zone. Due to the tuning of the algorithm, this data record provides consistency between sea and sea ice surface temperatures in the MIZ. Surface temperature climatology and trends will be computed for high latitude sea surface, MIZ and sea ice. The IST CDR & ICDR, as well as initial results of the trend analysis will be presented at the symposium.
Tore Wulf, Jørgen Buus-Hinkler, Matilde Brandt Kreiner, Suman Singha
Corresponding author: Tore Wulf
Corresponding author e-mail: twu@dmi.dk
The melting of Arctic sea ice due to anthropogenic warming has led to increased human activity in the region. As a result, maritime safety and planning require detailed and timely information about the state of the Arctic sea ice. Synthetic aperture radar (SAR) imagery can provide this information with a high spatial resolution, independence of solar illumination, and unimpeded by cloud cover. SAR imagery is an important source of information for the National Ice Centres worldwide, where ice analysts produce sea ice charts for maritime users. However, the manual interpretation of these images can be time-consuming, and with the incresing avaialability of satellite imagery, a partially automated process can assist the ice analysts in delivering high-resolution sea ice products in near-real-time. Fully automated sea ice mapping systems using deep learning-based models, such as Convolutional Neural Networks (CNNs), can provide high-resolution sea ice products to be integrated into forecast models to potentially improve forecast quality. Traditional machine learning techniques for SAR-based sea ice mapping, which rely on manually engineered texture features, have been limited due to the inherent ambiguity of SAR data. In our approach, we train a CNN in a supervised setting using manually produced ice charts as label data. Our CNN fuses high-resolution Sentinel-1 SAR imagery and passive microwave radiometer (PMR) observations from AMSR-2 to generate high-resolution maps of sea ice. Although microwave signatures in SAR imagery show patterns related to ice formations, classifying sea ice in SAR imagery is not a trivial task due to the ambiguities in backscatter intensities, noise phenomena and wind-induced surface roughness. Our approach tackles this obstacle by increasing the receptive field of the CNN and by fusing the SAR imagery with PMR observations. The CNN processes Sentinel-1 EW and IW GRD products resampled to an 80 m grid, which is close to the native spatial resolution of Sentinel-1 EW products. Our CNN achieves an R2-score of 92% against manually produced ice concentration charts, indicating a good level of agreement between the CNN and the ice analysts. However, manual ice charts have inherent uncertainties that are not well-documented, such as analyst subjectivity, inter- and intra-analyst variation, and mislabeling errors. Systematic biases introduced by the manual ice charting method might therefore be reproduced by the CNN.
Sea ice surface radiative fluxes from ground and airborne observations in the Weddell Sea
Gaëlle Veyssière, Jeremy Wilkinson, Povl Abrahamsen, Pushyami Kaveti, Isobel R. Lawrence, Carl Robinson, Sebastian Bjerregaard Simonsen, Hanumant Singh, Henriette Skourup
Corresponding author: Gaëlle Veyssière
Corresponding author e-mail: gaevey@bas.ac.uk
Despite global warming, Antarctic sea ice expanded during most of the first four decades of satellite observations. However, in 2016, the Antarctic sea ice area plummeted, in a change far outside the range of previously observed variability followed by a new sea ice minimum reached on 1 February 2022. Understanding the partitioning of solar radiation by snow and sea ice is critical to understand sea ice mass balance and to assess how much solar radiations reach the upper ocean. In addition, light is one of the critical drivers of primary production within and under sea ice; it acts as a trigger for sea-ice algae and phytoplankton blooms. In this study, we present the results from two campaigns in the Weddell Sea to further our understanding of solar radiation partitioning in this region of the Southern Ocean. In situ measurements of radiative fluxes were performed over young Antarctic sea-ice in March/April 2022 during a cruise campaign in the northern Weddell Sea. During this campaign, incoming, reflected and transmitted solar irradiances through snow and sea ice were measured. Further, shortwave, and longwave radiations fluxes were collected as part of an airborne survey over packed and broken sea ice in the western Weddell in December 2022. Combining these two sets of measurements, we aim to better understand the amount of solar energy reaching the sea ice surface and how changes in open water fraction influence the sea ice melt rates via increased solar absorption.
Simulating deformation structure in viscous-plastic sea-ice models with CD-grid approaches
Carolin Mehlmann, Sergey Danilov, Giacomo Capodaglio
Corresponding author: Carolin Mehlmann
Corresponding author e-mail: carolin.mehlmann@ovgu.de
Linear kinematic features (LKFs) are found everywhere in the Arctic sea-ice cover. They are strongly localized deformations often associated with the formation of leads and pressure ridges. Viscous–plastic sea-ice models start to produce LKFs at high spatial grid resolution, typically with a grid spacing below 5 km. Besides grid spacing, other aspects of a numerical implementation, such as discretization details, may affect the number and definition of simulated LKFs. To explore these effects, simulations with different sea-ice models such as MPAS, CICE, ICON, FESOM and MITgcm are compared in an idealized configuration. We found that the nonconforming finite-element CD-grid discretization produces more LKFs than the CD-grid approximation based on a sub-grid discretization. Furthermore the nonconforming finite-element approach simulates the same number of LKFs as conventional Arakawa A-grid, B-grid, and C- grid methods, but on grids with fewer degrees of freedom ( a coarser mesh). This is due to the fact that CD-grid approaches have a higher number of degrees of freedom to discretize the velocity field. Due to its enhanced resolving properties, CD-grid methods are an attractive alternative to conventional discretizations.
Pooling resources to investigate and share information on sea ice: the Sea Ice Portal
Klaus Grosfeld, Renate Treffeisen, Seaiceportal team
Corresponding author: Renate Treffeisen
Corresponding author e-mail: renate.treffeisen@awi.de
Today, sea ice covers roughly 7% of the ocean. It cools the entire planet, affects ocean currents and offers a habitat for countless species. Due to climate change, sea ice is rapidly disappearing – with consequences for the entire planet. On Sea Ice Portal we share what we know – hot off the press, scientifically sound, and in accessible language. The Sea Ice Portal (www.seaiceportal.de) is an information and data portal on the topic of sea ice and offers essential information on this and many other developments. Since 2023, the joint project of the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), the Helmholtz Climate Initiative REKLIM, and the University of Bremen is available in a completely new format – with a more modern interface and new, more accessible content specially targeting users who are newcomers to the topic of sea ice. The portal has undergone a rigorous relaunch according to the newest knowledge of usability, search engine optimization as well as responsiveness on different digital platforms. The Sea Ice Portal was developed within the framework of the Helmholtz Climate Initiative ‘Regional Climate Change and Humans’ (REKLIM) and as a joint project of the Climate Office at the AWI, the University of Bremen and the AWI – one of the world’s leading sea-ice research centres. Researching the sea ice of the Arctic and Antarctic and highlighting its essential role in the Earth system is a substantial scientific undertaking. Accordingly, research institutes from around the globe have joined forces, allowing each to benefit from the strengths of the others. The same applies to knowledge transfer. We pursue research on a public basis for the benefit of all, yet it is equally important that all have access to our findings. Consequently, strong partners from the sea-ice research community have formed an alliance to share information on their findings. Since going online in 2013, the Sea Ice Portal has provided reliable, research-based information, straight from the source: daily updated ice maps based on satellite readings, regular news updates on the latest trends, expedition reports from researchers working directly on the ice, and detailed background articles – e.g. on sea-ice formation and measuring methods –, not to mention a data portal allowing users to directly access raw scientific data and work with it themselves.
Modeled ice algal production in antarctic landfast sea ice
Pat Wongpan, Klaus M/ Meiners, Martin Vancoppenolle, Alexander D. Fraser, Sebastien Moreau, Benjamin T Saenz, Kerrie M. Swadling, Delphine Lannuzel
Corresponding author: Pat Wongpan
Corresponding author e-mail: pat.wongpan@utas.edu.au
Much of the Antarctic coast is fringed by seasonal landfast sea ice (fast ice), which serves as an important habitat for ice algae. Fast-ice algae provide a key early-season food source for coastal pelagic and benthic food webs, and contribute to biogeochemical cycling in Antarctic coastal ecosystems. Despite the fact that sea ice algae only contributes an estimated ∼1% of total Southern Ocean primary production, and 12–50% of total primary production in the sea ice zone, sea ice algae are ecologically significant because their production occurs in locations and at periods when production in the water column is limited. The overall productivity of fast-ice algae has remained un-quantified due to both limited observations and modeling efforts. By linking a novel, high-resolution fast-ice distribution dataset with a one-dimensional sea-ice biogeochemical model, we provide the first estimate of the spatio-temporal variability of Antarctic fast ice-associated algal primary production and annual gross production on a circum-Antarctic scale. Modeled annual fast-ice primary production estimates, with a focus on the 2005/06 season, range from 2.6 to 4.4 Tg C y–1, depending on sensitivity experiments. These estimates represent about 11–19% of the overall Southern Ocean sea-ice algae production. Fast-ice-associated primary productivity is larger than that of pack ice in the Indian Ocean Sector. Due to the uncertain interactions of these often overlooked but crucial components of the nearshore Antarctic system, incorporating Antarctic fast ice into Antarctic ice–ocean–atmosphere models becomes an urgent priority. Altogether, primary production in Antarctic fast ice is a major component which is poorly understood, and this greatly limits our ability to accurately project its future.
Ed Blockley
Corresponding author: Ed Blockley
Corresponding author e-mail: ed.blockley@metoffice.gov.uk
Sea ice plays an important role in the Earth system. In winter the sea ice insulates the relatively warm ocean from the colder atmosphere above. while in summer the higher albedo of sea ice reflects more of thesun’s radiation back to space. Sea ice also plays a key role in how the climate responds to changes in radiative forcing, such as those induced by atmospheric CO2 increase. In climate models, changes in sea ice cover are inherently tied to changes in temperature, with global-mean surface temperature trends being related to sea ice trends in both hemispheres. Feedbacks associated with the loss of sea ice contribute to the sensitivity of the climate system (to CO2) and, through the ice–albedo feedback, to the polar amplification of warming. The initial sea ice state of a model, therefore, is important for the future projections of both global temperature and sea ice cover. Furthermore, the underlying variability of the system is important for how we interpret future changes in the model – in particularly whether those changes can be intrinsically tied to changes in the external (CO2) forcing or are consistent with (internal) variability. The CMIP6 model HadGEM3-GC3.1-LL exhibits considerable variability in its pre-industrial control run – with both Antarctic sea ice and global temperature varying considerably on centennial scales. As well as persistent open water polynyas in the Weddell Sea, the model also exhibits occasional, deep convection-driven, polynya events in the Ross Sea that have been linked with state change in the global climate. To understand the impact of such variability, and state change, for the global climate evolution, new CMIP runs have been performed with HadGEM3-GC3.1-LL over a much longer (2000+ years) pre-industrial control than was used for CMIP6. In this talk we show how the initial Antarctic sea ice state effects the evolution and climate sensitivity (to CO2) in these new climate change runs. We also show that the way in which the model variability and drift is taken into account has considerable impact on the interpretation of trends and changes in the climate system in these model simulations.
Sea-ice-thickness product intercomparison exercise: the ESA SIN’XS project
Elodie Da Silva, Christian Haas, Sara Fleury, Michel Tsamados, Stephan Paul, Mathis Bertin, Eric Munesa, Stefan Hendricks, Javier Pastor, Jerome Bouffard
Corresponding author: Christian Haas
Corresponding author e-mail: chaas@awi.de
The sea ice-thickness product inter-comparison exercise (SIN’XS) project, led by NOVELTIS in collaboration with AWI, LEGOS and UCL, is a 3-year activity (May 2022–May 2025) funded by ESA in the frame of the Polar Science Cluster, with the objective to foster collaborative research and interdisciplinary networking actions. In light of rapid changes of the Arctic and Antarctic sea ice cover, continued and improved observations, understanding and predictions of its thickness are particularly important for a range of fields from climate studies to offshore operations in ice. Systematic and accurate ice thickness observations are now available from several satellite missions. However, they differ in used processing algorithms and assumptions, temporal and spatial coverage and resolution, and applicability to stakeholder needs like modelling and assimilation, numerical weather prediction, and ship routing. These differences between products have so far complicated the consistent use of the various data products, and there is little consensus about Arctic and Antarctic sea ice volume variability and change. SIN’XS will identify some of these gaps by carrying out in-depth intercomparisons of a wide range of satellite ice thickness products from altimetry and other methods, in close collaboration with an international community of scientific and operational sea ice experts, and in partnership with the WMO Global Cryosphere Watch (GCW).It will develop joint protocols for the intercomparison of ice thickness products and their validation, using established approaches from the GEO/CEOS quality assurance framework for Earth observation (QA4EO) and by further developing a framework for fiducial reference measurements. SIN’XS will develop an online system to engage the community with data submission and to support scientific analysis and impact assessment of the data sets and intercomparisons. The poster will present the main objectives, the tools and the first outcomes of the project.
Robert Ricker, Steven Fons, Arttu Jutila, Nils Hutter, Kyle Duncan, Sinéad L. Farrell, Nathan T. Kurtz, Renée Mie Fredensborg Hansen
Corresponding author: Robert Ricker
Corresponding author e-mail: rori@norceresearch.no
Information about the sea ice surface topography and deformation is crucial for studies of sea ice mass balance, sea ice modeling and ship navigation through the ice pack. NASA’s Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) has been on-orbit for over 4 years, sensing the sea ice surface topography with six laser beams capable of capturing individual features such as pressure ridges. To assess the capabilities and uncertainties of ICESat-2 products, coincident high-resolution measurements of the sea ice surface topography are required. During the year-long Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) Expedition in the Arctic Ocean, we successfully carried out a coincident underflight of ICESat-2 with a helicopter-based airborne laser scanner (ALS) achieving an overlap of more than 100 km. Despite the comparably short data set, the high-resolution ALS measurements on centimetre scales demonstrate their vales for evaluating the performance of ICESat-2 products. Here we present the results of our study, which investigated how sea ice surface roughness and topography are represented in different ICESat-2 products, and how sensitive ICESat-2 measurements are to leads and small cracks in the ice cover. We compared the ALS measurements with ICESat-2’s primary sea ice height product, ATL07, and the high-fidelity surface elevation product developed by the University of Maryland (UMD). We developed a ridge-detection algorithm and found that 16% (4%) of the number of obstacles in the ALS data set are found using the strong (weak) center beam in ATL07. Significantly higher detection rates of 42% (30%) are achieved when using the UMD product. We also analyzed the presence of leads in the ICESat-2 data. While only one lead is indicated in ATL07 for the underflight, the ALS reveals many small and only partly open cracks that appear to be overlooked by ATL07. Eventually, this study links the MOSAiC ALS measurements with ICESat-2 measurements from space, to allow studying the evolution of surface topography and deformation of the sea ice in the vicinity of the MOSAiC camp in the context of large-scale changes captured by ICESat-2.
Capacity of the selected CMIP6 models to simulate Arctic sea ice drift
Xinfang Zhang, Jari Haapala
Corresponding author: Xinfang Zhang
Corresponding author e-mail: xinfang.zhang@fmi.fi
Evaluating CMIP6 model performance helps to improve the prediction of future changes in Arctic sea ice. We aim to look at the seasonal cycles, ice distribution, and evolution in different regions between 1979 and 2014, and compare CMIP6 output with observations. We also discuss the coupling behaviors between ice motion and sea ice extent (SIE), thickness variation in observations, and how CMIP6 models explain them. Following six models were selected for the CMIP6 study: EC-Earth3, ACCESS-CM2, BCC-CSM2-MR, GFDL-ESM4, MPI-ESM1-2-HR, and NorESM2-LM for ice concentration (SIC), thickness (SIT), and velocity data. These outputs are compared with the reference data: SIE from the Gridded Monthly Sea Ice Extent and Concentration dataset by NSIDC; SIT from PIOMAS and CryoSat2 data; and sea ice speed from the IABP buoy data. The analytical techniques include linear regressions and calculation of propagation uncertainties when comparing the CMIP6 models with observations. Most model outputs have a similar seasonal cycle to the observations when it comes to SIE and ice motion, while more than half of the CMIP6 models can not simulate the seasonal cycles for SIT well particularly during summer due to the high uncertainty of SIT data in summer months. There’s a visible decreasing trend of SIT in both PIOMAS and CMIP6 outputs in the Arctic between 1979 and 2014. Almost all CMIP6 models and PIOMAS agreed that winter sea ice is thicker than summer, while in summer, sea ice has a faster thinning process. However, the deviation rate of SIT magnitude in the CMIP6 model output is generally high. CMIP6 model output for sea ice motion does not have a high deviation compared with the IABP buoy data, except for the MPI-ESM1-2-HR model. Most CMIP6 models simulated an increasing trend of sea ice motion, but the rate of increase is much lower than in reality, and they failed to capture the increasingly accelerating feature of sea ice motion. According to regional comparisons in SIT and ice motion, the ice motion is accelerating in the whole Arctic. The marginal sea has a faster sea ice thinning process and sea ice motion acceleration compared with the central Arctic, some CMIP6 models can capture this feature. Among the marginal seas, Laptev and the East Siberian Sea are becoming more active in the 36 years. In general, SIT and SIE are the influencing factors of ice motion acceleration, but the negative correlation between SIT, SIE, and sea ice speed is weak, especially in CMIP6.
Sea ice thematic data products for CRISTAL: design, development and validation
Michele Scagliola, Jerome Bouffard, Paolo Cipollini
Corresponding author: Michele Scagliola
Corresponding author e-mail: michele.scagliola@esa.int
The Copernicus Polar Ice and Snow Topography Altimeter (CRISTAL) is a satellite system developed as part of the European Union Copernicus program expansion activities. The main objective of the CRISTAL mission design is to measure and monitor variability of Arctic and Southern Ocean sea ice thickness and its snow depth. Built on the heritage of CryoSat, the CRISTAL instrument technical solution is based on a dual-frequency synthetic-aperture radar altimeter with interferometric capabilities at Ku-band and a second Ka-band frequency. Throughout this abstract it is described the current plan for the design, development and validation of the ESA CRISTAL Level-2 Thematic data products (TDP), which are related to the sea ice, land ice and hydrology aspects of the Mission. The CRISTAL Level-2 TDP and algorithms are planned to be provisioned in a two-step approach prior to launch: a ground processor prototype will be designed and developed in a first stage, with the primary objective of defining the Level-2 product format and up-to-date algorithms for the geophysical variables retrieval to leverage the full capabilities of the CRISTAL instruments, while the operational processor will be developed in a second stage. The CRISTAL Level-2 ground processor prototype in the sea ice domain will implement the geophysical retrieval algorithms for the following variables: sea ice freeboard, sea ice thickness, snow depth over sea ice, ice shelves thickness, iceberg distribution and volume. To achieve the mission performance objectives, advanced geophysical retrieval algorithms for sea ice and icebergs are needed to be defined so that the Level-2 GPP activity will carry on R&D studies to support the definition and implementation of the retrieval algorithms. Another key task to be carried on is the definition of the methods and protocols for the validation of the CRISTAL Level-2 TDP. An in-flight validation plan will be prepared to define methods and protocols for the validation of the CRISTAL Level-2 products versus fiducial refence measurements and in synergy with other missions, primarily with the other Copernicus Expansion Missions operating in the polar domain, CIMR and ROSE-L. The activities for the design and development of the CRISTAL Level-2 ground processor prototype will start in 2023 and others will follow in the next years having 2027 as target date for CRISTAL launch.
Tracking individual sea ice floes using in-situ ice drift observations
Catherine Taelman, Anthony P. Doulgeris, Johannes Lohse
Corresponding author: Catherine Taelman
Corresponding author e-mail: cta014@uit.no
In April and May 2022, the Centre for Integrated Remote Sensing and Forecasting for Arctic Operations (CIRFA) conducted a research cruise (CIRFA-22 cruise) to the Belgica Bank area in western Fram Strait. During this cruise, 17 buoys were deployed on drifting sea ice and collected a unique data set of in-situ sea ice drift observations in Fram Strait and the Greenland Sea. The buoys sampled a GPS position at 30 min intervals, and the resulting time series covers the transition from freezing conditions to melt onset. These observations provide the opportunity to track individual sea ice floes and retrieve their synthetic radar aperture (SAR) time series. Previously, studies on Lagrangian tracking approaches for sea ice have demonstrated that satellite-based methods work well to reconstruct sea ice trajectories in the Arctic basin. However, these satellite-based methods have a limited performance in Fram Strait, due to the high drift speeds characterizing this region. We therefore use the in-situ drift observations collected during the CIRFA-22 cruise to retrieve SAR sea ice trajectories. All Sentinel-1 images overlapping with the in-situ trajectories are automatically found and the drifter is located in each satellite scene. The main idea is that we expand the tracked areas by identifying distinct surface structures or floes that are clearly visible in the vicinity of the drifter location in consecutive radar images. This enables us to obtain the SAR time series for a much larger number of floes and ice structures than are tagged by buoys. Identification and tracking of the features in the vicinity of the drifter is first done manually. We also demonstrate how to automate this step using a combination of feature detection and pattern matching algorithms (e.g. region growing and image correlation), with the manually identified features as validation. Finally, we show how the SAR time series can be used to study the temporal evolution and incident angle dependence of radar backscatter signatures of individual floes or sea ice structures, as they undergo physical changes during melt onset. This topic has been extensively studied for landfast ice, but rarely for drifting sea ice.
Evgenii Salganik, Benjamin A. Lange, Philipp Anhaus, Christian Katlein, Ilkka Matero, Julia Regnery, Knut V. Høyland, Mats A. Granskog
Corresponding author: Evgenii Salganik
Corresponding author e-mail: salganikea@gmail.com
During the melt season, sea ice melts from the surface and bottom. The melt rates substantially vary for sea ice ridges and undeformed first- and second-year ice. Ridges generally melt faster than undeformed ice, while the melt of ridge keels is often accompanied by further summer growth of their consolidated layer, which increases their survivability. We examine the spatial variability of ice melt for different types of ice from in situ drilling, coring and multibeam sonar scans of remotely operated underwater vehicle. Six sonar scans performed between 24 June and 21 July were analyzed and validated using seven ice drilling transects. The area investigated by the sonar (0.4 km×0.2 km) consisted of several ice ridges, surrounded by first- and second-year ice. We show a substantial difference in melt rates for sea ice with a different draft. We also show how ridge keels decay depending on the keel draft, width, steepness and location relative to the surrounding ridge keel edges. We also use temperature buoy data to distinguish snow, ice surface and bottom melt rates for both ridges and level ice. These results are important for quantifying ocean heat fluxes for different types of ice during the advanced melt, and for estimation of the ridge contribution to the total ice mass and summer meltwater balances of the Arctic Ocean.
Sea ice age climate data record
Anton Korosov, Leo Edel
Corresponding author: Anton Korosov
Corresponding author e-mail: anton.korosov@nersc.no
The SICCI sea ice age algorithm previously developed by us (Korosov et al., 2018) has several advantages over the classical NSIDC ice age algorithm as it produces continuous fields of fractions of ice of different age. That allows to compute sea ice age as a more accurate weighted average of the fractions. In addition, that increases the accuracy of the multi-year ice (MYI) area estimation. The ice age algorithm was further improved by using a Lagrangian triangular mesh instead of a Eulerian advection scheme. The mesh moves together with sea ice drift, which reduces the diffusion of fractions of ice of older age. The mesh is re-meshed in order to keep the area and the perimeter of the elements in a predefined range. Contribution to the new elements of the re-meshed mesh from the original elements is computed as area weighted average, and the weights are saved at each advection step. That allows us to do the computationally expensive advection of the mesh only once and then reuse the weights and indexing of the elements for advecting any sea ice property almost instantaneously. The new sea ice age algorithm was applied to the newly released climate data record of sea ice drift (OSI-455) from Ocean and Sea Ice Satellite Application Facility (OSI SAF) and a data record of sea ice age from 1995–2020 was produced. Analysis of individual fractions of ice age distinctly show two changes in the regime in the Arctic sea ice. First, there is a gradual replacement of MYI by first-year ice observed in the period 2000–10. Second, there is a sudden drop in the replenishment of 6-year old ice in 2017.
Investigating the incorporation of micro- and nanoplastics into young artificial sea ice
Alice Pradel, Martin Schneebeli, Denise M. Mitrano
Corresponding author: Alice Pradel
Corresponding author e-mail: alice.pradel@gmail.com
Microplastics (MPs, 1 &mum–5 mm) and nanoplastics (NPs, <1 &mum) are accumulating in the Arctic Ocean. They can pose hazards to polar organisms and impact biogeochemical cycles. Therefore, it is crucial to determine the transport pathways of MPs and NPs in the Arctic Ocean, including their incorporation into sea ice. Due to climate change, Arctic sea ice is increasingly young and thin. Since, the formation of young sea ice strongly redistributes concentrations of dissolved and particulate species, we investigated how MPs and NPs are engulfed or expulsed from a freezing front. We hypothesized that particles’ density and effective size (i.e. the size of a single particle if dispersed or of aggregated particles) will govern the extent of their enrichment in sea ice. We used a novel experimental design that mimics the freezing of seawater to systematically assess to what extent and by which processes particles are accumulated in sea ice. This design allows us to control the system temperature, salinity and pressure, which constitutes a significant improvement compared to other experimental designs. We used artificial Arctic Central Basin surface waters (32 g L–1, pH 7.97) and model MPs (63–125 &mum and <63 &mum) and NPs (174 ± 42 nm) that were doped with metal tracers, allowing them to be quantified in low concentrations by ICP-MS. We plan to study carbon black to compare how particle size and chemistry influences engulfment by the growing ice front. Each freezing experiment was conducted in triplicate with a temperature gradient from –6 to 1°C. The ice core was removed and centrifugated at –2.3°C to separate the connected brine while preserving the ice core structure. This allowed us to i) obtain a mass balance of particles in the brine, brine-free ice and underlying liquid separately and ii) analyze the structure of the ice by micro-computed tomography. By combining this unique data we gain insight into how the formation of young sea ice impacts particle transport.
Polar thematic data products for CIMR: DESIGN, development and validation
Michele Scagliola, Pierre Féménias, Craig J. Donlon, Klaus Scipal
Corresponding author: Michele Scagliola
Corresponding author e-mail: michele.scagliola@esa.int
The Copernicus Imaging Microwave Radiometer (CIMR) is a satellite system developed as part of the European Union Copernicus program expansion activities. The main objective of the CIMR mission design is to fulfill the need to measure fundamental quantities associated with large-scale ocean–cryosphere–atmosphere processes. The CIMR instrument technical solution is based on a multi-channel conically scanning microwave imaging radiometer that includes channels between 1.4 and 36.5 GHz. CIMR will allow to provide geophysical estimates with an increased accuracy, spatial resolution and temporal resolution compared to current products. Here, the current plan for the design, development and validation of the ESA CIMR Level-2 thematic data products in the polar domain is described. The CIMR Level-2 processing will comprise two main steps: a remapping/regridding tool and an ensemble of retrieval functions. The CIMR remapping/regridding tool will be in charge of remapping the brightness temperatures so that the field of view of different channels is resampled at common resolution and location. The retrieval functions aim to estimate the different geophysical variables and to arrange the results in Level-2 TDP. In particular, polar Level-2 TDP will contain the geophysical variables related to the polar domain (e.g. sea ice concentration, sea surface temperature, thin sea ice thickness, sea ice edge). The CIMR Level-2 TDP and algorithms are planned to be provided in a two-step approach prior to launch: a ground processor prototype will be designed and developed in a first stage, with the primary objective of defining the Level-2 product format and up-to-date algorithms to leverage the full capabilities of the CIMR instrument, while the operational processor will be developed in a second stage. Another key task is the definition of the methods and protocols for the validation of the CIMR Level-2 TDP. An in-flight validation plan will be prepared to define methods and protocols for the validation of the CIMR Level-2 products versus fiducial refence measurements and in synergy with other missions, primarily with the other Copernicus expansion missions operating in the polar domain, CRISTAL and ROSE-L. The activities for the design and development of the CIMR Level-2 ground processor prototype will start in 2023 and others will follow in the next few years, with 2028 as target date for CIMR launch.
Fracture properties of sea ice across spatial and temporal scales
Wenjun Lu, Sveinung Løset, Aleksey Shestov
Corresponding author: Wenjun Lu
Corresponding author e-mail: wenjun.lu@ntnu.no
Fracture of sea ice plays an important role in both ice engineering applications and geophysical-scale ice modelling. However, these two research communities seem to interpret and handle sea ice fracture rather differently due to the scale differences in their respective research questions. However, the need for high-resolution ice modelling and progress in scientific computing enable us to close this gap and treat sub-scale physical processes in more details. This means that we will have the computation tool/capacity to model detailed ice fractures up to the floe scale (i.e. 1 m–100 km). However, before we perform any meaningful modelling, inputs are critical. Among all the related inputs, the fracture properties of sea ice at various scales must be studied. The fracture properties (e.g. the fracture toughness) of sea ice studies are not new. However, its scaling issue is a lasting problem subjected to decades of debates. For example, the ‘fracture toughness’ measured in the lab and in the field are almost twice different. To address this issue, we performed a series of field ice fracture experiments over five seasons (2015, 2016, 2017, 2018 and 2023) in Svea, Svalbard. This paper will report some of the processed results and discuss the fracture properties of sea ice across various spatial and temporal scales. The authors acknowledge financial support from the Research Council of Norway (RCN) through the research centre SAMCoT CRI to carry out the field experiments. The first author would also like to thank VISTA, a basic research programme in collaboration between the Norwegian Academy of Science and Letters and Equinor (former Statoil), for financial support in theoretical studies in this paper. Last, we would also like to thank the RCN for financial support through the research project ‘Multi-scale integration and digitalization of Arctic sea ice observations and prediction models (328960)’.
Improving short-term sea ice predictability using deformation observations
Anton Korosov, Pierre Rampal, Einar Olason
Corresponding author: Anton Korosov
Corresponding author e-mail: anton.korosov@nersc.no
Short-term sea ice predictability is challenging despite recent advancements in sea ice modelling and new observations of sea ice deformation that capture small-scale features (open leads and ridges) at kilometre scale. A new method for assimilation of satellite-derived sea ice deformation into the Next-Generation Sea Ice Model (neXtSIM) is presented. Ice deformation provided by the Copernicus Marine Service is computed from sea ice drift derived from synthetic aperture radar at a high spatio-temporal resolution. We show that high values of ice deformation can be interpreted as reduced ice concentration and increased ice damage – scalar variables of neXtSIM. This proof-of-concept assimilation scheme uses a data insertion approach and forecasting with one member. We obtain statistics of assimilation impact over a long test period with many realizations starting from different initial times. Assimilation and forecasting experiments are run on synthetic and real observations in January 2021 and show increased accuracy of deformation prediction for the first 2–3 days. It is demonstrated that neXtSIM is also capable of extrapolating the assimilated information in space – gaps in spatially discontinuous satellite observations of deformation are filled with a realistic pattern of ice cracks, confirmed by later satellite observations. Limitations and usefulness of the proposed assimilation approach are discussed in a context of ensemble forecasts. Pathways to estimate intrinsic predictability of sea ice deformation are proposed.
Valentin Ludwig, Helge Goessling, Axel Schweiger, Laurent Bertino, Ed Blockley, Frédéric Dupont, Wendy Ermold, Robert Grumbine, Yukie Hata, Jennifer Hutchings, Antonia Jost, Frank Kauker, Thomas Krumpen, Jean-François Lemieux, François Massonnet, E. Joseph Metzger, Malte Müller
Corresponding author: Valentin Ludwig
Corresponding author e-mail: valentin.ludwig@awi.de
The deformation of sea ice drives the opening and closing of leads within the ice pack, which can impact the ice mass balance through freezing and melting processes. In our contribution, we assess the capability of a variety of sea-ice forecasting systems to represent and predict the deformation mainly of the MOSAiC Distributed Network (DN), but also of buoy arrays at larger spatial scales. The forecasts stem from the Sea Ice Drift Experiment (SIDFEx). In the framework of SIDFEx, we have been collecting more than 200 000 forecasts for trajectories of single sea-ice buoys in the Arctic and Antarctic since 2017. Forecasts are provided by various forecast centres and collected into a common archive system for consistent access and processing. Their lead times range from daily to seasonal scales. We know from previous studies that the systems have skill at predicting the motion of individual buoys, but expanding this analysis to an array of buoys to study deformation is something novel, the current state of which we will be presenting here. For 1-day forecasts, our findings show significant correlations of 0.54 for total deformation at DN scale (area of 4000 km), with correlations for divergence (0.18) being worse than for shear (0.6). At pan-Arctic scale, the correlations increase to 0.69 for total deformation, 0.58 for divergence and 0.85 for shear. We explain the scale dependence by the design of the models, which are designed for representing sea-ice kinematics at large scales with smoothly varying strain rates over scales which are larger than those of the DN.
Stefan Kern, Rasmus Tage Tonboe, Wiebke Margitta Kolbe, Thomas Lavergne
Corresponding author: Stefan Kern
Corresponding author e-mail: stefan.kern@uni-hamburg.de
Sea ice concentration products derived from satellite microwave radiometer observations form the basis of today’s knowledge of the polar sea ice area during the past 50 years. Within the framework of ESA’s Climate Change Initiative Sea Ice ECV project ‘Sea_Ice_cci’ brightness temperature observations of the electrically scanning microwave radiometer (ESMR) onboard the Nimbus-5 satellite were used to derive a new sea ice concentration product (https://doi.org/10.5285/34a15b96f1134d9e95b9e486d74e49cf). This product covers the period 1972 to 1977 and hence extends known sea ice concentration products, e.g. from Eumetsat OSI SAF or NOAA/NSIDC, back into the past. In this contribution, we show first results of an inter-comparison of Sea_Ice_cci ESMR sea ice concentrations with sea ice concentrations estimated from clear-sky Landsat-1 Multispectral Scanner System (MSS) visible / near-infrared imagery. We obtained Landsat Collection 2 Level-1 Landsat data via USGS’ Earthexplorer web portal https://earthexplorer.usgs.gov/. We use measurements at bands 4 through 6 at 60 m grid resolution to compute the top-of-atmosphere reflectance which we combine to an estimate of the broadband shortwave surface albedo after performing a simple correction for the atmospheric influence. We visually inspect the resulting albedo maps and carry out a manual classification into the three surface types open water, thin (bare) ice and, thick (snow-covered) ice using scene-specific albedo thresholds. Subsequently, we use these classified maps to compute Landsat sea ice concentration on the 25 km resolution grid of the ESMR sea ice concentration product. We compare the two sea ice concentration data sets by means of standard statistical measures and discuss the first results in the context of known limitations in both data sets. Our study illustrates the importance of data rescue initiatives to unearth and exploit early satellite missions for production and validation of climate data records.
Thirteen years of CryoSat quality control: evolution and current status of the ice processors
Erica Turner, Alessandro Di Bella, Liv Toonen, Michael Williams
Corresponding author: Erica Turner
Corresponding author e-mail: erica.turner@telespazio.com
Launched in 2010, the European Space Agency’s (ESA) polar-orbiting CryoSat satellite was specifically designed to measure changes in the thickness of polar sea ice and the elevation of the ice sheets and mountain glaciers. To reach this goal, the CryoSat products have to meet the highest data quality and performance standards, achieved through continual improvements of the instrument processing facilities (IPFs). Processing algorithms are improved based on recommendations from quality control (QC) activities, calibration and validation campaigns, the CryoSat Expert Support Laboratory and the scientific community. Since launch, CryoSat QC activities have been performed by the ESA/ESRIN Sensor Performance, Products and Algorithms (SPPA) office with the support of the Quality Assurance for Earth Observation (IDEAS-QA4EO) service led by Telespazio UK. IDEAS-QA4EO routinely monitors all CryoSat ice and ocean products generated operationally. These activities aim to detect anomalies, support investigations, and prevent the distribution of poor-quality data products to users. QC reports, published daily, are a valuable tool for users to understand the quality of the data they are using. QC activities also provide a valuable input to CryoSat processor evolution and all anomalies identified during routine QC are investigated, tracked and later resolved in an updated IPF. The CryoSat Ice products are generated with Baseline-E, following the last major processor upgrade in September 2021. This upgrade brought improvements to all near real time and offline ice products, including improved sea surface height anomaly interpolation, provision of an improved snow depth correction, improvements to land-ice retracking and the addition of pseudo-LRM estimates to the L1B products. Following this, the Ice Baseline-E reprocessing campaign is currently underway to reprocess the full mission dataset (July 2010–September 2021) to Baseline-E, thereby providing a consistent high-quality dataset to users. The IDEAS-QA4EO team plays an important role in the reprocessing campaign, providing best practice guidance and knowledge transfer to the reprocessing team, checking output data products and monitoring processing failures. This poster provides an overview of CryoSat QC activities performed by the IDEAS-QA4EO team on operational and reprocessed CryoSat data products. The main Ice Baseline-E evolutions are presented plus anticipated evolutions for the future.
Investigating the surface energy balance at the Arctic sea-ice edge
Julia Steckling, Markus Ritschel, Johanna Baehr, Dirk Notz
Corresponding author: Julia Steckling
Corresponding author e-mail: julia.steckling@studium.uni-hamburg.de
We characterize and investigate the future evolution of heat fluxes and the resulting surface energy balance at the Arctic sea-ice edge in CMIP6 model simulations. To do so, we build on the study of Notz and Stroeve (2016), in which the existence of a strong linear relationship between Arctic sea-ice area and cumulative anthropogenic CO2 emissions was shown. In explaining this linear relationship, the authors hypothesized that the surface energy balance at the sea-ice edge remains constant, following the conceptual idea of the sea-ice edge retreating northwards to compensate for the increasing longwave radiative input due to global warming by a decrease in shortwave radiation at higher latitudes. We examine the validity of this hypothesis by first identifying the sea-ice edge in the model data, and then scrutinizing whether or not the surface energy balance at the ice edge stays constant under future sea-ice retreat. Furthermore, we decompose the energy balance into its constituents to explore dynamic effects and oceanic influence. We find that the annual mean surface energy balance shows stronger spatial variations than temporal variations as the ice edge moves northwards. Looking at individual seasons, it can be seen that the surface energy balance is negative in winter and positive in summer along the ice edge, while the annual mean remains constant over time in most regions. The only exception is the Atlantic sector, where the surface energy balance has increased from the 1990s, probably caused by an enhanced oceanic influence from the Atlantic inflow. Finally, we find that, at the ice edge, the downwelling longwave radiation increases less with cumulative CO2 emissions than in the Arctic as a whole. The increase in downwelling longwave radiation due to anthropogenic CO2 emissions is thus partially compensated by a reduction of longwave input due to a spatial northward migration of the ice edge. In summary, our findings indicate that to a good approximation, the overall energy balance at the ice edge indeed stays roughly constant in a warming climate.
Quantifying the effect of snow–ice formation on SnowModel-LG snow depth and density product
Ioanna Merkouriadi, Glen Liston, Heidi Sallila
Corresponding author: Ioanna Merkouriadi
Corresponding author e-mail: ioanna.merkouriadi@fmi.fi
This study quantified the effect of snow–ice formation on SnowModel-LG snow depth and density product. We coupled SnowModel-LG, a snow modeling system adapted for snow depth and density reconstruction over sea ice, with HIGHTSI, a 1-D sea ice thermodynamic model, to simulate snow–ice and thermal-ice growth. Pan-Arctic model simulations were performed over the period 1 August 1980 through 31 July 2021. We compared snow depth and density from the coupled product (SnowModel-LG_HS) to outputs from the SnowModel-LG only. In SnowModel-LG_HS, snow depth decreased (domain average: 18%), and snow density increased (2.3%). The differences were much larger in the Atlantic sector. Our simulations suggest that when snow-on-sea-ice models do not account for snow–ice formation, snow depth can be significantly overestimated. Sea ice thickness retrievals from CryoSat-2 were guided by SnowModel-LG_HS and were validated against Airborne Electromagnetic Measurements. SnowModel-LG_HS performance was highest when compared to other snow products.
High resolution analysis of sea ice deformation during MOSAiC
Matias Uusinoka, Arttu Polojärvi, Jari Haapala, Mikko Lensu
Corresponding author: Matias Uusinoka
Corresponding author e-mail: matias.uusinoka@aalto.fi
Past observations on sea ice deformation have usually relied on satellite imagery resulting in low spatial and temporal resolutions even if a lower bound of scale invariance in ice deformation is likely at the scale of ice thickness. In response to the lack of high resolution observational data, ship radar imagery gathered during MOSAiC between November 2019 and May 2020 was used for statistical analysis of seasonal evolution in sea ice deformation and spatio-temporal scaling characteristics with scales down to tens of meters and 1-minute temporal interval. To account for possible sources of error, different definitions of strain were considered. Deformation rate components derived from infinitesimal strain were found to follow the established spatio-temporal power law scaling in the domain of 20 km×20 km. With a 1-minute temporal resolution, the spatial scaling exponent β was observed to approach 0.9 during strong deformation events signifying a high level of localization observable in the domain. Strain-rate statistics were supported by an analysis of relative surface area change to better describe the seasonal evolution of the ice cover and help in distinguishing deformation events.
Understanding the intermodel spread of simulated Arctic September sea-ice sensitivity
M. Katharina Stolla, Hauke Schmidt, Dirk Notz
Corresponding author: M. Katharina Stolla
Corresponding author e-mail: katharina.stolla@mpimet.mpg.de
We investigate the reasons for the intermodel spread of simulated Arctic September sea-ice sensitivity. Previous studies have found that Arctic September sea-ice area declines linearly with cumulative CO2 emissions both in observations and climate-model simulations. However, the models’ sensitivity differs substantially, with the models generally underestimating the sensitivity of sea-ice area to CO2 emissions. We here examine the reasons for the large intermodel spread in order to be also able to understand the general underestimation. We identify a chain of processes contributing to the overall sea-ice sensitivity and investigate the simulation of each sub-process separately in each CMIP6 model. The process chain considers the global-mean temperature response to CO2 increase, Arctic amplification, the increase in incoming longwave radiation, the total non-shortwave heat flux in the Arctic, and the resulting sea-ice loss. In addition, we separately examine the impact of the simulated incoming longwave radiation for the spread of sea-ice sensitivity. Doing so, we find that clouds play a minor role for the spread of simulated incoming longwave radiation but that temperature rise and water vapour content in the Arctic are relevant. Based on these analyses, we identify three processes whose different representation in climate models likely is the main cause for the intermodel spread of simulated sea-ice sensitivity, and which need to be improved to improve the modeled sensitivity of Arctic sea ice: firstly the global-mean temperature response to CO2 increase, secondly the Arctic amplification and thirdly local sea-ice processes. The first two factors highly impact the evolution of temperature in the Arctic which affects the incoming longwave radiation and thus the evolution of sea ice.
Scales apart: from brine pockets to global climate
Dirk Notz
Corresponding author: Dirk Notz
Corresponding author e-mail: dirk.notz@uni-hamburg.de
The interaction between the microstructure of sea ice and the global climate system spans about 10 orders of magnitude in spatial scale. In this overview presentation, I examine how these interactions can be simplified to become accessible for modelling studies, which uncertainties arise in these simplifications, and how we can overcome these. I will focus on an analysis of radiative fluxes that govern the heat balance of Arctic sea ice and that depend on small-scale properties of the ice, on internal phase changes and their impact of the heat storage in the ice, and on the interaction of brine gravity drainage and ocean circulation. A particular focus will be on the potential relationship between the scale of a question we are asking and the related relevant scale of sea-ice–climate interaction.
How can image anisotropy help to improve a sea ice model?
Anton Korosov
Corresponding author: Anton Korosov
Corresponding author e-mail: anton.korosov@nersc.no
The next generation sea ice model (neXtSIM) simulates sea ice drift with very realistic rates and patterns of sea ice deformation. These patterns were previously analysed in terms of spatial scaling (dependence of statistical moments of deformation PDF on spatial scale) and using the linear kinematic features (LKF) analysis: length, orientation, density, and intersection angle of LKFs. Comparison with the satellite observations (the Radarsat Geophysical Processor System dataset) and with other sea ice models showed that neXtSIM ranked among the best for simulating the observed probability distribution, spatial distribution and fractal properties of sea ice deformation, even though it operates on a low-resolution mesh of 10 km. Despite successful applicability of the spatial scaling- and LKF-based metrics for model validation and intercomparison, their applicability for calibration of model parameters is a challenge. These metrics are not sensitive enough to moderate changes of the model rheology parameters. These changes, however, alter the spatial pattern of the LKFs significantly enough to be visible by sight. In this study we present application of the image anisotropy for analysis of the sea ice deformation fields. Anisotropy characterizes elongation of an object on an image and its orientation. Anisotropy is computed in a sliding window at different spatial scales (window sizes). A spatial scale of maximum anisotropy is then detected in each pixel and a PDF of the scales characterizes the field of deformation. These PDFs are quite sensitive to the pattern of LKFs and can be used for fine tuning of model rheology parameters. Another advantage of image anisotropy analysis is a relative simplicity and robustness of the method compared, e.g. to the LKF detection method which has many parameters affecting the results. The anisotropy-based metric allowed to improve parametrization of the sea ice faulting process in the framework of the brittle Bingham–Maxwell (BBM) rheology of neXtSIM.
Airborne observations of melt pond characteristics in different Arctic sea ice regimes
Gerit Birnbaum, Niklas Neckel, Niels Fuchs, Lena Buth, Tim Sperzel, Evelyn Jaekel, Natascha Oppelt, Thomas Krumpen
Corresponding author: Gerit Birnbaum
Corresponding author e-mail: gerit.birnbaum@awi.de
Arctic sea ice is undergoing severe changes in the context of climate change. A critical driver of enhanced sea ice melt is the ice–albedo feedback, with melt ponds being a key element in this mechanism, because they strongly impact the sea ice energy budget by decreasing surface albedo. Here we present an overview of results obtained from airborne measurements over ponded sea ice during summer since 2010. Observations by means of research airplanes and helicopters have been linked to the long-term airborne ice thickness and ice roughness monitoring program run by the Alfred Wegener Institute. The instrument suite for melt pond studies became more complex over the years. We started with a nadir RGB and a hyperspectral camera. Since 2020, the Modular Aerial Camera System (MACS) containing RGB, NIR and TIR sensors, an airborne laser scanner and pyranometers to derive surface albedo have been deployed. In our contribution, we highlight examples of derived high-resolution data sets and case studies focusing on melt pond fraction and size distribution for ice of different roughness and age. Furthermore, newly developed methods to retrieve melt pond bathymetry and melt pond albedo from the aerial image data will be addressed. Additionally, we point to the high potential of new instrument systems such as the MACS to better validate satellite-derived melt pond products. The achieved monitoring of summer sea ice surface properties advances our understanding of ongoing changes impacting the Arctic sea ice energy budget.
A unified sea-ice area data product
Dirk Notz, Jakob Dörr, Stefan Kern, Lena Nicola, Quentin Rauschenbach
Corresponding author: Dirk Notz
Corresponding author e-mail: dirk.notz@uni-hamburg.de
We present a unified data product of sea-ice area from model simulations and observational records. The data product will be made freely available online for research activities, and allows for a consistent, easy-to-use exploitation of the sea-ice area metric for a broad range of purposes. As an auxiliary metric, the product also contains sea-ice extent. The observational record is based on available sea-ice concentration products from historical reconstructions and satellite records. Model simulations are currently available for CMIP control simulations, historical simulations and future scenarios. We discuss the design choices made in deriving sea-ice area from observational records, the approach taken to obtain sea-ice area from model simulations, quantify the uncertainties of the resulting time series, and discuss the respective data formats. The data product contains total sea-ice area separately for the northern and southern hemisphere, and is expected to greatly simplify related research activities of our community
Measuring snow depth on sea ice using a drone-based snow radar
Robert Ricker, Rolf-Ole Rydeng Jenssen, Polona Itkin
Corresponding author: Robert Ricker
Corresponding author e-mail: rori@norceresearch.no
Snow on sea ice is one of the key parameters for the polar climate system regulating sea-ice growth and melt. Moreover, snow depth and density are required to estimate sea ice thickness from satellite altimetry but must be assumed by using a climatology or model simulations based on reanalysis data. However, climatologies and modelled snow parameters lack temporal and spatial variability or convey substantial uncertainties. Obtaining snow depth from satellite measurements has the potential to reduce this gap. Future snow depth retrieval algorithms based on dual-frequency satellite altimetry, such as the Copernicus Polar Ice and Snow Topography Altimeter (CRISTAL) satellite by the European Space Agency (ESA), need to be calibrated and validated with in-situ data, and in-depth information about the snowpack is crucial to characterize penetration into the snow layer in both frequencies. Airborne campaigns alone or in combination with ground measurements (e.g. snow probe surveys) have been carried out previously to validate satellite altimetry measurements. However, a seamless link from ground observations via airborne surveys to satellite observations is limited by differences in range, spatial coverage and footprint size, as well as different sensors. Ground data also seldom cover any thin or deformed ice areas. Moreover, also information about snow density on Arctic sea-ice is sparse. Therefore, new methods to retrieve accurate but spatially representative measurements of snow depth and density are urgently required. Here we present a measurement system to fill the gap between ground measurements and aircraft observations of snow on sea ice. The presented unmanned aerial vehicle system carries an ultra-wideband radar and can obtain information about the snow layer on sea ice to complement future satellite calibration/validation activities, including measurements of snow depth and potentially snow density. In addition, it can support future research studies and field campaigns that benefit from this mobile and flexible system. To demonstrate the capability of the drone-based snow radar, we present first results over Arctic sea ice during spring 2021.
Bin Cheng, Timo Vihma, Anna Kontu, Fei Zheng, Yubao Qiu, Annette Rink, Yubing Cheng
Corresponding author: Bin Cheng
Corresponding author e-mail: bin.cheng@fmi.fi
Boreal lakes in the high Arctic represent an important component of the Arctic environmental system. Lakes can adjust the local climate and affect the environment through interactions among physical, hydrological, biological and chemical processes. The strongest effects of climate change are felt in the lake surface temperature and lake ice phenology. The ice cover duration and the growth processes of lake ice are important for understanding the local and regional winter climate. On a large scale, it has been concluded that lake ice season is getting shorter and lake ice is getting thinner. In fact, the physical and biochemical processes in different Arctic lakes ice could be used as a proxy reference to support the Arctic process studies across the temporal and spatial scales. A sustainable snow–ice observation program has been based in Lake Orajärvi, northern Finland since 2009. Usually, the lake ice season lasts up to 6 months. The average seasonal ice thermodynamic growth reaches 60–70 cm before the onset of melting. For winter 2019/20, we observed extraordinary lake ice composition. The seasonal maximum lake ice reached 68 cm before the melt onset. The ice core revealed that 80% of lake ice was granular ice and only 20% was columnar ice. We investigate the climate factors and local weather conditions predisposing to such extreme lake ice composition. A thermodynamic snow and ice model was applied to simulate the ice mass balance. We concluded that extreme seasonal snow accumulation was the primary driving factor for creating extreme seasonal granular ice formation. Early ice formation, the largest number of snowfall episodes, and the strongest seasonal (JFM) Arctic Oscillation since 2000 were the driving factors resulting in extreme seasonal lake ice composition. The thermodynamic evolution of the Arctic landfast sea ice is the same as Arctic lake ice. Extreme snow may possibly result in extreme seasonal Arctic landfast sea ice composition in future.
Alice Carret, Sara Fleury, Jérôme Bouffard, Alessandro di Bella, Florent Garnier, Antoine Laforge
Corresponding author: Alice Carret
Corresponding author e-mail: alice.carret@legos.obs-mip.fr
For more than 10 years, CryoSat-2 (CS2) has been observing and monitoring the polar regions, providing unprecedented spatial and temporal coverage. Satellite altimetry allows the measurement of sea ice thickness, a key variable for understanding sea ice dynamics. Many products developed by the community have already demonstrated the capabilities of CryoSat-2 to estimate sea ice thickness. Nevertheless, several questions remain to better assess the relevance and quality of the measurements according to the ice type. These include the effects of ice roughness in the footprint and Ku frequency penetration levels in the snow cover. In July 2020, CS2’s orbit was raised, as part of the CRYO2ICE project, to have tracks co-located with NASA’s high-resolution IceSat-2 altimeter over the Arctic Ocean. These coincident measurements between the Ku-band SAR altimeter for CS2 and the LIDAR altimeter for IceSat-2 provide a unique means of assessing the impact of radar footprints and snow properties in the measurements. Here we present a snow depth product from IceSat-2 and CryoSat-2 over the IceSat-2 period. This product is also available only for the colocated tracks of the CRYO2ICE project. We compared this product to other snow depth datasets obtained from in situ data, radiometry, altimetry, models, airborne measurements and climatologies. The comparisons show strong correlations, highlighting the reliability of our product. We also focus on the added value of the CRYO2ICE project by investigating the possibility and the advantage of using high-frequency snow depth for sea ice retrieval compared with gridded products. We also use the SARAL mission and its Ka-Band altimeter to investigate the surface roughness contribution on our product. Finally we propose a correction to account for the effect of surface roughness to better understand penetration into snow at different frequencies.
Ice crystal growth in different environments: an approach from micro to macro scales
Bernd Kutschan, Silke Thoms, Andrea Thom, Tim Ricken
Corresponding author: Bernd Kutschan
Corresponding author e-mail: bernd.kutschan@awi.de
Starting from a small-scale level we consider snowflakes and other natural ice crystals which are created under different environmental conditions. They are out-of-equilibrium growth shapes and these are the result of a nonlinear growth dynamics and a variational principle. A special role during the pattern formation is played by kink solutions that represent the different state of affairs at the phase boundaries. The mechanisms of kink formation give an insight into the dynamics of phase transitions. In this sense the phase field model of Kobayashi describes the shape of ice crystals due to supercooling and the strength of anisotropy. In addition, the impact of salt on the growth process is considered. This pattern formation is different from a reaction–diffusion system according to Alan Turing and the earlier thermodynamic approaches. We modify Kobayashi’s phase field model and supplement with the influence of salt in order to describe a fine network of microscopic brine channels and cavities filled with brine that are formed during the freezing process in sea ice. The phase transition at the microscopic level, which leads to the formation of brine channels, is coupled to a phenomenological approach, the ‘theory of porous media’ (TPM), on the macro scale driven by the divergence of heat flux. The aim of these studies is to gain insight into the small-scale coupled physical processes of freezing and melting sea ice and their connections to the size and distribution of the enclosed brine channels.
Seasonality of spectral radiative fluxes and optical properties of Arctic sea ice
Marcel Nicolaus, Christian Katlein, Philipp Anhaus, Mario Hoppmann, Gunnar Spreen, Hannah Niehaus, Evelyn Jäkel, Manfred Wendisch, Christian Haas, Ran Tao
Corresponding author: Ran Tao
Corresponding author e-mail: ran.tao@awi.de
The solar partitioning of sea ice is important for physical and biological processes in the ice-covered Arctic ocean and atmosphere. Here, we analyse data from autonomous drifting stations to investigate the seasonal evolution of the spectral albedo, transmittance and absorptance for different sea ice, snow and surface conditions as measured during the MOSAiC expedition in 2020. We find that the spatial variability of these quantities was small during spring, and that it strongly increased after melt onset on 26 May, when the liquid water presence on the surface increased. The enhanced variability was then mostly determined by the formation of melt ponds, which increased the total energy absorption of the sea ice by 50% compared to adjacent bare ice. The temporal evolution of surface albedo and sea ice transmittance was mostly event-driven and thus neither continuous nor linear. However, absorptivity and transmittance showed strong variabiliy, which depended on internal sea ice optical properties and under-ice biological processes, not only on surface conditions. The heterogeneity of sea ice conditions strongly impacted the partitioning of the solar short-wave radiation. Thus, this study shows that the evolution of melt ponds determines the total (summer) heat deposition and sea ice melt much more than the melt onset date. The small-scale heterogeneity and the timing and duration of ponding events have to be considered when comparing (local) in-situ observations with large-scale data sets, as well as for improvements in numerical models.
Sea-ice decline makes zooplankton stay deeper for longer
Hauke Flores, Gaelle Veyssière, Giulia Castellani, Jeremy Wilkinson, Mario Hoppmann, Michael Karcher, Lovro Valcic, Astrid Cornils, Maxime Geoffroy, Marcel Nicolaus, Barbara Niehoff, Pierre Priou, Katrin Schmidt, Julienne Stroeve
Corresponding author: Hauke Flores
Corresponding author e-mail: hauke.flores@awi.de
As Arctic sea ice deteriorates, more light enters the Arctic Ocean, causing largely unknown effects on the ecosystem. A novel autonomous bio-physical observatory provided the first record of the vertical distribution of zooplankton under sea ice drifting across the Arctic Ocean from dusk to dawn of the polar night. Its measurements revealed that zooplankton ascend into the under-ice layer during autumn twilight, following a consistent trigger isolume. We applied this trigger isolume to IPCC models enabled to incorporate incoming radiation after sunset and before sunrise of the polar night. The models project that, in about three decades, the total time spent by zooplankton in the under-ice layer will be reduced by up to one month, depending on geographic region. This will impact zooplankton winter survival, the Arctic foodweb, and carbon and nutrient fluxes. These findings highlight the importance of processes in the twilight periods for predicting change in high-latitude ecosystems.
Modeling the seasonal evolution of the ice thickness distribution along the MOSAiC drift
Florent Birrien, Frank Kauker, Luisa von Albedyll, Valentin Ludwig, Kirstin Schulz, Helge Goessling, Michael Karcher
Corresponding author: Frank Kauker
Corresponding author e-mail: frank.kauker@awi.de
The single-column sea ice model ICEPACK (CICE consortium) was adapted to simulate the evolution of the ice thickness distribution (ITD) along the MOSAiC drift. This Lagrangian approach allows full exploitation of the extensive observational data on sea ice and snow collected during the MOSAiC expedition. The model is initialized with observed ITDs (derived from airborne electromagnetic thickness measurements) with 10 cm thick bins, which provide an accurate and representative initial state of the sea ice. The model is then driven by atmospheric (re)analyses (NCEP/CFSv2 or ERA5) and with prescribed snow cover (derived from SIMBA buoys), observed ocean conditions and deformation fields derived from buoy arrays of the distributed network to investigate the thermodynamic (growth/melting) and dynamic (bulging) response of sea ice along the track. Here we will present the Lagrangian framework and a comparison between simulated and observed ITDs, and evaluate the performance of the model in describing sea ice evolution during the MOSAiC winter period. Special attention will be given to ocean forcing, which proved to be conceptually difficult to implement. Vertical heat fluxes at the interface of the mixed layer as well as the temperature and salinity of the mixed layer calculated or collected during MOSAiC are used to determine the lower boundary layer of ICEPACK. Different implementations are described and their implications for sea ice development are discussed briefly.
Mapping Arctic sea ice surface roughness with multi-angle imaging spectroradiometry and ICESat-II
Thomas Johnson, Michel Tsamados, Jan-Peter Muller, Julienne Stroeve
Corresponding author: Thomas Johnson
Corresponding author e-mail: thomas.johnson.17@ucl.ac.uk
Sea ice surface roughness (SIR) is a crucial parameter in many ocean and climate studies, constraining the transfer of heat and momentum at the air–ice interface, providing preconditioning for the distribution of melt ponds and snow layers, with near-real-time applications for navigational purposes, while also closely related to ice age. High-resolution roughness estimates from airborne laser measurements are limited in spatial and temporal coverage while pan-Arctic satellite roughness has remained elusive and does not extend over multi-decadal time-scales. Launched in 1999, the MISR (multi-angle imaging spectroradiometer) instrument acquires optical imagery at 275 m (red channel) and 1.1 km (all channels) resolutions from nine near-simultaneous camera view zenith angles sampling specular anisotropy. This work extends on previous works to model SIR from MISR sampling of specular anisotropy. Our approach uses calibration of angular reflectance signatures with estimates of SIR derived from coincident laser altimetry data from the ICESat-II mission. This enables; removal of harsh seasonal temporal constraints, more extensive ability in investigation of feature-length scale dependence on surface roughness, in addition to greater certainty in identification of cloud-free data compared with previous IceBridge-related work. Surface roughness, defined as the standard deviation of the within-pixel elevations to a best-fit plane, is modelled using several machine learning regression techniques and product performance is assessed with independent validation. We present an independently validated novel SIR product with potential for a near real time processing chain.
Light availability and variability over and under the Arctic sea ice
Ran Tao, Marcel Nicolaus, Christian Katlein, Philipp Anhaus, Maddie Smith, Bonnie Light, Niels Fuchs, Niels Fuchs, Niklas Neckel, Christian Haas
Corresponding author: Ran Tao
Corresponding author e-mail: ran.tao@awi.de
The availability of sunlight on and under the Arctic sea ice controls many physical and biological processes. Solar energy contributes to sea ice thermodynamic melt, and shapes habitat conditions. Due to the harsh climate and logistical limitations, up to now it has been difficult to compose a long-term dataset describing the seasonality of collocated surface albedo and under-ice transmittance over an integrated area. Here, we show the temporal evolution and spatial distribution of light over and under sea ice during the MOSAiC expedition from May–September 2020. Albedo was estimated from surface images collected by helicopter and drone flights, and under-ice transmittance was mapped with a remotely operated vehicle, covering in total an approximately 150 m grid area. We compare the estimated albedo to in-situ observations, apply it to classified surface types, and then investigate its spatial variability and impact on the surface net influx of solar irradiance. We present measurements of light transmittance before melt onset, during the melt season, and during freeze-up in the Central Arctic. By combining both albedo and transmittance, we are able to determine the solar partitioning of various ice and surface types, quantifying the amount of energy being absorbed by the sea ice. This study provides a comprehensive view of light availability in and under sea ice, and highlights the importance of spatial heterogeneity forthe large-scale energy budget.
Thomas Lavergne, Atle Sørensen, Rasmus Tonboe, Courtenay Strong, Matilde Kreiner, Roberto Saldo, Anton Birkedal, Fabrizio Baordo, Trygve Aspenes, Steinar Eastwood
Corresponding author: Thomas Lavergne
Corresponding author e-mail: thomas.lavergne@met.no
The 40+ years long time-series of sea-ice extent (SIE) and area (SIA) are headline indicators of climate change. The interested public follows their seasonal evolution and record low and high values on online trackers, and climate scientists benchmark their model systems against them. These climate indicators are based on multi-mission data records of sea-ice concentration (SIC), themselves derived from brightness temperature measurements by passive microwave missions since the 1970s. Over the past few years, we conducted a coordinated R&D effort from the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) and the ESA Climate Change Initiative (CCI) programme. It has resulted in a collection of state-of-the-art sea-ice concentration climate data records and their operational extensions. Version 3 of this data was released in 2022 and was successfully transferred to the Copernicus Marine (CMEMS) and Climate Change Service (C3S). The previous version (released in 2017) informed the IPCC Assessment Report 6 cycle, and is used in the C3S reanalyses. We introduce the latest version of these SIC CDRs. We present key elements of the algorithm baseline as well as characteristics of the products. The algorithm baseline was designed to ensure climate consistency across the satellite missions, and to avoid potential artificial trends in the input and auxiliary data. The algorithms include 1) dynamical tuning of the algorithms and their tie-points, 2) reduction of the retrieval uncertainties using radiative transfer models, and 3) per-pixel uncertainties. Specific R&D during CCI+ project led to an improved spatial resolution of the SIC data record, exploiting the near-90 GHz imagery channels available since the early 1990s. The product files are designed with several user communities in mind, and allow, e.g., accessing more ‘raw’ SIC data (before the last filters are applied) for easing validation and data assimilation. We finally present results from an evaluation of our SIC records and a comparison to those from other data providers. This work was supported by the EUMETSAT OSI SAF and ESA CCI+ Sea Ice projects.
CryoSat: mission status, science, and future challenges over the ice-covered oceans
Alessandro di Bella, Jerome Bouffard, Tommaso Parrinello
Corresponding author: Alessandro di Bella
Corresponding author e-mail: alessandro.di.bella@ext.esa.int
Launched in 2010, the European Space Agency’s (ESA) CryoSat mission was the first polar-orbiting satellite flying a SAR interferometric altimeter dedicated to the cryosphere, with the objective of monitoring precise changes in the thickness of polar ice sheets and floating sea ice. After 13 years in orbit, CryoSat remains one of the most innovative radar altimeters in space and continues to deliver high-quality data, providing unique contributions to several Earth Science and applications domains. Numerous CryoSat-based studies have been carried out over the last decade to optimize sea ice processing algorithms. These innovations have been transposed into an operational framework to generate new thematic products, so-called ‘Cryo-TEMPO Sea Ice’, enriching the CryoSat data portfolio and enabling the full scientific and operational exploitation of CryoSat data. In summer 2020, CryoSat’s orbit was changed to periodically align it with that of NASA’s ICESat-2 to allow collocated radar and lidar measurements of the same ice at nearly the same time. The new orbit configuration, called CRYO2ICE, provides valuable data enabling scientists to investigate how dual-frequency data can be combined to retrieve snow depth, one of the largest sources of uncertainty in altimetry-based sea ice thickness estimates, and to prepare for the upcoming Copernicus CRISTAL mission, which will provide coincident measurements at Ka and Ku bands. CryoSat is expected to be extended until the end of 2025 with the scope to achieve new important objectives, to extend the synergy with other missions and integration into sea ice models as well as to secure a unique long-term climate record at high latitude. The scope of this presentation is to describe the current mission status, show its main scientific achievements and present future R&D challenges over the Arctic and Antarctic ice-covered oceans. We will also provide an overview of recent product evolutions and new science results which are paving the way for the development of the CRISTAL Sentinel Expansion mission.
Adding the third dimension to recent Antarctic sea ice extent variability
Isobel Lawrence, Andrew Shepherd, Jeremy Wilkinson, Paul Holland, DEFIANT Team
Corresponding author: Isobel Lawrence
Corresponding author e-mail: isobel.lawrence@esa.int
Southern Ocean sea ice has undergone dramatic losses in extent in recent years, this year reaching a record (40-year) low of 1.91 million square kilometres in early February, weeks before its minimum annual extent. These drastic losses have garnered much attention from the scientific community and the media, but for the moment our understanding of these events remains two-dimensional because observations of sea ice thickness and volume are limited. Were changes in extent caused by increased convergence of the sea ice pack with a little overall change in volume? or did thermodynamic forcing during low-extent years promote thinner ice more prone to summer melt? Here we utilize data from the ESA CryoSat-2 and Copernicus Sentinel-3 radar altimetry missions, combining satellite radar freeboard with a newly developed snow-on-Antarctic-sea-ice model to derive circumpolar sea ice thickness and volume from 2011–23. We assess the variability in sea ice thickness in the run-up to the February minimum, focussing on the difference between below-average and above-average extent years to ascertain if low summer extent was facilitated by a thinner winter-spring ice pack. Using sea ice concentration and motion data, we then decompose monthly and weekly sea ice thickness changes into dynamic and thermodynamic components to understand the principal driving mechanisms behind sea ice thickness variability between 2011 and 2023, and the dramatic extent losses of 2017, 2022 and 2023. This work forms part of the NERC DEFIANT project, which combines new in-situ and satellite data sets with advanced modelling techniques to better understand the drivers and effects of Antarctic sea ice variability.
Prediction of sea ice conditions using Sentinel-1 imagery and sea ice drift forecast
Anna Telegina, Denis Demchev
Corresponding author: Anna Telegina
Corresponding author e-mail: anna.telegina@uit.no
Short-term (meaning a few hours to days) forecasts of detailed sea ice conditions are often mentioned as one of the most important products which navigators in sea ice infested waters lack. It is especially relevant considering current acceleration in growth of activities in the Arctic. The goal of this research is to combine the most popular in operational use synthetic aperture radar (SAR) images from space and products derived therefrom with modelled drift data to develop a methodology of forecasting sea ice conditions. Results of experiment will be presented where modelled drift fields are used for prediction of ice conditions based on input SAR image and warping algorithm developed at Chalmers University of Technology. For modelled drift data the Barents-2.5 model is used. This is a coupled ocean and sea ice model covering the Barents Sea and areas around Svalbard and MET Norway’s main forecasting model for sea ice in the Barents Sea. Predicted sea ice conditions and sea ice drift field will be compared with consequent SAR image and drift information from an algorithm for sea ice drift retrieval based on two SAR images. Such problems as effect of deformation on short-term forecast as well as reliability of different sea ice types and conditions together with model accuracy will be discussed.
Drivers of extreme summer Arctic sea ice reductions with rare event simulation methods
Jerome Sauer, Francesco Ragone, François Massonnet, Jonathan Demaeyer, Giuseppe Zappa
Corresponding author: Jerome Sauer
Corresponding author e-mail: jerome.sauer@uclouvain.be
Various studies have identified possible drivers of extreme Arctic sea ice reductions such as were observed in the summers of 2007 and 2012, including preconditioning, feedback mechanisms, oceanic heat transport and the atmospheric circulation. However, a quantitative statistical analysis of these drivers and a better understanding of the seasonal predictability of such events are hindered by poor sampling of extreme events from observations and from numerical simulations. Recent studies have tackled the problem of sampling extreme events in climate models by using rare event algorithms, computational techniques originally developed in statistical physics, to reduce the computational cost required to sample rare events in numerical simulations. In this work, we apply a rare event algorithm to the intermediate complexity coupled climate model Planet Simulator (PlaSim) to investigate extreme negative summer and September pan-Arctic sea ice area anomalies under fixed pre-industrial greenhouse gas conditions. By using the rare event algorithm, we guide ensemble simulations to oversample rare dynamical trajectories characterized by extreme negative sea ice area anomalies on average over summer and during September. In this way, we are able to perform composite analyses of dynamical quantities conditional on these events at a smaller statistical uncertainty than with conventional simulation strategies, and we have access to ultra-rare events that are very unlikely to be observed in conventional climate model simulations. We exploit the improved statistics of extreme negative summer and September pan-Arctic sea ice area anomalies to study precursors of these events, including a surface energy budget analysis to disentangle oceanic and atmospheric forcing on the sea ice. We also investigate the links between extreme negative sea ice area anomalies and the dominant modes of atmospheric circulation variability, as well as between the extremes and preconditioning through the winter–spring sea ice state. The project is currently funded by a Seedfund grant given to Professor Francesco Ragone, a Fedtwin academic at the Catholic University of Louvain and at the Royal Meteorological Institute, Belgium.
Seasonal and regional sensitivity of Arctic sea ice
Markus Ritschel, Dirk Notz
Corresponding author: Markus Ritschel
Corresponding author e-mail: markus.ritschel@uni-hamburg.de
We examine the seasonal and regional evolution of sea-ice coverage in the Arctic in response to changes in the forcing. Using satellite and reanalysis data in combination with CMIP6 model simulations, we build on previous studies that have found a linear relationship between September sea-ice area of the northern hemisphere and global atmospheric air temperature (TAS) as well as anthropogenic CO2 emissions. Instead of focusing on the whole Arctic and September sea ice only, we perform sensitivity analyses on higher-resolution regional and seasonal scales, aiming to identify the atmospheric and oceanic drivers that govern the evolution of sea-ice coverage on these scales and derive simple empirical relationships that describe the impact of these processes. We find clear linkages also on these higher-resolution scales, with different regions and different seasons showing diverse sensitivities of sea-ice area evolution with respect to TAS and anthropogenic CO2. Furthermore, we use a multivariate metric to quantify a single simulation matching the observations, thus considering the different sensitivities of all seasons of the year. Building the combined covariance matrix of observations and simulations as a measure of the joint uncertainties, we can determine how close to the observations every single member of the simulations is. This allows us to separate models whose sensitivities are in overall good agreement with the observations from those that are apparently not capable of properly simulating the response of the sea ice to the forcing throughout all months. Based on our findings we can infer the dominant drivers that force Arctic sea-ice evolution on a regional and seasonal scale and also derive projections for the future evolution of Arctic sea ice for different climate scenarios based on simple empirical relationships that can directly be estimated from observational records.
Sea ice growth, melt and dynamics in an increasingly marginal Arctic
Rebecca Frew, Danny Feltham, David Schroeder, Adam Bateson
Corresponding author: Rebecca Frew
Corresponding author e-mail: rebecca.frew@reading.ac.uk
As summer Arctic sea ice extent has retreated, the marginal ice zone (MIZ) has been widening and making up an increasing percentage of the summer Arctic sea ice. The MIZ is defined as the region of the ice cover that is influenced by waves, and for convenience here is defined as the region of the ice cover between ice concentrations of 15–80%. The MIZ is projected to become a larger percentage of the summer ice cover as the Arctic transitions to ice-free summers. We compare the processes of ice volume gain and loss in the ice pack to those in the MIZ to establish and contrast the relative importance of processes in the pack and MIZ, and the changes as the summer MIZ fraction and amplitude of the seasonal sea ice growth/melt cycle increases. We use an atmosphere-forced, physics-rich sea-ice–mixed-layer model that includes a prognostic floe size distribution (FSD) model including brittle fracture and form drag. The model has been compared to FSD observations, satellite observation of sea ice extent and PIOMAS. We find that the fraction of the July sea ice cover that is MIZ increases from 14% (20%) in the 1980s to 46% (50%) in the 2010s in the NCEP (HadGEM2-ES) atmosphere-forced simulations. In the HadGEM2-ES forced projection, the July sea ice cover is almost entirely MIZ (93%) in the 2040s. The percentage of melting that is top melt is half as much in the MIZ compared to in the pack ice, whilst the proportion of melting that is lateral melt is twice as high in the MIZ. In the region that becomes MIZ in the 2010s peak melting shifts 20 (12) days earlier in the NCEP (HadGEM2-ES) forced simulations relative to the 1980s. This continues in the projection where peak melting in the region that becomes MIZ in the 2040s shifts 14 days earlier relative to the 2010s.
Salinity, temperature, and δ18O: making sense of the record in sea ice
Aura Diaz, Tim Papakyriakou, Jens Ehn
Corresponding author: Aura Diaz
Corresponding author e-mail: umdiaza@myumanitoba.ca
Sea ice is a direct manifestation of the interaction between atmospheric and hydrographic processes. Its bulk properties, such as temperature, salinity, and oxygen isotopic composition (δ18O), are a function of these processes and can, therefore, be interpreted as a record of the conditions that prevailed during its formation. Here, we present data from three case studies on landfast sea ice which include both ice core data, atmospheric and hydrographic observations over spatial or temporal gradients: 1) distance from river mouth providing a gradient in under-ice freshwater content; 2) distances from polynya and flaw lead with significant ice formation; and 3) time-series exploring changes in bulk ice properties and upper water column. Our datasets suggest that local processes play a key role in defining the spatial variability of sea ice and demonstrate the linkages between formation environment, under-ice processes, and ice properties. In addition, our results illustrate how ice core data can be used as an alternative approach to derive the under-ice conditions associated with the thermodynamic growth and melt.
Arctic and Antarctic sea ice thickness and volume changes during the last 29 years from satellites
Marion Bocquet, Sara Fleury, Frédérique Rémy, Camille Boulard, Fanny Piras
Corresponding author: Marion Bocquet
Corresponding author e-mail: marion.bocquet@legos.obs-mip.fr
Both Arctic and Antarctic sea ice are undergoing deep changes in response to climate change. Whereas Arctic sea ice is thinning and seasonal ice is taking over, Antarctic sea ice global changes are not as clearly understood. While sea ice extent and area are well described with observations during the last four decades, sea ice thickness and volumes changes remain poorly known. However, thickness is a key variable to fully understand the past, present and future changes of sea ice. Despite improvements in sea ice thickness estimation from altimetry during the past few years thanks to SAR and laser altimetry, former radar altimetry missions such as Envisat and especially ERS-1 and ERS-2 have remained under exploited so far. ERS-2 Arctic sea ice thickness has been recently retrieved thanks to a machine learning approach aiming at calibrating ERS-2 and Envisat against CryoSat-2. We are now able to extend our estimations to ERS-1 for both polar oceans, allowing us to propose a 29-year-long series of monthly sea ice thickness and volume time. An uncertainty budget is derived from a Monte Carlo methodology. Nearly 30 years of sea ice volume time series reveals that Arctic sea ice is melting by 120 ± 45 km3 a –1 up to 81.5° N (–13.1 ± 5.1% per decade). Antarctic sea ice evolution show no significant trends along the whole period, but a volume change is observed since 2016. For both hemispheres, prominent regional changes have been identified, with a strong heterogeneity of trends across regions. A focus will be made on the latest three-decades’ time series of Antarctic sea ice thickness, especially on regional studies and temporal mode decomposition in relation to climate oscillations. This work is funded by a CNES/CLS PhD scholarship and supported by ESA in the framework of FDR4ALT project.
The Churchill Marine Observatory: a new hub for Arctic system studies
Feiyue Wang, C.J. Mundy
Corresponding author: Feiyue Wang
Corresponding author e-mail: feiyue.wang@umanitoba.ca
Dr David Barber was a champion of Arctic system science. He fully recognized that the dynamic and complex physical, biogeochemical, ecological and socioeconomic processes of a changing Arctic could only be addressed by a systems approach crossing disciplines, sectors and knowledge systems. One of the best examples of Dr Barber’s vision and approach is the Churchill Marine Observatory (CMO), which was one of the last projects he led before his untimely death in 2022. Under his leadership, the CMO was conceptualized in the 2000s with a large number of partners from academia, government, industry and most importantly the local community of Churchill, Manitoba. The development, construction started in 2017, and the facility has been partially operational since 2020. The goal of the CMO is to directly address technological, scientific and socioeconomic issues pertaining to climate change, marine transportation and resource development throughout the Arctic. The CMO comprises the Ocean–Sea Ice–Mesocosm (OSIM) facility and the Environmental Observatory (EO) system. The OSIM facility is located in Churchill off the west coast of Hudson Bay, featuring two identical outdoor seawater/sea ice pools with a moveable roof, an atmospheric monitoring station and two on-site laboratories. The purpose is to allow controlled mesocosm experiments for process-oriented studies of the ocean–sea-ice–atmosphere interface, with a special focus on issues related to emerging northern contaminants (e.g. oil spills from marine shipping) and freshwater-marine coupling. The EO system contains a network of four moorings, a cabled observatory in Churchill, and the coastal research vessel R/V William Kennedy to permit scaling of process studies conducted at the OSIM facility, support oceanographic investigations and quantify potential impacts from shipping and other economic development activities across Hudson Bay. In this presentation, we provide an update of the development status and research activities at the CMO, highlighting Dr Barber’s vision of using the CMO as a hub for Arctic system studies, and how that vision has already started to become a reality.
Yellow pancakes: sea ice super bloom in the south-eastern Weddell Sea
Ilka Peeken, Lena Eggers, Stefanie Arndt, Mara Neudert, Karley Campbell, Benoit Lebreton, Clara Flintrop, Susan Henkel, Moritz Holtappel, Florian Koch, Andreas Rogge, Alison Schaap, Markus Janout, Mariana Altenburg Soppa, Astrid Bracher, Christian Haas
Corresponding author: Ilka Peeken
Corresponding author e-mail: ilka.peeken@awi.de
The Weddell Sea (WS) hosts a diverse ecosystem that is highly dependent on carbon production associated with sea ice. Nearly 50% of the annual primary production of Antarctic sea ice is generated in the Weddell Sea, and the eastern margin in particular is one of the most productive regions. Here we report on the opportunistic sampling of a remarkable sea ice super bloom in the southeastern Weddell Sea in March 2021. It was carried out as part of an interdisciplinary study of ocean-ice-biology properties and interactions aboard the German icebreaker RV Polarstern. During the cruise, we observed overall low sea ice concentrations in this region, although environmental conditions were characterized by near-freezing temperatures and newly formed sea ice was prevalent throughout the sampling region. In early March, when air temperatures had temporarily dropped to –10°C with strong winds, we encountered an unusual, vast field of intensively yellow pancake ice at 76° S, 30.3° W that changed in colour from yellow to amber over the next few days, covering almost 100% of the surface. Ad hoc sampling of this pancake ice revealed extremely high biomass accumulation with an average chlorophyll a of 125 mg m–3 and an unusual complete depletion of the macronutrient nitrate within the pancake ice. Especially at the beginning of this bloom, a clear separation was observed between the yellow surface, which consisted mainly of a Phaeocystis species, and the bottom community, which consisted mainly of Fragilariopsis species also found in other sea ice cores. In addition, large bands of slush ice with maximum chlorophyll concentrations of 50 mg m –3 were found, especially near the coast, which consisted mainly of a mixture of both species. Here we will present the spatial extent of the bloom, the potential contribution to primary production and carbon export, and possible explanations for its occurrence. We will also discuss the role of such super blooms for a rapidly changing Antarctic sea ice scape.
Novel methods for assessment of sea ice cover from SAR-derived deformation
Polona Itkin
Corresponding author: Polona Itkin
Corresponding author e-mail: polona.itkin@uit.no
Here we present two novel methods to assess sea ice deformation in remote sensing and potentially in numerical models. The presented case is based on displacements between Sentinel-1 synthetic aperture radar (SAR) image pairs to detect deformation rates at 300 m resolution. The first method is used to characterize the evolution of the ice cover. The displacements and deformation strain rates are used to track parcels of sea ice throughout the winter ice pack. This enables new observations such as detection of re-activation of the linear kinematic features (LKFs) and the evolution of pack ice from relatively level ice during freeze up into a highly deformed state in spring. The second method is used to characterize the transient statistical properties of sea ice. Winter pack ice is divided into coherently moving clusters of ice plates – coherent deformation elements (CDE), that move along LKFs. Geometrical properties of CDE such as count, area, roundness and fragmentation can be used to describe the state of the ice cover. We apply the methods to the winter collection of Sentinel-1 SAR imagery available over the MOSAiC campaign. Our results show continuously active winter sea ice cover and its fracturization at strongest synoptic events. We also observe regularly distributed LKFs (damaged sea ice) that are seemingly independent of sea ice thickness and age. Some damaged areas are reactivated in temporally distant deformation events.
Inga J. Smith, Greg H. Leonard, Maren E. Richter, Kate E. Turner, Maddy S. Whittaker, Wolfgang Rack, Alexander D. Fraser, Jan L. Lieser
Corresponding author: Inga J. Smith
Corresponding author e-mail: inga.smith@otago.ac.nz
Land-fast sea ice is an important part of Antarctic physical and ecological systems, influencing ice tongue and ice shelf stability, water mass properties and ecosystem productivity. The distribution of fast ice has previously been shown to be strong linked to coastal polynya size. McMurdo Sound has had an established pattern of fast-ice break out from January to February followed by initial formation from March onwards, with period break-outs due to strong winds. Generally by April or May, a stable fast-ice cover has formed in the southern part of McMurdo Sound. In 2019, a stable fast-ice cover formed unusually late due to repeated break-out events. Here we analyse the 2019 sea-ice conditions and relate them to a modified storm index (MSI), a proxy for southerly wind events. We determined there is a strong correlation between the timing of break-out events and several unusually large MSI events and our key finding is that an increase in the frequency of intense winter storms in 2019 resulted in a delayed formation of a stable fast-ice cover. Further, repeated break-outs of the fast ice during winter 2022 demonstrated that fast-ice conditions in 2019 were not unique and were not even the worst-case scenario. The 2022 situation posed logistical challenges for the New Zealand Antarctic Programme and the United States Antarctic Program. These events suggest that the fate of fast ice in the sound may be a symptom of some larger change. Winter fast-ice dynamics in the sound appear to be largely driven by synoptic events as there are no identifiable trends in monthly averages of atmospheric drivers (e.g. air temperature, mean sea level pressure and wind speed and direction) of fast-ice breakout in the period 1985–2022.
Polona Itkin, Glen Liston
Corresponding author: Polona Itkin
Corresponding author e-mail: polona.itkin@uit.no
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) observations span the entire seasonal cycle of Arctic snow and sea ice cover. However, the measurements of atmospheric and ocean forcing, as well as distributed measurements of snow and ice properties, were occasionally interrupted for logistic reasons. The most prolonged interruption happened during the onset of the summer melt. Here were present a novel modeling tool that can assimilate the relevant observational data to provide continuous high temporal resolution time series of snow and sea ice parameters over the entire annual cycle. We use this tool to analyze differences between the three ice types found in the MOSAiC Central Observatory: relatively deformed second year ice, second year ice with extensive smooth refrozen melt pond surfaces, and first year ice. We demonstrate how, despite different initial conditions, the snow and ice mass balances are similar for all ice types at the end of the accumulation period and throughout the melt period. Finally, we quantify the role of individual synoptic events on controlling local snow sources and sinks, including snow erosion from level ice, and accumulation around pressure ridges and in leads with open water and thin ice.
Clara Flintrop, Jutta Wollenburg, Ilka Peeken, Scarlett Trimborn, Morten Iversen
Corresponding author: Clara Flintrop
Corresponding author e-mail: clara.flintrop@mail.huji.ac.il
Marine carbon cycling is driven by the biological carbon pump, which exports carbon to depth in the form of phytoplankton aggregates (‘marine snow’) and fecal pellets. The sinking velocity of these particles is a determining factor of the strength of the biological carbon pump. Incorporation of ballast minerals increases sinking velocities of marine snow and can increase carbon export by an order of magnitude. The origin of these minerals depends on both season and geographical location. Southern Ocean phytoplankton communities comprise large, heavily silicified diatoms, and biogenic silica is widely considered the main ballasting agent of sinking organic matter in these latitudes. During the Polarstern cruise PS124 in February/March 2021 to the Weddell Sea we collected in-situ formed particles and performed aggregation experiments on water samples comprising diverse phytoplankton assemblages to study the effects of a potential climate change-induced shift from heavily silicified diatoms towards non-ballasted Phaeocystis-dominated communities on carbon export in the Southern Ocean. To our surprise, size-specific sinking velocities were not significantly decreased in aggregates containing high amounts of Phaeocystis relative to diatoms. This could be partly due to differences in aggregate structure, i.e. how densely material was packed. It can also indicate that biogenic silica is not the only ballasting agent, and upon closer inspection we discovered considerable amounts of cryogenic minerals in both laboratory-formed and in situ-collected particles, including gypsum, ikaite and mirabilite. While cryogenic gypsum has been observed to ballast Phaeocystis in the Arctic, the presence of cryogenic minerals has not yet been described in aggregates collected in the Southern Ocean, which could be explained by their sensitivity to changes in temperature, pH and humidity, causing them to rapidly dissolve in the water column. This lability requires targeted sampling approaches and procedures to preserve their structure. Our findings suggest that cryogenic ballasting of settling aggregates plays an important role for carbon export in the Southern Ocean. This research highlights the need to gain a better understanding of the importance of cryogenic ballasting in the Southern Ocean relative to other ballast sources (e.g. diatoms), in order to predict how changes in air/water temperature and carbonate chemistry will alter carbon export in the future.
Improved lead detection with Sentinel-1 SAR images in the Arctic
Dmitrii Murashkin, Gunnar Spreen, Marcus Huntemann
Corresponding author: Dmitrii Murashkin
Corresponding author e-mail: Dmitrii.Murashkin@dlr.de
The Sentinel-1 synthetic aperture radar satellite constellation provides a valuable source of information on sea ice conditions over the Arctic region. It is able to cover a major part of the Arctic Ocean every 3 days with two satellites, which provides an opportunity for fine scale object monitoring on a global scale. Lead distributions in the Arctic are of interest both for shipping as well as climate process like energy and gas exchange between the ocean and atmosphere in ice covered regions. We have previously introduced an algorithm for automatic lead detection with Sentinel-1 SAR images based on grey level co-occurrence matrix and random forest classification. Here we introduce a new method for lead detection based on UNET convolutional neural network. An important part influencing classification result quality is a new preprocessing procedure that provides more consistency between Sentinel-1 scene subswaths, which is especially important for the cross-polarization HV images. We present the results of the new classification on fine scale and Arctic-wide, and compare the new results with those produced with the previously suggested algorithm.
Chemical transport in sea ice: a case study
Max Thomas, Briana Cate, Jack Garnett, Inga J Smith, Crispin Halsall, Martin Vancoppenolle
Corresponding author: Max Thomas
Corresponding author e-mail: max.thomas@otago.ac.nz
We investigate the effect of partial dissolution on the transport of chemicals within sea ice. Physically plausible mechanisms are added to a brine convection model that decouple tracers from convecting brine. The model is evaluated against a recent observational dataset collected in the Roland von Glasow Air-Sea-Ice Chamber. A suite of qualitatively similar chemicals (perfluoroalkyl substances, PFAS) with quantitatively different physico-chemical properties (carbon chain lengths from 4 to 12, partitioning coefficients ranging over several orders of magnitude) were frozen into growing sea ice. When the chemicals are modelled as perfectly dissolved they behave identically to the bulk salinity . The model performs poorly and does not reproduce the concentration of high chain-length PFAS. A simple scheme where PFAS are decoupled from brine salinity by partitioning to a stationary phase as a constant fraction gives better performance, bringing the model into agreement with the observations. A scheme where the decoupling is proportional to the brine salinity performs similarly well. A scheme where the decoupling is proportional to the internal sea-ice surface area performs poorly. All decoupling schemes capture a general enrichment of longer-chained PFAS and can produce concentrations in the uppermost sea-ice layers above that of the underlying water concentration, as observed. Our results show that decoupling from convecting brine can enrich chemical concentrations in growing sea ice and can lead to bulk chemical concentrations greater than that of the liquid from which the sea ice is growing. Brine convection modelling is useful for predicting the dynamics of chemicals with more complex behavior than sea salt, highlighting the potential of these modelling tools for a range biogeochemical research.
Bounded and categorized: data assimilation in a single-column sea-ice model
Molly Wieringa, Cecilia Bitz, Christopher Riedel, Jeffrey Anderson
Corresponding author: Molly Wieringa
Corresponding author e-mail: mmw906@uw.edu
We present a rigorous exploration of the sea ice data assimilation problem using a framework specifically developed for rapid, interpretable hypothesis testing. By coupling a single-column sea ice model to the Data Assimilation Research Testbed (DART), we explore the grid-cell response of complex sea ice models to adjustments made by a combination of data assimilation algorithms. We are particularly interested in understanding behavior related to the model’s ice-thickness distribution (ITD), as well as the bounded nature of both state and prognostic variables in the sea ice model. We find that assimilating with algorithms that respect boundedness does not necessarily improve the accuracy of the analysis but does minimize non-physical adjustments and lessens the need for post-processing. We also find that assimilating observations of the ITD directly notably improves the analysis across state variables when compared to assimilating aggregate quantities such as mean sea ice thickness or sea ice concentration. The full details of these results elucidate many of the positive and negative findings of previous sea ice data assimilation studies and tackle several challenges intrinsic to assimilating observations of a bounded material in which relationships between variables are non-linear. We anticipate that the insights gained from this work will facilitate better future sea ice reanalysis products.
Future response of Antarctic continental shelf properties to ice sheet melting and calving
Max Thomas, Jeff Ridley, Inga J Smith, David P Stevens, Paul R Holland, Shona Mackie
Corresponding author: Max Thomas
Corresponding author e-mail: max.thomas@otago.ac.nz
We present coupled climate model results investigating the impact of Antarctic freshwater forcing on continental shelf temperature and sea-ice cover. The model was forced with the SSP5-8.5 scenario and an uncoupled projection of basal melt and calving fluxes. SSP5-8.5 forcing with fixed pre-industrial freshwater forcing warms all continental shelves, such that historically ‘cold’ and ‘fresh’ shelves transition to ‘warm’. Additional freshwater cools the surface ocean, increasing sea-ice area significantly relative to SSP5-8.5 with fixed, pre-industrial freshwater forcing. Additional freshwater drives regionally varying feedbacks on subsurface continental shelf ocean temperatures. The Eastern Ross, Amundsen and Bellingshausen seas cool in response to freshwater, suggesting a negative feedback on basal melt. From the Weddell Sea to the Western Ross Sea – where continental shelves transition to ‘warm’ – fresh water increases temperatures at the continental shelf base, suggesting a positive feedback.
Uptake and fate of polycyclic aromatic hydrocarbons in experimental sea ice
Kasia Polcwiartek, Gary A. Stern, Feiyue Wang
Corresponding author: Kasia Polcwiartek
Corresponding author e-mail: polcwika@myumanitoba.ca
Over the past 30 years, decreases in Arctic sea ice extent and thickness have led to longer open-water seasons. This has resulted in increased Arctic ship traffic and other industrial activities and thus the risk of fuel and crude oil spills. Polycyclic aromatic hydrocarbons (PAHs) are among the most toxic substances in oil; however, few studies have examined their distribution and fate across the ocean–sea-ice–atmosphere (OSA) interface and their further fractionation between liquid and particulate fractions in ice, which is critical for PAH toxicity assessment. This study investigates the distribution of PAHs across the OSA interface and their partitioning between the liquid and particulate fractions in sea ice grown at the Sea-ice Environmental Research Facility at the University of Manitoba. The experiment was carried out from 24 February–16 March 2020, in six microcosms (240 L each) filled with artificial seawater. A mixed solution of naphthalene (NAP), phenanthrene (PHEN), pyrene (PYR) and benzo(a)pyrene (BaPYR) was injected under the sea ice in each of the microcosm when the ice thickness reached 10 cm. Bulk sea ice and water samples were collected 2, 5, 9, 14 and 19 days following the PAH injection. Water and melted ice samples were analyzed for PAHs and other parameters. Our results indicate that a fraction of each compound introduced under the actively growing sea ice layer was immediately entrained in the ice. We have also observed the migration of PAHs through the ice cover and their subsequent evaporation to the atmosphere. By the end of the experiment, up to 58%, 17%, 5% and less than 1% of NAP, PHEN, PYR and BaPYR, respectively, evaporated to the atmosphere. In comparison, these compounds were present in the sea ice layer in the following amounts: 2%, 6%, 9% and 35%, respectively. Our data further show that at the end of the experiment up to 2%, 13%, 56% and 93% of the total amount of NAP, PHEN, PYR, and BaPYR found in the ice, respectively, were present in the particulate phase. The remaining 98%, 87%, 44% and 7% of each compound, respectively, were present in the liquid phase. This can be explained by their tendency to the sorption onto organic particles, which follows the following ascending order: NAP > PHEN > PYR > BaPYR. Our findings emphasize that organic particle-laden sea ice may lead to enhanced retention of toxic particulate-bound PAHs, which could be an important exposure pathway to sea ice organisms.
Fanny Piras, Sara Fleury, Eero Rinne, Marion Bocquet, Pierre Féménias
Corresponding author: Fanny Piras
Corresponding author e-mail: fpiras@groupcls.com
In the framework of the European Long Term Data Preservation Program (LTDP+), which aims at generating innovative Earth system data records named fundamental data records (FDR) and thematic data records (TDP), similar to level 2+ geophysical products, ESA/ESRIN launched 3 years ago a reprocessing activity of the ERS-1, ERS-2 and ENVISAT altimeter and radiometer dataset, covering more than 20 continued years of data, from 1991–2012. A large consortium of thematic experts has been formed to perform these activities which are 1) to define new tailored end-user products including the long, harmonized record of uncertainty-quantified observations, 2) to define the most appropriate and state-of-the-art level 1 and level 2 processing, 3) to reprocess the whole times series according to the upgraded ground processing and, 4) to validate the different products and provide them to a large community of users focused on the observation of the atmosphere, ocean topography, ocean waves, coastal, hydrology, sea ice and ice sheet regions. The project kicked off in September 2019 and final products will be ready for June 2023. This activity resulted in the production of eight different datasets for each mission, each addressing a different need, including one fully dedicated to sea-ice that contains variables of interest such as radar freeboard, sea-ice thickness and snow depth. An uncertainty is associated with each measurement to ease data use. Performances of this new dataset has been fully assessed using in-situ measurements but also other altimetry datasets. Results show major improvements compared to the current ESA ERS and Envisat Altimetry products, with especially the production of the first radar freeboard time-series from ERS-1 (1994) to Cryosat-2 (2021). The objective of this poster is to inform the IGS members of this initiative, to explain the main guidelines, constraints and status of the project and then to present the content of the sea-ice thematic product and its excellent performances. In particular, the poster will show how the sea-ice community will be able to benefit from this reprocessing to improve long-term climate analysis.
Harry Heorton, Michel Tsamados, Paul Holland, Jack Landy
Corresponding author: Michel Tsamados
Corresponding author e-mail: m.tsamados@ucl.ac.uk
Sea-ice floating upon the Arctic ocean is a constantly moving, growing and melting surface. The seasonal cycle of sea ice volume has an average change of 10 000 km3 or 9 billion tonnes of sea ice. The role of dynamic redistribution of sea, the process by which it flows and deforms when blown by winds and floating upon ocean currents, has been observable during winter growth by the incorporation of satellite remote sensing of ice thickness and drift. Recent advances in the processing of CryoSat2 radar have allowed for the retrieval of summer sea ice thickness. This allows for a full year of a purely remote sensing derived observational volume budget analysis. Here we analyse the role of dynamical redistribution of sea ice using a thorough data uncertainty statistical method, revealing key length and timescales of data accuracy and key regions of ice growth and melt. Maps of ice growth, melt and dynamic redistribution are presented. Ten full winter growth and summer melt seasons are analysed over the CryoSat-2 period between October 2010 and April 2021. We reveal key circulation patterns that contribute to summer melt and minimum sea ice volume and extent. Specifically we show the importance of ice drift to the interannual variability in Arctic sea-ice volume, and the regional distribution of sea-ice growth and melt rates. The estimates of specific areas of sea-ice growth and, for the first time, sea-ice melt, provide key information for sea ice predictability and climate model validation. The statistical accuracy of each key region of the Arctic is presented, showing how, while daily data can have low accuracy, the accumulation of seasonal data presents reliable estimates of the whole sea ice volume budget. We make our product and code available to the community in monthly pan-Arctic netcdf files for the entire period October 2010–April 2021.
Understanding recent changes in Antarctic sea ice seasonality
Kenza Himmich, Martin Vancoppenolle, Sharon Stammerjohn, Gurvan Madec
Corresponding author: Martin Vancoppenolle
Corresponding author e-mail: martin.vancoppenolle@locean.ipsl.fr
Changes in the timing of Antarctic sea ice retreat and advance have been analyzed over over 1979–2012, based on satellite sea ice concentration retrievals. The Ross Sea showed large trends towards earlier sea ice advance and later retreat whereas the Bellingshausen and Amundsen Seas showed opposite trends. Since 2016, however, we find the occurrence of anomalously late advance and early retreat in the Ross and Weddell Seas and anomalously early advance and late retreat west of the Amtarctic Peninsula. Trends in the timing of sea ice retreat and advance are consequently weaker over 1979–2022 than over 1979–2012. Here we investigate the possible role of ocean thermodynamics and wind-driven ice drift in causing such anomalies and resulting trend weakening, using satellite and reanalysis data. In most of the seasonal zone, anomalies in the date of advance strongly correlate with anomalies in the previous seasonal maximum sea surface temperature (SST) and in the previous date of retreat. This suggests that anomalies in the date of advance are caused by summer ocean heat uptake anomalies, themselves constrained by anomalies in the previous date of retreat. In a large outer band of the seasonal ice zone, however, anomalies in the timing of sea ice advance seem linked to anomalies in the magnitude of winter southerlies, suggesting a possible role for ice drift anomalies there. By contrast, we find no clear correspondence between anomalies in the date of retreat and anomalies in winds or SST. We will provide more analysis to disentangle the thermodynamic and dynamic mechanisms causing anomalies in the date of retreat, based on a sea ice concentration budget decomposition.
Tracking summer Arctic sea-ice extent using microseism observation
Jui-Chun Freya Chen, Sunyoung Park, Douglas MacAyeal
Corresponding author: Jui-Chun Freya Chen
Corresponding author e-mail: freyachen@uchicago.edu
Climate models predict acceleration in sea-ice loss, particularly during summer in the Arctic Ocean. Yet there are large prediction uncertainties arising from insufficient and inaccurate measurements of sea-ice concentration. Despite the improvements in remote observation of sea-ice concentration by satellites and airborne radar imagery in recent years, spatial and temporal resolutions are still limited. In particular, sea-ice concentration along the coastal region during summer can be unreliable. Recent studies have indicated that this challenge can be overcome by utilizing seismic data with near-continuous temporal resolution. They have shown that microseism data at 0.1–3 s period are sensitive to variability in sea-ice concentration due to the sea-ice damping effect on ocean wave heights. As the source of these microseism signals is mostly local ocean wave activity, sea ice formation in winter reduces the wave activity and thus reduces seismic signals, while in summer signals increase due to the reduction of sea-ice concentration. In this study, we examine summer microseism over the past decades observed by the seismic station ALE (Alert) in Ellesmere Island. ALE is one of the permanent on-land stations near the margin of the Arctic Ocean and hence is probably sensitive to sea-ice concentration along the coast. In order to investigate the year-to-year variability of summer sea-ice concentration, we examine the difference in microseism signals at 0.1–3 s period for each year with respect to the average over multiple decades. By comparing our results with remote sensing observations, our goal is to assess how well microseism signals can track summer sea-ice extent over past decades. Depending on the outcome of this assessment, seismic microseism observation can potentially provide complementary information to improve sea-ice data and thus facilitate better climate-model predictions.
Grant Macdonald, Randall Scharien, Parnian Rezania, Christian Haas, Stephen Howell, Alexander Komarov
Corresponding author: Grant Macdonald
Corresponding author e-mail: grantmacdonald@uvic.ca
Knowledge of sea ice surface roughness is key for understanding air–ice surface momentum transfer and ice motion, the evolution of ice cover and the development of melt ponds, and for planning safe ice travel in Arctic regions. Sea ice elevation measurements are important for estimating thickness, which plays a key role in the transfer of energy between the atmosphere and ocean. Although roughness and elevation information can be obtained from altimetry, these data are spatially and temporally limited when compared to the capabilities of recent synthetic aperture radar (SAR) missions. In this study we assess sea ice surface roughness and elevation in the Canadian Arctic Archipelago and outline the utility of SAR backscatter data for retrieval of these parameters. Here we primarily compare sea ice surface roughness and elevation data obtained from ICESat-2’s ATL07 product with coincident C-band RADARSAT Constellation Mission (RCM) data in 2020 and 2021. First-year and multi-year ice are both studied, and the role of incidence angle and polarization in retrievals is assessed. Our work shows that a segmentation-based analysis enables the study of the relationship between air/spaceborne roughness measurements and the SAR backscatter of homogenous sea ice zones. We find C-band SAR to be effective at retrieving the surface roughness of first-year ice during the winter period, particularly at near- to mid-range incidence angles and the relationship between RCM backscatter and ice elevation is also notably strong. Additionally, we compare the performance of RCM with our analysis of other SAR missions, including Sentinel-1 and RADARSAT-2 (C-band) and PALSAR-1/2 (L-band), alongside coincident airborne topography data.
Advances in homogeneous time series of sea ice thickness and snow depth observed by altimetry
Camille Boulard, Sara Fleury, Marion Bocquet, Alice Carret, Frédérique Remy, Anne Lifermann
Corresponding author: Camille Boulard
Corresponding author e-mail: camille.boulard@legos.obs-mip.fr
The longest time series of sea ice thickness (SIT) observations currently available are limited to Envisat and CryoSat-2 period (2002–22), whereas because of the high interannual variability of sea ice, climatic analyses require longer time series. We have been able to improve and extend this time series in a homogeneous way from ERS-1 to CryoSat-2 (1993–2022) on both hemispheres. Another parameter, snow depth, is mandatory for the retrieval of the SIT, but there are very few basin-wide observations and still no highly confident estimations of this variable. A snow depth climatology (modified Warren-99 climatology) constructed from in-situ measurements before the first significant impacts of climate change is used in the Arctic. In the Antarctic, SIT products are impacted by the lack of snow depth information. Methods using satellite-borne microwave sensors (AMSR-E, AMSR-2) have been used to estimate snow depth, but validation exercises have shown that these products still need improvements. The product we propose is an alternative solution based on altimetry that could contribute to better snow depth estimations. This poster aims to present two recent products time-series that have been developed. The first product is a homogeneous SIT series over the long term, going back to ERS-1 altimeter. To provide this series, a neural network is used to calibrate Envisat radar freeboard data against CryoSat-2 radar freeboard and then ERS-2 radar freeboard against Envisat calibrated radar freeboard. The calibration is trained on the discrepancies observed between the altimeter measurements during the missions overlap periods, and parameters that characterize the sea ice state. This poster presents the latest version of the altimetric snow depth (ASD) product for both hemispheres from 2013 (Saral launch date). It is computed from the height difference between the Ka-band (Saral) and Ku-band (CryoSat-2) measurements. The main hypothesis is that the Ka-band reflects over the snow whereas the Ku-band penetrates the snowpack. We present the methods used to obtain these products, their main characteristics and how they have been validated against independent datasets, including in-situ measurements. Both products cover the six winter months for both hemispheres, except for SIT in Antarctic where winter and summer data are available. Acknowledgement: Esa, FDR4ALT and Polar+SnowOnSeaice.
Renaud Person, Martin Vancoppenolle, Olivier Aumont, Manon Malsang
Corresponding author: Martin Vancoppenolle
Corresponding author e-mail: martin.vancoppenolle@locean.ipsl.fr
Observations indicate iron concentrations in Antarctic sea ice an order of magnitude larger than in seawater, where iron limits phytoplankton growth – and the idea that iron release from sea ice could matter for phytoplankton dynamics in the Southern Ocean has been around for more than a decade now. We will review a series of modelling experiments that were run with NEMO at 1° resolution during these beautiful covid-19 times and illustrate the following key points: (i) The Southern Ocean phytoplankton activity is more realistic when modeling iron release from melting continental and sea ice. (ii) Continental and sea ice iron sources have an overall additive effect on the biological carbon pump strength. (iii) The fertilization effects of the sea ice iron source are larger when the continental-ice iron source is activated. Overall, we reiterate the key finding that Antarctic sea ice is an iron conveyor from growth to melting regions.
Optical instrument for in situ measurement of the nutrients in sea ice
Gabriel Lapointe, Yasmine Alikacem, Jean-Éric Tremblay, Marcel Babin
Corresponding author: Gabriel Lapointe
Corresponding author e-mail: gabriel.lapointe.8@ulaval.ca
The Arctic icescape is currently changing, and this is reflected in the different compartments of the marine ecosystem, notably the sympagic one where microalgae now develop in younger, thinner and more transparent sea ice. Although microalgae now have intenser and longer exposure to photosynthetically usable radiation, their growth remains constrained by the presence of nutrients in the water below and the ice above. In order to study the nutrient fluxes in the sea-ice matrix, an instrument is being developed to measure the concentration of nitrate in situ. Basically, brine is analyzed by extracting it from the ice inclusions with a probe designed to slowly sink into the sea ice by melting it. The nitrate concentration is then determined from its absorption peak in ultraviolet (UV) light. The optical part of the instrument consists of a deep UV spectrophotometer system optimized for nitrate detection in a liquid waveguide capillary. The aim of this development is to obtain fast and precise measurements in situ, in addition to vertically resolved measurements, feats impossible with techniques such as core sampling and the sackhole method. Results from this work in progress are presented, and challenges discussed.
Sea ice: an extraordinary and unique, yet fragile, biome
Letizia Tedesco, Eric Post
Corresponding author: Letizia Tedesco
Corresponding author e-mail: letizia.tedesco@environment.fi
Sea ice – a unique and extraordinary biome in its nature and dynamics – is under threat. I will review here how ocean warming, sea-ice decline and altered seasonality endanger the simple, vulnerable and low resilient sea-ice and ice-associated food webs in both polar oceans.
Henriette Skourup, Sara Fleury, Renée Mie Fredensborg Hansen, Jean-Christophe Poisson, Frederic Vivier, Antonio Lourenco, Emma Woolliams, Sajedeh Behnia, Elodie Da Silva, Pierre Femenias
Corresponding author: Henriette Skourup
Corresponding author e-mail: hsk@space.dtu.dk
The Copernicus Sentinel-3 (S3) Surface Topography Mission (STM) provides extremely valuable surface elevation information over inland waters, sea ice and land ice, thanks to its SAR altimeter which retrieves high-resolution along-track elevation measurements, and to its orbit that covers relatively high-latitudes in polar regions. The ESA st3TART project aims to define the framework of fiducial reference measurements (FRMs) and to collect and distribute FRM data for the validation of the S3 STM Land products. This presentation will focus on the work made within the St3TART sea ice theme, where the main geophysical measurements include surface type classification over sea ice (leads/floes), radar sea ice freeboard and sea ice thickness. Based on a thorough review of existing methods and lessons learnt from previous reference campaigns to identify suitable solutions in terms of, e.g., sensors, sampling strategy, uncertainty budget, we conclude that we need to use a variety of sensors and platforms representing different temporal and spatial scales to fully validate the S3 sea ice products. Based on these findings, the sea ice team has organized two field campaigns; 1) ESA St3TART 2022 spring campaign using new and tested sensors and techniques from fixed winged aircraft, drone and autonomous drifting buoys, 2) the DESIR project on board the ship Le Commandant Charcot to further test the drone setup in a moving environment. These campaigns have been acting as a test-bed for future Cal/Val reference measurements, but also demonstrated the challenges associated with field campaigns in the Arctic environment. We will here present; new results from the st3TART campaigns, with focus on the novel sensors and techniques i.e. the drone and drifting buoy, in combination with the airborne measurements to demonstrate the validation of S3 over sea ice. We will further use the airborne altimetry measurements, as an example to define the full cycle of properly characterized and traceable to standards and/or community best practices of a given FRM. We will conclude the presentation by presenting the roadmap for the provision of S3 FRMs for sea ice, including the most relevant and cost-effective methods to be maintained, supported as far as possible or implemented, and identifying the parameters that are missing or are insufficiently covered over the entire end-to-end duration of a satellite altimetry mission.
What governs the key transitions in the sea ice seasonal cycle?
Martin Vancoppenolle, Kenza Himmich, Marion Lebrun, Gurvan Madec
Corresponding author: Martin Vancoppenolle
Corresponding author e-mail: martin.vancoppenolle@locean.ipsl.fr
The sea ice community has taken a lot of trouble to understand and predict the spatial distribution of sea ice. The transition towards more seasonal ice raises the question of when in the season is sea ice present, of large importance from a local point of view. Whereas the seasonal cycle of sea ice is fairly well documented from satellite observations, basic understanding of what controls keystone moments in the seasonal cycle (advance, melt onset, retreat) is generally lacking. Over the last few years, we have elaborated conceptual approaches for the seasonal cycle of sea ice, from observations and modelling activities and identified a few overarching elements.which we discuss. (i) The date of advance is largely conditioned by the summer storage of heat in the ocean mixed layer. (ii) The date of retreat is conditioned by maximum ice thickness, but it is more variable and less predictable than the date of advance. (iii) Ice drift modifies thermodynamically predicted advance and retreat in large regions of the Arctic and Antarctic ice zones. (iii) At the regional scale, atmosphere and ocean heat supply are important factors to consider. We develop these ideas and discuss how these mechanisms shape the seasonal cycle in the Arctic and Antarctic sea ice regions.
Light under Arctic sea ice in observations and Earth system models
Marion Lebrun, Martin Vancoppenolle
Corresponding author: Marion Lebrun
Corresponding author e-mail: marion.lebrun@locean.ipsl.fr
The intensity and spectrum of light under Arctic sea ice, key to the energy budget and primary productivity of the Arctic Ocean, are tedious to observe. Earth system models (ESMs) are instrumental in understanding the large-scale properties and impacts of under-ice light. To date, however, ESM parameterizations of radiative transfer have been evaluated with a few observations only. From observational programs conducted over the past decade at four locations in the Northern Hemisphere sea ice zone, 349 observational records of under-ice light and coincident environmental characteristics were compiled. This data set was used to evaluate seven ESM parameterizations. Snow depth, melt pond presence and, to some extent, ice thickness explain the observed variance in light intensity, in agreement with previous work. The effects of chlorophyll-a are also detected, with rather low intensity. The spectral distribution of under-ice light largely differs from typical open ocean spectra but weakly varies among the 349 records except for a weak effect of snow depth on the blue light contribution. Most parameterizations considered reproduce variations in under-ice light intensity. Large errors remain for individual records, on average by a factor of ∼3, however. Skill largely improves if more predictors are considered (snow and ponds in particular). Residual errors are attributed to missing physics in the parametrizations, inconsistencies in the model-observation comparison protocol, and measurement errors. We provide recommendations to improve the representation of light under sea ice in the ice–ocean model NEMO, which may also apply to other ESMs and help improve next-generation ESMs.
The ESA CCI sea-ice thickness climate data record: current state and evolution
Stephan Paul, Stefan Hendricks, Henriette Skourup, Heidi Salilla, Eero Rinne, Thomas Lavergne
Corresponding author: Stephan Paul
Corresponding author e-mail: stephan.paul@awi.de
Polar sea ice is both an indicator and a driver of global climate change with today almost 30 years of sea-ice thickness data from various space-borne sensors available to us. ESA’s Climate Change Initiative (CCI) aims to combine this data into a single dataset and achieve an improved spatial resolution and best possible consistency across satellite missions. In its previous versions, the CCI sea-ice thickness climate data record (CDR) laid the foundation for a comprehensive multi-altimeter data record produced on Arctic and Antarctic sea-ice freeboard from October 2002 to April 2017. Building on this foundation, the data set was temporarily extended to include the ERS-1/2 satellite era in order to cover the winter months from October 1993/95 to April 2022. In its current state, the CDR comprises various processing levels from orbit trajectories (L2p) to gridded data products (L3C). In order to keep the data between the different sensors (ERS-1/2, ENVISAT, CryoSat-2) and sensor systems (delay-Doppler vs pulse-limited) as consistent as possible, we analyze and utilize dual-mission orbital crossovers and orbital track matches in the respective operational overlap periods between all sensor systems, e.g. the winter months between October 2010 and March 2012 for CryoSat-2 and ENVISAT. From these data sets, optimal retracker parameters for the consistently used Threshold First Maximum Retracker Algorithm are derived from recent to older sensors while using CryoSat-2 freeboard estimates as a reference. Subsequently, training data sets for the overlap periods and sensor combinations are created and used to calibrate and validate different deep-learning models to be used for the adaptive retracker threshold computation. Additional new features comprise the use of an updated data set and methods for snow on sea ice, improved uncertainty estimates, and the extension to interim sea-ice type data from C3S. Shortcomings still exist, in particular for all Antarctic sea-ice retrievals due to large uncertainties resulting from the Antarctic sea-ice snow cover, as well as knowledge gaps on the sea-ice density distribution. Improvements were achieved for the marginal sea-ice zone, both in the Arctic and the Antarctic.
Rosemary Willatt, Robbie Mallett, Jeremy Wilkinson, Julienne Stroeve, Vishnu Nandan, Thomas Newman
Corresponding author: Rosemary Willatt
Corresponding author e-mail: r.willatt@ucl.ac.uk
Antarctic sea ice extent hit a record low in 2022, and will almost certainly reach an even more extreme minimum in 2023. Unlike its areal coverage, satellite retrieval of Antarctic sea ice thickness remains a formidable challenge due to a characteristically thick and poorly observed snowpack. In particular, uncertainties surrounding radar penetration of snow on Antarctic sea ice represent a barrier to radar-retrievals of underlying sea ice thickness with instruments such as Cryosat-2’s Ku-band altimeter, and SARAL-AltiKa’s Ka-band altimeter. We present 16 radar profiles from five snow covered sea ice floes in the Weddell Sea, taken in March 2022. These profiles are taken in the Ka & Ku bands to mimic the operation of satellite altimeters, but they have a considerably higher range-resolution which allows detailed study of the origins of backscattered radar power. Our data come from ice floes that survived the summer melt and had a thick cover of remnant, heavily modified snow which generally did not allow radar power to return in significant quantities from the ice surface. However, a very clear signal was generally apparent from the boundary between the remnant snow and overlying snow that had not been exposed to above-zero temperatures. Our findings have wide implications for the development of radar-derived sea ice thickness products in the Weddell and Ross Seas, which act as refugia for ice at the summer minimum.
Daily drift-aware sea ice freeboard and thickness maps from satellite altimetry
Robert Ricker, Thomas Lavergne, Stefan Hendricks, Mari Anne Killie
Corresponding author: Robert Ricker
Corresponding author e-mail: rori@norceresearch.no
The polar regions are a hot spot of climate change, and large-scale satellite observations to monitor sea ice decline are important. One of the essential climate variables is sea ice thickness, controlling the heat exchange between ocean and atmosphere. Within the European Space Agency Climate Change Initiative project, consistent sea ice thickness time series across different satellite altimetry missions are generated to observe long-term trends. To provide monthly maps of ice freeboard and thickness, daily trajectories are averaged on a 25 km grid, while each trajectory only represents the ice thickness in the moment of the satellite overflight. However, sea ice can drift significantly within 1 month, especially in areas with typically high drift rates, such as in the Beaufort Gyre or Fram Strait. Moreover, in the context of climate change, studies suggest that sea ice will become more mobile in the future. Neglecting sea ice drift when generating monthly sea ice thickness maps from satellite altimetry will cause blurring of the spatial distribution of ice thickness. We therefore suggest synergizing sea ice freeboard and thickness information from satellite altimetry with sea ice drift estimates from passive microwave satellite sensors. With our approach, we successively advect individual parcels of satellite altimeter measurements daily over a time span of 1 month to obtain drift-aware sea ice freeboard and thickness maps. Because of the drift correction, we can also determine sea ice that was overflown by the satellite multiple times. This allows us to estimate growth rates and changes in the sea ice thickness distribution due to deformation and thermodynamic ice growth between satellite overflights. With the estimation of sea ice growth, measurements can be corrected for the time offset between the acquisition day and the target day, the day to which all measurements within a month are projected. Here we present the first new daily drift-aware sea ice freeboard and thickness maps, using CryoSat-2 and ICEsat-2 data, covering the entire Arctic sea ice domain. Moreover, we will show first validation results, using MOSAiC data of year-long sea ice thickness observations as well as airborne data sets.
Correlations between sea ice and cloud properties over the Arctic from advanced radiation datasets
Linh Vu, Zhonghai Jin, Matteo Ottaviani, Greg Cesana
Corresponding author: Matteo Ottaviani
Corresponding author e-mail: catullovr@hotmail.com
Sea ice significantly impacts the radiative budget in the Arctic and global climate systems, and is sensitive to both atmospheric and ocean forcings. Clouds are a key driver of incoming shortwave and longwave fluxes at the surface, and can lead to warming or cooling depending on cloud phase and altitude. In particular, liquid clouds are highly reflective and highly emissive, which strongly influences the radiative budget at the surface. It is thus critical to assess the relationship between sea ice, atmospheric radiation and cloud properties for the betterment of climate models and Arctic climate. We present an extensive correlation analysis, which exploits cloud and radiation retrievals from three state-of-the-art satellite datasets. High-resolution CERES satellite data provides a spatially complete record of sea ice, cloud, and radiative flux data for the past 20 years. Active-sensor CALIPSO-based datasets (DARDAR and GOCCP) enable the analysis of the possible correlations between sea ice and cloud altitude and phase. Monthly statistics of liquid, ice and mixed-phase clouds, subset to latitudes above 60°, are produced on a 1×&1deg; grid. Cloud cover and 3-D fraction are specified with respect to cloud type. The comparison with the classification of ISCCP-based cloud types is also presented. We find strong correlations between the different liquid-bearing cloud categories and sea-ice extent. However, the magnitude of these correlations slightly differs depending on the region, suggesting a substantial influence of large-scale meteorology.
Lena Buth, Gerit Birnbaum, Thomas Krumpen, Niklas Neckel, Niels Fuchs, Christian Haas
Corresponding author: Lena Buth
Corresponding author e-mail: lena.buth@awi.de
The presence of meltwater ponds on sea ice strongly influences the ice-albedo feedback and thereby polar climate. On a large scale, the areal fraction of melt ponds on Arctic sea ice is determined from satellite-derived products. However, most of these products do not have the necessary resolution to represent individual ponds and their usage is limited to clear sky conditions. By providing high resolution observations of the sea ice surface, aircraft campaigns and drone surveys can help to bridge the gap between satellite remote sensing and in-situ observations. The presented data set of aerial RGB imagery of summer Arctic sea ice allows for the extraction of information on melt pond fraction and size distribution along the flight tracks. In our study we investigate statistical relationships between observed melt pond and sea ice morphology, in particular surface roughness information obtained from coincident airborne laser scanner measurements. Furthermore, pond properties are linked to satellite-based variables derived from a sea ice backtracking approach. Among other linkages we can thereby investigate correlations between the sea ice age and the determined melt pond characteristics. Linking these parameters derived from various instruments and platforms helps step towards a better understanding of the processes related to melt pond formation and improved parameterizations of melt ponds in models.
The effects of the Arctic oscillation on snow on sea ice in a warming Arctic
Melinda Webster, Sahra Kacimi, Thomas Ballinger, Chelsea Parker, Ignatius Rigor, Linette Boisvert
Corresponding author: Melinda Webster
Corresponding author e-mail: melindaw@uw.edu
Over the last four decades, Arctic sea ice has undergone unprecedented change, becoming thinner, less extensive and less resilient to summer melt. These changes have manifested in a seasonal ice cover that is more sensitive to its environmental conditions, including its overlying snow cover. Snow’s insulating effect hinders the growth of sea ice in winter, while its reflective properties shield the ice surface and upper ocean from solar radiation in summer. Gaining insights on the causes of snow’s interannual and decadal variability is therefore essential context for better understanding Arctic sea-ice variability and long-term loss. In this work, we examine the role of the Arctic Oscillation (AO) in snow depth variability on sea ice over seasonal and multi-decadal timescales. We find that a positive AO index enhances sea-ice export from the Arctic, which reduces the amount of time that sea ice can accumulate snow. In contrast, a positive AO index enhances Arctic snowfall which increases snow accumulation. We highlight the effects of these two contrasting relationships on summer snow conditions using a combination of satellite, model, and reanalysis data over 1980–2022. We further investigate how the response of snow and sea-ice conditions to the AO has changed with sea-ice loss, which may reveal insight into the evolving relationship between climate variability and snow on sea ice in a warming climate.
Arctic and Antarctic summer sea ice albedo trends from ENVISAT and Sentinel-3 satellite data
Larysa Istomina, Georg Heygster, Gunnar Spreen, Christian Haas
Corresponding author: Larysa Istomina
Corresponding author e-mail: larysa.istomina@awi.de
Changes in the Arctic and Antarctic sea ice albedo affect the radiation budget of the Earth–atmosphere system and have the potential to affect the global climate. Satellite optical and near infrared observations of Arctic and Antarctic sea ice properties have been carried out for decades. One of the longest available time sequences of sea ice albedo is derived from AVHRR data with the broadband albedo retrieved from only two broad spectral bands, which means that the spectral signatures of various surface types are no longer present in the resulting sea ice albedo product. In this work, we analyze Arctic and Antarctic summer sea ice spectral albedo trends. We utilize the historic ENVISAT (2002–12) and Sentinel-3 (2017–present) optical and near infrared data and apply an established sea ice albedo retrieval which transforms the satellite measured top of atmosphere reflectance into the albedo of the pixel using a physical forward model of the summer sea ice. The retrieval takes OLCI measured top of atmosphere reflectances in the range 412–885 nm and produces spectral albedo at six wavelengths: 400 nm, 500 nm, 600 nm, 700 nm, 800 nm and 900 nm, so that separate spectral regions can be investigated. In addition, a broadband albedo is produced using a narrow-to-broadband conversion. As cloud contamination has the potential to affect the accuracy of the sea ice albedo product, it is important to ensure high quality cloud screening over snow and ice. In this work, we use a Bayesian method trained on a reference AATSR data for the ENVISAT sea ice albedo retrieval, and a synergy of OLCI and SLSTR for the Sentinel-3 sea ice albedo retrieval. We combine the daily sea ice albedo averages into weekly composites to ensure higher spatial coverage and analyze the weekly long-term trends on a 12.5 km grid. The resulting trends show decreasing Arctic sea ice albedo ar the beginning of the melt season, which may be connected to the earlier sea ice melt onset in recent years. For the albedo in the Antarctic, the wide marginal ice zone displays high variability most probably connected to the varying ice concentration. The albedo of the fast ice regions shows clear distinction between first- and multiyear ice types, impurities and blue ice. The snow-covered Antarctic fast and pack ice displays higher albedo than that of the Arctic sea ice before melt season.
Letizia Tedesco, Kristian Spilling, Tomas Lovato, Filippa Fransner, Robinson Hordoir, Anna Villnäs, Heikki Peltonen
Corresponding author: Letizia Tedesco
Corresponding author e-mail: letizia.tedesco@environment.fi
In shallow seasonally ice-covered seas the sea-ice, pelagic and benthic ecosystems are tightly linked but rarely modeled together. Here we investigate the fully coupled system by means of a new configuration of a stoichiometric biogeochemical model, the BFM. The model is implemented at a relatively shallow coastal site typical of the northern Baltic Sea, characterized by seasonal sea ice and muddy oxic sediments. Among the highlights, the pelagic component describes the spring-competing diatoms and dinoflagellates and summer cyanobacteria, the sea ice component focuses on ice algae coupling to phytoplankton, and the benthic component is of intermediate complexity to represent nutrient regeneration and study of P retention in sediments. We present model results averaged over the period 1991–2013 and verify them against monitoring data. We investigate the sensitivity of the system to the coupling by running the pelagic model i) as a closed system, neglecting river runoff, ii) without the benthic component, iii) without the sea-ice component, and iv) as a standalone. We show how the overall biogeochemical dynamics are impacted in the different experiments and conclude that both the composition of the biological community and the phenology of relevant biological events change dramatically depending on the inputs and habitat components considered. Importantly, considering the fully coupled and open system, the description of the shallow ice-covered coastal system improves. Finally, we explore the sensitivity of the fully coupled system to different climate regimes and nutrient load scenarios. We clustered ice seasons into mild, average and severe and applied a 25% decrease/increase of N and P loads to investigate the potential recovery/deterioration of the ecosystem in different climate regimes. Remarkably, in a warmer climate P retention in sediments is the largest in absolute terms but the annual buffering capacity is the highest, pointing to the complex response of the ecosystem to the interplay of climatic and non-climatic stressors.
Alaska landfast ice breakouts: large scale risk factors and early warnings
Andrew Mahoney, Andrew Einhorn, Peter Bieniek, Seth Danielson
Corresponding author: Andrew Mahoney
Corresponding author e-mail: armahoney@alaska.edu
Serving as a floating extension of the land, landfast ice is the most accessible form of sea ice and the one most often encountered by people. Members of Arctic coastal communities use landfast ice to travel between communities and hunt marine mammals and birds that are commonly found at its seaward edge. Landfast ice also serves as a logistics platform for the oil and gas industry in the Arctic and for research and resupply in Antarctica. The distinguishing feature of landfast ice that allows it to fulfill these roles is its attachment to the coast, which prevents it from drifting like the majority of sea ice found in the ocean. The potential for detachment, or breakout, from the coast is therefore of paramount concern for anyone travelling, hunting or operating on landfast ice. Here, we explore the potential for predicting regional breakout potential by identifying characteristic patterns of sea-level pressure associated with breakout events on the Alaska coasts of the Chukchi and Beaufort Seas between 1996 and 2022. We also look in more detail at short terms behavior of landfast ice near Utqiaġvik, Alaska, USA. Using data from a coastal sea ice radar, an under-ice acoustic Doppler current profiler, and the airport weather station, we observe the response of the landfast sea ice to strong winds and currents. Although a clear relationship between breakout events, winds and currents remains elusive, we are able to detect signals related to small-scale motion of ice that may serve as an early warning for breakout events and improve our understanding of coastal sea ice dynamics.
Retrieval of summer sea ice thickness using melt pond optical properties from satellite data
Larysa Istomina, Hannah Niehaus, Janna Rückert, Christian Haas, Georg Heygster, Gunnar Spreen
Corresponding author: Larysa Istomina
Corresponding author e-mail: larysa.istomina@awi.de
With sea ice thickness (SIT) being one of the essential climate variables, in situ, airborne and remote sensing SIT research have been carried out for decades. Remote sensing observations using radar and laser altimetry (e.g. CryoSat-2, ICESat-2) and L-band microwave radiometers (e.g. SMOS/SMAP) have been successfully used to determine the Arctic and Antarctic SIT. While in situ and airborne SIT data is mostly available during Arctic summer, the satellite remote sensing SIT products mostly cover the winter and freezing seasons as the surface wetness and the presence of melt ponds on top of the sea ice complicate both of the mentioned retrieval methods during the Arctic summer. In this work, we present an alternative way to retrieve summer SIT using optical satellite data and the connection of the melt pond optical appearance to the thickness of the sea ice underneath. As input, we use eight spectral channels of the OLCI sensor onboard Sentinel-3. For the retrieval we utilize a physical forward model of the melting sea ice, which allows simultaneous retrieval of melt pond fraction and the sea ice thickness within melt ponds. The boundary conditions to invert the forward model have been derived from a comprehensive set of in situ spectral albedo measurements taken during the RV Polarstern ARK27-3 ‘IceArc’ cruise (August–October 2012, central Arctic). We use the synergy with the Sentinel-3 SLSTR sensor to perform cloud screening over sea ice. The resulting retrieval is performed on the full-resolution OLCI data with 300 m spatial resolution. As ground truth we take helicopter-based SIT measurements performed using electromagnetic conduction sounding (EM-Bird) taken during the RV Polarstern PS 131 ‘ATWAICE’ cruise (July–August 2022, western Nansen Basin). The comparison of the retrieved optical satellite SIT to the EM-Bird data shows good correspondence. The observed slight underestimation of the satellite-derived SIT is expected and may be connected to the melt ponds forming in depressions of the ice floe relief. We discuss ways to correct for this discrepancy, as well as the applicability limits of the summer SIT retrieval. The presented optical SIT retrieval provides a spatial distribution of the summer SIT at a high spatial resolution of 300 m within a wide 1270thinsp;km swath and has the potential to complement the passive microwave and altimeter SIT data on local to global Arctic scales.
Jacqueline Stefels, Maria van Leeuwe, Deborah Bozzato, Alison Webb, Ellen Damm
Corresponding author: Jacqueline Stefels
Corresponding author e-mail: j.stefels@rug.nl
This presentation is a contribution to the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The MOSAiC field campaign took place on board RV Polarstern, drifting with the Arctic sea ice, from October 2019 to October 2020. As partner of the MOSAiC team, our project contributed to the production of a time series of sulphur compounds in Arctic sea ice and underlying seawater. The aim of our project was to address how seasonality, sea ice dynamics and water characteristics in the Arctic Ocean affect the cycling of organic sulfur compounds. The sampling of sea ice and surface water was part of the concerted actions of the BGC, ICE and ECO teams during MOSAiC. A crucial compound for organisms to survive the cold and saline environment of sea ice is the organic sulfur compound dimethylsulfoniopropionate (DMSP), which is mainly synthesized by algae. Between 1% and 10% of total primary production is invested in DMSP, making it a key compound in the lower – and potentially also higher – trophic levels. DMSP is also the precursor of the climate active semi-volatile compound dimethylsulfide (DMS). Our work combines measurements of concentrations of DMSP, DMS and the (photo-)oxidation product of DMS, dimethyl sulfoxide (DMSO), transformation rates of these compounds using stable isotope addition experiments and identification of the microorganisms driving these processes. We show persistent features of DMS(O/P) distribution in vertical profiles of the MOSAiC floe, and surface-water distribution of DMS(O/P) in relation to water mass, link these profiles to algal community structure, and discuss the connection between ice and surface water DMS(O/P) concentrations. We will present a conceptual model of how the growth of sea ice in the central Arctic Ocean results in specific DMS(P) distribution patterns.
Timing of rainfall associated with Arctic cyclones and impacts on the sea ice
Linette Boisvert, Melinda Webster, Chelsea Parker, Samantha Halstead-Santez
Corresponding author: Linette Boisvert
Corresponding author e-mail: linette.n.boisvert@nasa.gov
Arctic cyclones are responsible for bringing in the majority of snowfall which falls on Arctic sea ice and builds up the snowpack throughout the year. Previous studies have shown conflicting results that cyclone frequency and intensity have not necessarily changed over the past four decades (1980–2020). However, with a warming climate and given that the Arctic is warming faster than anywhere on Earth, it is hypothesized and shown that the precipitation phase of these cyclones could be shifting from predominantly snow to more rain-dominated. This could have profound effects on the sea ice survivability, especially if this ‘rainy’ cyclone season extends earlier in the spring and later into the fall. Cyclone rainfall on the snowpack in the spring would decrease the albedo and might initiate melt, whereas cyclone rainfall on sea ice in the fall would hinder the build-up of the snowpack and could cause the sea ice thickness regrowth to occur at a faster rate. In previous work we investigated the occurrence and amount of rainfall associated with Arctic cyclones, and how the timing and amount of rainfall might have changed in recent decades. In this work, we will assess how the timing of these rainy cyclones impact individual sea ice parcels in a Lagrangian sea ice framework to better understand the effect that cyclone rainfall has on the sea ice and when it hurts or hinders its survivability.
Developing an unmanned airborne electromagnetic system for sea ice and snow thickness measurements
Achille Capelli, Thimira Asurapmudalige, Denise Thorsen, Dejan Raskovic, Hans-Peter Marshall, Andrew Mahoney
Corresponding author: Achille Capelli
Corresponding author e-mail: acapelli@alaska.edu
In a changing Arctic environment transitioning from perennial to seasonal ice, measuring sea ice thickness and snow cover depth is fundamental for understanding the present and future state of the ice cover and polar marine environment. Changing ice conditions are moreover a challenge for the traditional uses of sea ice such as travel and subsistence hunting. Different satellite-based methods for ice-thickness observation exist but still lack the time and spatial resolution, and accuracy, for many applications. In situ observations of ice and snow cover thickness are, therefore, still crucial. Ground based and airborne electromagnetic (EM) sounding allow sea ice thickness measurements with an accuracy better than 90%. However, existing ground-based systems are limited to accessible sea ice, whereas airborne systems are expensive, require infrastructure for landing and takeoff, and cause disturbance when flying low. Additionally, they generally do not account for the snow cover. Within the Long-range Airborne Snow and Sea Ice Thickness Observing System (LASSITOS) project we developed a sensor system for measuring sea ice and snow thickness from an unmanned aerial system (UAS). We used a combination of multifrequency EM, laser altimeter and FMCW radar for determining both ice and snow thickness. The use of a UAS allows flexible deployment from land and marine platforms, thickness measurement of ice inaccessible to surface travel and 2-D mapping on a small scale. We present the challenges of developing the AEM system and the preliminary results of the first field measurement of land-fast ice in Utqiaġvik, Alaska, USA.
The role of forcing in the simulated rate of Arctic sea ice loss
Patricia DeRepentigny, Marika Holland, Alice DuVivier
Corresponding author: Patricia DeRepentigny
Corresponding author e-mail: pderepen@ucar.edu
Recent work has shown that the Arctic is particularly sensitive to forcings often considered less important than anthropogenic greenhouse gas changes. For instance, a modeling study showed that without increases in industrial aerosol emissions since 1920, the Arctic would not have experienced any 50-year cooling trends over the past century. The subsequent reductions in anthropogenic aerosols emissions since the 1980s in turn may have warmed the Arctic surface. Emissions of ozone depleting substances have also been shown to enhance Arctic warming and sea ice loss in the second half of the 20th century. More recently, it was shown that a large part of the enhanced early 21st century Arctic surface warming and September sea ice decline in the Community Earth System Model version 2 (CESM2) can be attributed to the increased inter-annual variability in prescribed Northern Hemisphere mid-latitude biomass burning emissions in the CMIP6 forcing compared to CMIP5. This is the second time that aerosol-related forcing changes have been shown to impact Arctic sea ice trends between CMIP generations, highlighting how sensitive sea ice is to the effects of aerosol emissions. We dig deeper into the concept of forcing uncertainty that arises from imperfect knowledge or representation of climate forcings in model simulations and look at the impact of other changes in prescribed forcing from CMIP5 to CMIP6 on the simulation of Arctic climate and sea ice loss. We make use of the CESM2 Single Forcing Large Ensemble to isolate the effect of different types of forcing on the changing Arctic climate. Consistent with previous work, we find evidence that the sea ice response to aerosol forcing is influenced by the mean climate state. To further diagnose the sensitivity of sea ice to aerosols, we perform and analyze additional sensitivity simulations to address the state dependence of the response of non-linear climate feedbacks to the imposed forcing and initial sea ice conditions.
Andrew Einhorn, Andrew Mahoney
Corresponding author: Andrew Einhorn
Corresponding author e-mail: aheinhorn@alaska.edu
Landfast ice is sea ice found adjacent to the coast and immobilized by grounded ridges and bottomfast ice. Arctic coastal communities use landfast ice as a seasonal extension of land for intercommunity travel and subsistence hunting, among other uses. In addition, landfast ice serves as a natural protector from coastal erosion and provides a habitat for marine mammals. The extent and timing of landfast ice is a key indicator for the climate conditions in the coastal Arctic. The Alaska Sea Ice Program (ASIP) has produced digitized ice charts from 2007 to the current season identifying areas of landfast ice in Alaska, USA. This dataset is being used to provide the binary presence or absence of landfast ice and create an up-to-date climatology of landfast ice extent in Alaska. However, to improve our understanding of the mechanisms by which landfast ice attaches and detaches from the coast and, in turn, the safety of on-ice activities, we would like to know not just where landfast ice is present but also how stable that ice is. Here, we present a pan-Alaska analysis of landfast ice using synthetic aperture radar interferometry (InSAR). InSAR holds promise as a means for automated identification of landfast ice extent based on coherence thresholding, but it can also detect small-scale deformation within the fast ice extent. We use 12-day Sentinel-1 interferograms to establish the landfast ice extent and stability during the four seasons from 2018–22. We use a coherence threshold to delineate the extent of landfast ice in each interferogram and find that it aligns well with the extent as defined by the ASIP ice charts. We also calculate the interferometric phase gradient to quantify centimeter-scale deformation in the line-of-sight direction. Such motion does not disqualify the ice from being landfast ice but is interpreted to indicate reduced stability of the ice. Based on phase gradients, we identify three different classes of stability within the landfast ice: bottomfast, stabilized and nonstabilized. Over the course of a season, we found that the monthly phase gradient tends to decrease for ice that remains in place, suggesting increasing stability during winter. This technique offers an opportunity to assist and improve charting of landfast ice extent while also allowing us to assess how landfast ice stability may change the future.
The seasonal evolution of Antarctic snow and sea ice thickness from ICESat-2
Ted Maksym, Steve Ackley, Sharon Stammerjohn, Jean-Louis Tison
Corresponding author: Ted Maksym
Corresponding author e-mail: tmaksym@whoi.edu
Antarctic sea ice thickness evolution is driven by a complex combination of ice growth, deformation and snow accumulation. Yet, quantifying the relative roles of these processes is challenging due to limited observations and the ambiguity in satellite thickness retrievals due to ambiguity in snow depth. We present an assessment of the relative roles of these processes in ice production in the Ross Sea from ICESat-2. This approach uses a Lagrangian ice-tracking scheme to examine the change in ice thickness distribution for ice patches sampled multiple times by ICESat-2. To attribute observed changes in freeboard to specific processes, the freeboard distribution is segmented into ice types, using observed relationships between ice topography and snow depth from a suite of observational data. Changes in observed freeboard are then compared to estimates from an ice growth model, precipitation and ice drift. We show that this method can reduce ambiguities in satellite-derived ice thickness change that are not possible with regional estimates. Results show that sea ice production in coastal polynyas in the Ross Sea is consistent with, but somewhat greater than in-situ based estimates, suggesting spatial sampling biases in either ICESat-2 freeboard or in-situ observations. For the broader Ross Sea, results suggest that thick ice production is predominantly driven by deformation and snow ice production. The role of the latter in modulating sea ice thickness variability is examined by comparing results to ice core data obtained from four prior winter sea ice cruises.
The influence of snow on Antarctic sea ice
Ruzica Dadic, Julia Martin, Roberta Pirazzini, Martin Schneebeli, Brian Anderson, Bin Cheng, Petra Heil, Henna-Reetta Hannula, Mario Hoppmann, Polona Itkin, Matthias Jaggi, Michael Lehning, Greg Leonard, Bonnie Light, Henning Löwe, Amy Macfarlane, Wolfgang Rack
Corresponding author: Ruzica Dadic
Corresponding author e-mail: ruzica.dadic@slf.ch
Snow cover affects the variability of the physical properties of sea ice. The snow’s unique thermal and optical properties govern the mass and energy fluxes in the sea ice system and are important for sea ice evolution and energy exchanges between the ocean and the atmosphere, as well as light availability for ecosystems below the sea ice. Furthermore, snow significantly impacts the remote sensing retrievals, especially for sea ice thickness. Yet, data on the physical properties of snow and its effects on sea ice are extremely limited, especially in Antarctica. This leads to large uncertainties in the coupling of climate feedback and results in significant biases in model representations of the sea ice cover. During our field campaign from October to December 2022 in McMurdo Sound, we quantitatively investigated the physical properties of snow on Antarctic sea ice, following the same protocols that were used during the MOSAiC expedition. The season’s unique sea ice conditions provided the ideal laboratory to study a range of snow conditions and to differentiate between sea ice and snow drivers for the atmosphere–sea ice–ocean system. Our set of snow measurements on sea ice, unprecedented in Antarctica, include ground snow/ice measurements, automatic weather and radiation stations, and drone-based measurements. These extensive measurements made it possible to capture the physical properties of snow and their spatial variability and, at the same time, to measure the different components of the energy balance at varying spatial scales. We will use this dataset to improve our understanding of the role that snow plays for the Antarctic sea ice system.
Emily R. Fedders, Andrew R. Mahoney, Dyre Oliver Dammann, Chris Polashenski, Jennifer Hutchings
Corresponding author: Emily R. Fedders
Corresponding author e-mail: erfedders@alaska.edu
Despite being stationary by definition, landfast ice continually experiences intermittent episodes of both continuous and brittle strain affecting its stability as a platform for subsistence and industry use. Here we demonstrate a new analytical inverse method for quantifying such strains from repeat-pass interferometric synthetic aperture radar (InSAR) and apply this technique in tandem with field measurements of point displacement to observe strain variations in landfast ice in and around Elson Lagoon, Alaska, USA over a single season. We calculate 12- and 24-day repeat-pass Sentinel 1 interferograms covering Elson Lagoon and the surrounding area between December 2018 and May 2019 using the Alaska Satellite Facility’s Hybrid Pluggable Processing Pipeline (HYP3) interface. These interferograms coincide with measurements from a laser strain observatory (LSO), consisting of a high precision total station and an array of retroreflectors deployed on the lagoon during the 2018/19 Sea Ice Dynamics Experiment (SIDEx) project field campaign. We use an analytical inverse method accounting for interferometric fringe patterns arising from simple shear, axial divergence, radial divergence, and rotation to quantify relative displacement across regions of smoothly varying phase. Ambiguity between inverse model solutions representing different deformation modes is mitigated by comparing inverse modeled displacements with LSO observations, implementing reasonable bounds on strain magnitudes, and consideration of deformation modes likely to occur in particular coastal geometries. Inverse modeled displacements closely match LSO observations, giving us confidence in inversion results between and beyond these point measurements. Within the sheltered lagoon, we observe radial convergence, probably driven by thermal stresses, to be the primary mode of deformation. Maximum strains in the lagoon on the order of 10–4 over 12-day periods are observed early in the season, when ice and snow cover are still thin. Outside the lagoon, where fast ice is exposed to dynamic stresses exerted by impinging pack ice, axial divergence and simple shear are the dominant deformation modes. The work here demonstrates this new analytical inverse method for quantifying strain in landfast ice from regular InSAR acquisitions in complement to field observations as a valuable tool for further understanding the mechanics and stability of the landfast ice zone through routine observation opportunities.
The seasonal evolution of sea ice deformation in the Arctic and Southern Oceans
Kyle Duncan, Sinéad L. Farrell, Eric Leuliette, John M. Kuhn
Corresponding author: Kyle Duncan
Corresponding author e-mail: kduncan@umd.edu
Sea ice deformation features, such as pressure ridges, formed by the convergence of ice floes, impact sea-ice–atmosphere and sea-ice–ocean momentum fluxes through ridge sails and keels, respectively. Deformation through ridging provides resilience to summer melt and contributes to the sea ice thickness distribution. Deformation of the Arctic and Southern Ocean sea ice packs has remained poorly understood largely due to a lack of observations at the basin scale. Sea ice models require these observations to better constrain the sea ice thickness distribution. Since its launch in 2018, ICESat-2 has delivered observations of sea ice deformation at short length scales and at the basin scale, providing the insights needed for advancing sea ice parameterizations. The high pulse repetition frequency (10 kHz) and small footprint diameter (~11 m) of the advanced topographic lidar altimeter system (ATLAS) on ICESat-2 results in along-track sampling of ~0.7 m allowing for the detection of individual pressure ridges and deformation at the basin scale. Here we apply the University of Maryland-Ridge Detection Algorithm (UMD-RDA), a sea ice surface tracker, to the ICESat-2 ATL03 global geolocated photon height data product to derive sea ice surface height at the nominal resolution of ~0.7 m. We apply techniques to distinguish individual ridge sails and ridge complexes, and we calculate the height, frequency and spacing between objects. Sea ice parameters such as surface roughness, pressure ridge sail height, ridging intensity, and ridge sail spacing are derived monthly at the basin scale. Ridging intensity, defined as the mean sail height multiplied by the sail frequency, shows that sea ice deformation varies with respect to ice regime and geographic location. Here we examine and contrast the seasonal variability in wintertime (October–April) Arctic sea ice deformation with that of wintertime (March–September) sea ice deformation in the Southern Ocean, and present results for the 2018–22 period.
Towards seamless sea-ice prediction at AWI with global models and ensemble data assimilation
Helge F. Goessling, Svetlana N. Loza, Mahdi Mohammadi-Aragh, Marylou Athanase, Longjiang Mu, Frank Kauker, Michael Karcher, Jan Streffing, Miguel Andrés-Martínez, Lars Nerger, Bimochan Niraula, Tido Semmler, Dmitry Sidorenko
Corresponding author: Helge F. Goessling
Corresponding author e-mail: helge.goessling@awi.de
Despite continuous advances in sea-ice prediction research and development, outperforming rather simple statistical benchmarks remains a challenge for model-based initialized sea-ice prediction on daily to annual timescales. Here, after sketching some key developments and the current state of sea-ice prediction in general, we outline AWI’s efforts to develop seamless sea-ice prediction systems based on global models and ensemble data assimilation. The two main configurations share the same ocean/sea-ice model component, the Finite-volume Sea-ice Ocean Model (FESOM), and the assimilation of a comprehensive suite of ocean and sea-ice observations with an Ensemble Kalman Filter (EnKF) implemented within the Parallel Data Assimilation Framework (PDAF). An uncoupled configuration utilizes atmospheric reanalysis data to force the ocean/sea-ice model, during the assimilation phase with contemporary reanalysis data and during the forecast phase with reanalysis data from previous years. A coupled configuration comprises a dynamic atmospheric model, the Open Integrated Forecast System (OpenIFS). We do not apply data assimilation in the atmospheric component, but explore options to constrain the atmospheric state by spectral nudging of the large-scale winds during the assimilation phase. We present preliminary results and discuss the advantages and disadvantages of the different approaches.
The Sea Ice Dynamics Experiment; observing stress-strain-fracture in sea ice at floe scale
Chris Polashenski, Angela Bliss, David Clemens-Sewall, Pedro Elosegui, Emily Fedders, Erin Fischell, Caileigh Fitzgerald, Jari Haapala, Jennifer Hutchings, Jennifer Hutchings, Mackenzie Jewell, Larson Kaidel, Kelsey Kaplan, Kamhamettu Chandra, Andrew Mahoney, Kevin Manganini, Michael May
Corresponding author: Chris Polashenski
Corresponding author e-mail: chris.polashenski@gmail.com
The Sea Ice Dynamics Experiment (SIDEx) seeks to better understand sea ice mechanical behavior over relatively short (< week) timescales and high (< km) spatial scales. We hypothesize that heterogeneity in ice strength and floe geometry controls how far field stress propagates through the ice pack at these scales, creating stress concentrations that govern ice failure timing and location, possibly deterministically. A scale gap in prior observations of sea ice deformation limits our ability to test this hypothesis. Few observations of ice deformation exist at m–km scales, specifically those scales larger than laboratory studies and smaller than buoy or remote sensing studies. Observations of stress-strain-fracture fields over these scales are needed to investigate the stress state acting on or leading to fractures in natural sea ice. SIDEx has now employed a range of new technologies to fill this gap, collecting a fully integrated set of stress, strain and fracture observations. Observations were collected in landfast ice (targeting thermal stresses), at MOSAiC (stress and strain), and at a 2021 SIDEx camp (full suite) in the Beaufort Sea over scales from 1 m to 10 km capturing (1) internal ice stress, (2) intra-floe elastic or creep strains, (3) the location and size of thermal and mechanical fractures, (4) inter-floe dynamic strains (e.g. floe-floe shear), and (5) the morphology of the ice. We present an overview of the SIDEx field campaign, the datasets collected and findings on the mechanical behavior of ice that seek to better describe rheology, thermal expansion, fracture initiation, ridging, multi-floe stress transfer and deformation scaling processes in drifting pack ice.
Kiledar Singh Tomar, Vishnu Nandan, Torsten Geldsetzer, John Yackel, Dustin Isleifson
Corresponding author: Kiledar Singh Tomar
Corresponding author e-mail: kiledar.tomar@ucalgary.ca
We present the first-ever simulations of Ku-, X- and C-band microwave backscatter of snow-covered sea ice using the higher-order Snow Microwave Radiative Transfer Model (SMRT). The modeled backscatter is validated using surface-based scatterometer observations of snow-covered first-year sea ice (FYI) collected during May 2012 near Resolute Bay, NU in the Canadian Arctic. Ku-, X- and C-band scatterometer observations are acquired quasi-coincident with in-situ geophysical snow measurements. In situ geophysical measurements are used as input parameters to the SMRT model to simulate VV- and HH-polarized backscatter. Observed and SMRT-modelled backscatter, as a function of incidence angle and polarization are compared. Modelled Ku-, X- and C-band backscatter exhibit greater HH than VV backscatter for all incidence angles. Modelled Ku-band backscatter is consistently greater than X-band, followed by C-band backscatter. These results are consistent with measured backscatter. Modelled backscatter indicates that volume scattering is dominant at Ku-band, and surface scattering dominates at C-band. Analyses of the backscatter response to different snow and ice properties indicates that snow grain size, snow thickness and snow density have the greatest effect on Ku-band backscatter, whereas snow salinity has the greatest effect on C-band backscatter. X-band backscatter appears to be influenced by a complex combination of snow properties. These multi-frequency findings improve understanding of variations in the thermodynamic, geophysical and electrical state of snow-covered sea ice and their impacts on microwave interactions. The results demonstrate that SMRT has the potential to be a valuable tool for understanding the backscatter response from snow-covered FYI.
Julien Laliberté, Marcel Babin
Corresponding author: Julien Laliberté
Corresponding author e-mail: julien.laliberte@gmail.com
Important under-ice phytoplankton blooms were recently documented, and their presence was attributed to sufficient under-ice photosynthetically available radiation (uPAR). At the top of the water column, uPAR is generally measured locally or modeled from coarse grid cells; both spatial scales being unfit to assess photosynthetic activity by drifting phytoplankton under the heterogeneous icescape. We present a satellite-based method to get better informed on uPAR, with estimates at medium spatial (~3 km–2) and temporal (~5 d–1) scales. In this approach, uPAR is sandwiched between two values. An extreme value is one in which sea ice completely absorbs the PAR (lower bound), and the other is one in which all PAR not reflected to the atmosphere is transferred to the top of the water column (upper bound). We applied the method to study the seasonal evolution of uPAR under a landfast ice cover (low light regime) evolving to open water (high light regime) and back to the polar twilight (low light regime) at a coastal location in Western Baffin Bay where the Green Edge ice camp took place in 2015 and 2016. We then compared our results to local measurements of uPAR and vertically integrated marine chlorophyll-a. We found that 1) uncertainties of uPAR would benefit from a better assessment of the loss of PAR due to absorption in sea ice; 2) an increase in uPAR was associated with an increase in chlorophyll-a, but more research is required to identify dates of bloom initiation. Overall, the method shows promise as it allows evaluation of the evolution of under-ice light regimes for different locations across the Arctic using only satellite-derived data.
Vaishali Chaudhary, Vishnu Nandan, Julienne Stroeve, Dustin Isleifson
Corresponding author: Vaishali Chaudhary
Corresponding author e-mail: chaudh23@myumanitoba.ca
The stability of landfast ice is a crucial component for the livelihood of people living in northern communities in the Canadian Arctic. Landfast ice is used for hunting, traveling, migration and cultural identity. In response to frequent warm air advection events, several optical satellite-based studies have shown the diminishing stability of landfast ice over the past decades. Hence, regular monitoring and near- to long-term forecasting of sea ice break-up events affecting its stability are essential to improve disaster risk, mitigation and adaptation strategies for the safety and health of northern communities. This research is focused on quantifying these sea ice break-up events and trends in five selected communities: Tuktoyaktuk, Pond Inlet, Paulatuk, Cambridge Bay and Ulukhaktok in the Canadian Arctic between 2016 and 2023 using the European Space Agency’s C-band Sentinel-1 synthetic aperture radar (SAR) data. We examine the links between sea ice fracturing events with wind-driven sea ice dynamics along the coastal regions in these communities. Here, we show a case study from Tuktoyaktuk, mapping regions affected by frequent winter breakout events. Weather station data in Tuktoyaktuk procured from Environment and Climate Change Canada provides information on temperature, wind speed and direction. SAR images are processed to discriminate open water and leads from landfast sea ice using backscattering thresholds. The preliminary results show clear breakouts within landfast sea ice, which are then quantified by applying a grid over the image with each grid cell having a defined size. These quantified breakouts are then correlated with respective wind and temperature data. The study can help in forecasting the low-stability regions within sea ice for providing better navigation to the local community.
Alice Bradley, Annabel Flatland, William Downs
Corresponding author: Alice Bradley
Corresponding author e-mail: alice.c.bradley@williams.edu
Trends towards thinner sea ice are a hallmark of climate change in the Arctic. Whether these trends accelerate in a primarily first-year ice Arctic depends on an annual feedback cycle: shorter ice growth seasons resulting in thinner sea ice, earlier opening/retreat, longer summers and delayed freeze-up. We analyze correlations between freeze-up and melt dates to evaluate whether this feedback process is evident in the Arctic Sea ice seasonal change and melt/freeze climate indicators from satellite data observations. The over-summer process shows consistently high correlations across the Arctic, but the winter process is less broadly supported by the data. Sets of years with similar ice drift patterns (found using k-means clustering of overwinter drift tracks from Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors) show some localized correlations between freeze-up dates in one location and melt dates in another. While this feedback process plays a general role in overall thinning of Arctic sea ice, the weak winter feedback and effects of ice motion suggests that ice ‘memory’ may be short-term and scattered.
Radiative transfer in sea ice: from in-ice angular radiance distributions to optical properties
Bastian Raulier, Raphael Larouche, Christian Katlein, Simon Lambert-Girard, Simon Thibault, Marcel Babin
Corresponding author: Raphael Larouche
Corresponding author e-mail: raphael.larouche@takuvik.ulaval.ca
The Arctic sea ice cover is currently undergoing major changes, most visible in a shift from thick multiyear ice to a seasonal ice cover that is thinner, has a higher melt pond coverage in spring, and gives way to open water earlier during the summer. These changes in ice conditions have a direct impact on under-ice photosynthetically available radiation (PAR, 400–700 nm) for primary producers. To better understand and predict the future of Arctic primary production, it is necessary to measure the optical properties of sea ice and their variation during the season. To shed light on these properties, we propose an innovation, based on the improvements brought by the miniaturization of recreational optical instruments. We show that it is possible to measure the radiative field and its structure with a 360° commercial camera, along its path from the atmosphere to the underlying water column. This method allows a single instrument to obtain all radiometric quantities at a given depth in a single measurement. From these quantities, we demonstrate the feasibility of retrieving the medium inherent optical properties using HydroLight software for radiative transfer simulations. This compact and inexpensive measurement method will undoubtedly contribute to the knowledge of the optical properties of ice and thus allow a better representation of this complex medium in models.
Sea ice drift patterns in a changing Arctic environment
Annabel Flatland, Alice Bradley
Corresponding author: Alice Bradley
Corresponding author e-mail: alice.c.bradley@williams.edu
Sea ice drift is an important factor in trying to quantify many ice feedback processes. This analysis uses the Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors to generate virtual ice buoy drift trajectories over the course of each winter 1978–2020. For several freeze-up locations across the Arctic, including a range of predominantly first and multi-year ice regions, we track ice drift over the winter until either the ice melts or the following September. These tracks are then analyzed using k-means clustering to identify sets of years where ice followed similar drift trajectories. These sets of years reflect transitions from multi-year to first-year ice environments and large-scale patterns in atmospheric (e.g. AO) and ocean circulation.
Chris Polashenski, Larson Kaidel
Corresponding author: Chris Polashenski
Corresponding author e-mail: chris.polashenski@gmail.com
The field of sea ice research has grown rapidly in size in recent years as the importance of sea ice to the global climate system has grown. An ever-increasing proliferation of model parameterizations and algorithms for interpreting remote sensing data are being generated; rapidly improving our understanding of the changing ice system. Many of these represent diverse approaches to address common sensing or prediction challenges. Prominent examples in remote sensing include melt pond coverage, snow depth, ice type classification and ice thickness/freeboard. Each of these examples (as well as many other topics and parameters not listed here) has multiple groups, algorithms and approaches being developed and tested. This diversity of approaches is an excellent sign of a healthy and growing scientific field. In addition to growing the sea ice community, the importance of these problems and the challenges they represent have attracted interest from outside the historic sea ice community, particularly in applied mathematics. As a diversity of approaches increases, however, there is a need to intercompare them. Frequently, however, the datasets against which these approaches are being tested are different for each approach, making it challenging to assess the differences between methods. We will present a concept of ‘Sea Ice Challenge Problems’ along with several early examples for discussion. These ‘SIC Problems’ are pre-packaged data sets that can be used for algorithm testing and/or model validation surrounding parameters with diverse approaches. The data sets have been selected, curated and posted alongside tools and explanatory material that makes them accessible to non-experts. The concept is to give a common framework for inter-comparing multiple algorithms that seek to determine a single parameter. We hope to discuss the shortcomings of the version 1.0 SIC Problems at the meeting and build collaborations for iterating the concept and, by naming and generalizing the concept, to encourage others to lead the development of additional data challenges.
Monojit Saha, Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Thomas Newman, Julienne Stroeve, John Yackel, Dustin Isleifson
Corresponding author: Monojit Saha
Corresponding author e-mail: saham1@myumanitoba.ca
Satellite radar altimetry is widely used to derive basin-scale estimates of snow depth on sea ice and lake ice. However, one of the critical uncertainties identified in the retrieval process is the ambiguous penetration of the Ku-band radar signals through the snow pack. This study focuses on analyzing radar altimetry measurements of snow-covered first-year sea ice (FYI) and lake ice acquired from a polarimetric, surface-based Ku- and Ka-band radar (KuKa radar), collected during the 2021 freeze-up period in Churchill, Canada. We investigate diverse polarimetric and dual-frequency approaches to retrieve snow depth on sea and lake ice from KuKa radar and validate against coincident measurements of snow depth collected from a snow magnaprobe. The dominant scattering horizon of Ku- and Ka-band radar signals will be analyzed, supported by ambient snow pack geophysical conditions. Comparison of snow depths on saline FYI and fresher lake ice under similar meteorological settings will help us understand differences in radar penetration depths, as a function of contrasting snow physical properties and polarimetric radar interactions. Exploring such uncertainties will help improve critical deficiencies in the understanding of satellite level snow depth retrievals on sea and lake ice environments from CRYO2ICE and future satellite altimetry missions such as ESA’s CRISTAL.
A satellite climate data record of sea ice surface temperatures for the Arctic Ocean, 1982–2021
Jacob Høyer, Pia Nielsen-Englyst, Wiebke Kolbe, Tian Tian, Suman Singha, Shuting Yang, Gorm Dybkjaer
Corresponding author: Jacob Høyer
Corresponding author e-mail: jlh@dmi.dk
Sea ice surface temperature (IST) is a crucial parameter for understanding, monitoring and predicting climate change in the Arctic and was recently recognized as an essential climate variable in the 2022 GCOS implementation plan. Within the framework of the Copernicus Marine Monitoring Service Sea Ice Thematic Assembly Center, the first gap-free (L4) of combined sea surface temperature (SST) and IST climate data set of the Arctic (>58° N) has been developed for the period 1982–p 2021. The CDR has been generated using optimal interpolation to combine multiple infrared satellite observations to daily, gap-free fields with a spatial resolution of 0.05 degrees. The product provides a consistent foundations for climate indicators, which can be used to monitor day-to-day variations as well as climate trends in the Arctic Ocean. Validation against in situ measurements validation shows a mean IST difference of 1.52°C and standard deviation of 3.12°C, for skin surface temperatures. For air temperatures from the North Pole (NP) ice drifting stations as well as ECMWF distributed buoys and CRREL buoys, validation shows mean differences to the IST of –p2.35°C, –p3.21°C and –2.87°C and standard deviations of 3.12°C, 3.34°C and 3.36°C, respectively. A stability analysis revealed a very small trend in the mean differences compared with in situ of –0.166°C decade–1, which is comfortably between breakthrough and threshold stability requirements of 0.1 and 0.3°C decade–1, respectively. Analysis of the CDR shows that the surface temperature of the Arctic has risen with about 4.5°C over the period 1982–2021, with a peak warming of around 10°C in the northeast Barents Sea. Finally, the ISTs have been converted to T2m near surface air temperatures using a statistical model and have been compared against CMIP6, ERA-5 and CARRA model results to evaluate the performance of the different models in representing the surface temperature over sea ice.
From regional to Arctic-wide melt pond fraction estimates
Hannah Niehaus, Larysa Istomina, Tim Sperzel, Evelyn Jäkel, Ran Tao, Marcel Nicolaus, Gunnar Spreen
Corresponding author: Hannah Niehaus
Corresponding author e-mail: niehaus@uni-bremen.de
A wide variety of surface types are present in the Arctic: open ocean, sea ice, snow and melt ponds cover the surface, which is thus strongly heterogeneous. Due to the large differences in their albedo, the areal composition of these surface types strongly impacts the radiative feedback and hence the surface energy budget, which is crucial for climate models and future simulations. However, climate models struggle to realistically represent melt ponds. This is caused by the complexity and variability of melt pond formation and evolution and the mismatch between true and observational scales. We have derived a dataset of melt pond fractions from high resolution (10 m) Sentinel-2 satellite imagery, to bridge between in-situ and medium-resolution (300 m–1 km) satellite observations. In-situ measurements are locally and temporally limited but provide high resolution. Medium-resolution satellite observations can cover the complete cloud-free Arctic but can not resolve individual melt ponds. The developed Sentinel-2 product is evaluated by comparison with higher resolution (0.5 m) helicopter-borne and satellite observations measured in June and July 2020 during the MOSAiC campaign. In a next step, the Sentinel-2 derived melt pond fraction product is used to improve Arctic-wide melt pond faction products from medium resolution Sentinel-3 observations. We retrieve melt pond and sea ice fractions from medium-resolution (1.2 km) Sentinel-3 satellite imagery with the MPD algorithm developed by Zege et al. Comparing the Sentinel-3 and Sentinel-2 products indicates an overestimation of melt pond fraction at medium resolution. This may be related to the limitation of this algorithm to two surface types: sea ice and melt ponds. We present a further developed MPD algorithm, including open water as a third surface type. For this purpose we use the temperature history along the drift track as prior knowledge to constrain the algorithm. This leads to a significant reduction in overestimation of Sentinel-3 melt pond fraction, paving the way for improved Arctic-wide melt pond fraction datasets and an enhanced representation of melt ponds in climate models.
Maddie Smith, Bonnie Light, Ran Tao, Marcel Nicolaus, Niels Fuchs, Don Perovich, Philipp Anhaus
Corresponding author: Maddie Smith
Corresponding author e-mail: madisonmsmith@whoi.edu
Sea ice forms a relatively bright, reflective surface on the Arctic Ocean during the sunlit season. Regardless, a significant portion of the incoming solar energy is absorbed by the ice or transmitted into the ocean below, which provides heat for melt and light for biological communities. The partitioning of the solar energy between the atmosphere, ice, and ocean evolves in a non-linear and sometimes episodic manner, particularly associated with the development of melt ponds on the sea ice and weather events which change the optical properties of the ice surface. We quantified this partitioning using collocated albedo and transmission measurements over approximately 150 m of first-year sea ice observed during summer 2020, supplemented by a novel laboratory method for calculating absorption profiles of sampled ice cores. Preliminary conclusions from combining these types of observations suggest how the evolution of solar partitioning is a result of competing effects of changes in inherent optical properties (absorption, scattering) and mass balance changes (melt pond evolution, thinning). Ice itself may get less transmissive as it enters the melt season, as brine and gas inclusions increase in size, even as the ice cover on the whole gets more transmissive due to melt evolution. We in particular examine the impact of episodic events (such as summer snowfall) compared to the longer-term trends in driving the total budget of the sunlit season. Capturing key features of the solar radiative budget in sea ice requires representing both such surface changes as well as physical changes in absorption and scattering of the ice. We make recommendations of considerations for improved future radiative transfer modeling of Arctic sea ice.
Mapping potential timing of under-ice algal blooms from satellite
Julienne Stroeve, Gaelle Veyssière, Carmen Nab, Jack Landy, Bonnie Light, Donald Perovich, Andrew Barrett, Glen Liston, Marion LeBrun, Robbie Mallett
Corresponding author: Julienne Stroeve
Corresponding author e-mail: Julienne.Stroeve@umanitoba.ca
Satellite-based data products can provide key snow and ice variables for estimating how much light penetrates through the sea ice. Until recently, a key limitation had been the lack of a daily sea ice thickness data record as well as ice thickness measurements were limited to the cold season. With new data processing techniques and new satellite sensors, it is now possible to map under-ice photosynthetically active radiation (PAR) on a daily time-scale, and thus the potential timing for when an under-ice algal bloom may occur. This study provides the first pan-Arctic estimates for potential algal bloom onset by combining newly developed daily sea ice thickness products from radar and laser altimetry together with snow depth modeling. Sufficient light to initiate a bloom onset occurs most everywhere in the Arctic Ocean by the end of April, with some regions with deeper snowpacks in spring having enough light by the end of May. Variability in year-to-year potential bloom onset timing over the 2011–20 time-period is largely a function of snowpack variability.
Assessing sea ice lead characteristics with ICESat-2
Oliwia N. Baney, Sinéad L. Farrell, Kyle Duncan, Laurence Connor, Jaemin Eun, Dong (Tony) Chen
Corresponding author: Sinéad L. Farrell
Corresponding author e-mail: sineadf@umd.edu
Sea ice leads, formed through ice dynamical processes, are an important component of the ice cover, directly linking the polar ocean and atmosphere, and regulating the exchange of energy, moisture and momentum between the two. Leads provide a critical sea level reference for the derivation of freeboard and, in turn, ice thickness from laser and radar altimeters. Here we assess techniques for observing leads using multiple, high-resolution remotely sensed datasets collected over Arctic sea ice at the onset of freeze-up. ICESat-2’s Advanced Topographic Lidar Altimeter System (ATLAS) delivers enhanced detection of leads when compared to previous spaceborne altimeters. Its ~11 m footprint and pulse repetition frequency of 10 kHz results in an along-track sampling every ~0.7 m that allows us to resolve very narrow lead features <5 m wide. We investigate the accuracy of ICESat-2 lead detections through comparisons with coincident altimetric and optical data sets acquired during an airborne calibration and validation survey in September 2019. We contrast sea surface height results obtained from the narrow footprint of ICESat-2’s profiling instrument with the swath-mapping capabilities of the airborne laser altimeter. We also evaluate a new algorithm, the Advanced Lead Finder (ALF), for improved lead detection with ICESat-2. ALF aims to reduce the effects of clouds on ICESat-2 lead detections and the misclassification of ‘dark’ leads (surfaces with low photon-rate returns). This allows for the full use of ‘dark’ as well as specular leads for the derivation of sea ice freeboard, resulting in fewer data gaps and an increased number of observations when compared to the existing, ICESat-2 mission-level sea ice freeboard product. To quantify lead characteristics, we examine the sea ice freeboard, lead length and lead frequency distributions obtained from the multiple, high-resolution, coincident airborne and satellite datasets at the study site. Our results inform the development of new sensors and future mission definition for the retrieval of both sea ice freeboard and sea surface height in the ice-covered polar oceans.
Anatomy of the MOSAiC sea ice deformation events
Jari Haapala, Luisa von Albedyll, Jenny Hutchings, Polona Itkin, Thomas Krumpen, Ola Persson, Chris Polashenski, Gunnar Spreen, Matias Uusinoka
Corresponding author: Jari Haapala
Corresponding author e-mail: Jari.haapala@fmi.fi
Formation of sea ice fractures, cracks, leads and linear kinematic features, have a large impact on exchanges of energy and matter between the ocean and atmosphere, surface heterogeneity, and sea ice mass balance. Fracturing also weakens the dynamic strength of pack ice. Based on ice radar, satellite images, and ice drift and stress buoy data we have identified the most significant local ice dynamics events at the Central Observatory. In this presentation, we will provide an anatomy of events that occurred 15–25 November 2019 and 20 March–4 April 2021. The analysis shows where and when large-scale shearing, lead opening and compression occur, with ridging often under shear. In a single spot, these modes of deformation are occurring consecutively but within a few km2 areas, all these modes occur simultaneously. Furthermore, old shear zones, leads, and ridges are reactivated throughout the winter.
Updates and analysis of the on-ice Arctic sea ice thickness archive
Benjamin Holt, Ryan Avila
Corresponding author: Benjamin Holt
Corresponding author e-mail: benjamin.m.holt@jpl.nasa.gov
At the last IGS Sea Ice Symposium in 2019, we presented initial analysis of on-ice sea ice thickness measurements of the Arctic Ocean (On-Ice archive), held at the National Snow and Ice Data Center. This archive consists of measurements primarily made by ice auger, ice coring devices and surface-based electromagnetic induction (EM), consisting of sea ice thickness measurements extending from the earliest records from 1879–81 up to 2015. We have recently added additional records and will show further analysis. While comparatively sparse, the on-ice methods of ice thickness measurements are the such records obtained at least until the late 1950s, when ice draft measurements from upward-looking sonar data were collected by submarines. Also, on-ice measurements are still the most accurate compared to satellite and airborne collections. In putting together these records, it became clear that in situ sea ice thickness data were acquired for multiple reasons. Many were collected for safety or on limited scales. Eventually, on-ice methods were obtained to examine details of varying sea ice floes and in varying seasons. With the development of electromagnetic induction techniques, surface collections by EM were made to characterize larger expanses of varying sea ice, which significantly increased the number of records. More often than not, surface EM data were collected coincidently with independent ice measurements made by auger as well as snow depth in order to correct the EM data. On a limited scale rather remarkable sets of measurements were made by drilling extensive numbers of holes over thick multiyear ice in grid patterns, to understand the relationship of surface and under-ice topography. Our initial results showed that the most useful time series is probably the first-year ice measurements made in March–May after a full winter growth season. These were uniform with little variation over time until approximately the 1990s when an apparent slight decrease was seen, along with more variation. In this presentation, along with an updated error analysis, the winter first year ice measurements will be updated. The relationships of thickness, snow depth and freeboard will be presented. Lastly, we will examine selected Arctic regions where a larger number of on-ice data are available which can be compared with more recent observations.
Developing the Arctic Sea ice attribution system: the role of snow depth data assimilation
Mahdi Mohammadi-Aragh, Frank Kauker, Svetlana N. Losa, Helge F. Goessling, Michael Karcher
Corresponding author: Mahdi Mohammadi-Aragh
Corresponding author e-mail: mahdi.aragh@awi.de
Under the current conditions of decreasing Arctic sea ice and increasing human activity in the polar oceans, a reliable Arctic sea ice and snow prediction system would allow a number of related scientific and socio-economic needs and requirements to be met. We are developing such a quasi-operational forecasting system that combines numerical model simulations and observations of the Arctic ocean, sea ice and snow. The system consists of FESOM2, a sea-ice–ocean model augmented by assimilation of sea-ice and ocean observations. The data assimilation component was previously developed as part of the AWI coupled prediction system and is based on the use of an ensemble Kalman filter that is part of the parallel data assimilation framework (PDAF). Originally, the assimilated observational data included sea ice concentration, sea ice thickness and sea ice drift, sea surface temperature and salinity, and sea surface height. As a major extension of our uncoupled data assimilation system, we included the assimilation of snow depth; precisely, we assimilate the AMSR-2 product from the Universiät Bremen on Arctic sea ice. The extended system is evaluated using experiments conducted for the period 2012– 22 and preliminary results are presented and discussed.
Matthias Wietz, Taylor Priest, Ellen Oldenburg, Wilken-Jon von Appen, Ovidiu Popa, Sinhue Torres-Valdez, Christina Bienhold, Katja Metfies, Magda Cardozo-Mino, Julian Merder, Thorsten Dittmar, William Boulton, Thomas Mock, Bernhard Fuchs, Rudolf Amann, Antje Boetius
Corresponding author: Matthias Wietz
Corresponding author e-mail: matthias.wietz@awi.de
The Arctic Ocean is experiencing unprecedented changes because of climate warming, necessitating detailed analysis of the ecology of biological communities to understand ecosystem shifts. Here, we show the impact of sea-ice cover and Atlantic water influx on bacterial communities in the East Greenland Current (Fram Strait) using a multi-year, high-resolution amplicon dataset and an annual cycle of long-read metagenomes. Densely ice-covered polar waters harboured a temporally stable microbiome, whereas low-ice cover and Atlantic water influx coincided with seasonally fluctuating populations. Sea-ice cover had the strongest influence on bacterial community functionality. Communities under high ice cover were rich in genes for the degradation of bacterial and terrestrial-derived organic matter, such as D-amino acids and ketones, and inorganic substrate metabolism. Under low ice cover, there were more genes for the metabolism of phytoplankton-derived carbohydrates (e.g. laminarin) as well as dissolved organic nitrogen and sulfur compounds (e.g. taurine and trimethylamine). These functional differences between Arctic and Atlantic water masses indicate a progressive ‘biological Atlantification’ of the warming Arctic Ocean, where resident bacterial populations are replaced by invaders from the North Atlantic, with probable consequences for biogeochemical cycles. Comparison with MOSAiC and TARA Arctic revealed a number of metagenome-assembled genomes (MAGs) with wide distribution throughout the Arctic Ocean, suggesting the presence of key Arctic bacteria whose abundance might be diminished in the warming Arctic. The impact of sea ice on microbial community dynamics was underlined by incubation experiments with melting sea ice, showing that ice microbes and substrates are transferred from sea ice to seawater during melt, illustrating biological–chemical connectivity.
Relation of passive microwave L-band signal to sea ice physical properties during ice growth phase
Marcus Huntemann, Justus Heilingbrunner, Gunnar Spreen
Corresponding author: Marcus Huntemann
Corresponding author e-mail: marcus.huntemann@uni-bremen.de
Passive microwave remote sensing is a long-established tool for remote sensing of sea ice. Since 2010, also observations at low microwave frequencies such as L-band (1.4 GHz) have been available from different satellites such as SMOS, Aquarius and SMAP. Different studies suggested that the L-band signal is related to the sea ice thickness, among other physical properties. However, physical models are struggling to explain the observed signal because of high uncertainties in the parameters, such as salinity. With the long time-series of L-band observations, we are investigating the brightness temperature evolution in the Arctic and Antarctic for the initial ice growth phase up to thick first-year ice. We use a combination of satellite observation from SMOS and a thermodynamic model to separate the different physical effects contributing to the L-band signal, where, in particular, we study ice thickness, snow depth and temperature. The investigation includes 13 years of SMOS observations from 2010–23 for different regions of growing sea ice in the Arctic and Antarctic. We investigate in relation to temperature, snow depth and ice thickness while treating the modeled ice and snow condition with a high uncertainty as no measurements are used in this study. The regional differences of brightness temperature evolution are found to be small compared to overall variability in brightness temperature evolution during the ice growth phase.
Ruzica Dadic, Bin Cheng, Roberta Pirazzini, Julia Martin, Brian Anderson, Greg Leonard, Inga Smith, Natalie Robinson, Petra Heil, Mario Hoppmann, Henning Löwe, Lauren Vargo, Martin Schneebeli
Corresponding author: Ruzica Dadic
Corresponding author e-mail: ruzica.dadic@slf.ch
Landfast ice plays a significant role in climate and ecosystems in Antarctic coastal regions. From October–December 2022, we investigated the physical properties of snow and sea ice on Antarctic landfast ice in McMurdo Sound. The sea ice is fastened to Ross Island and the Ross Ice Shelf. Considering the presence of relatively cold and fresh ice shelf cavity water, there are many platelets beneath McMurdo Sound sea ice. The season’s unique sea ice conditions provided the ideal laboratory to study a range of snow and ice conditions and to differentiate between sea ice and snow drivers for the atmosphere–sea-ice–ocean system. Additional to regular snow temperature profile measurements, we deployed three thermistor-string-based snow and ice mass balance apparatus (SIMBA) at the beginning of October 2022. The initial snow, ice and platelet thickness at sites A, B and C was 0.14 m/2.4 m/1.8 m, 0.01 m/1.0/0.65 m and 0.05&thinsplm/0.82&thinsplm/0.23 m, respectively. The SIMBAs at B and C sites were recovered on 3.12.2023, while the SIMBA at site A is still operating. SIMBA temperatures revealed a clear snow–ice–ocean interface, and the data are potentially helpful in understanding better the ice–ocean interaction. Furthermore, we see a clear influence of the snow cover on sea ice temperatures, confirming snow to be a significant driver of sea ice evolution.
Microwave emission of snow and sea ice during the MOSAiC expedition
Gunnar Spreen, Marcus Huntemann, Lars Kaleschke, Philip Rostosky, Julienne Stroeve, Rasmus T. Tonboe
Corresponding author: Gunnar Spreen
Corresponding author e-mail: gunnar.spreen@uni-bremen.de
For 50 years, satellite microwave radiometer observations have provided one of the longest time series about the state of Arctic. Without them the strong decrease in Arctic sea ice cover during recent decades could not have been monitored daily, Arctic-wide, and independent of cloud and illumination conditions. For a better physical interpretation of the satellite microwave signal a combination of in-situ microwave radiometers observing the sea ice and measurements of the snow and sea ice physical properties are needed. The MOSAiC drift expedition from October 2019 to September 2020 offered the opportunity to perform such combined measurements for a full seasonal cycle. Microwave radiometers measuring between 0.5 and 89 GHz were deployed on the ice and on the ship. While ice dynamics, logistics and technical failures reduced the available data during some periods, at six frequencies observations are available from all seasons. Strongest brightness temperature variability is observed during atmospheric events such as warm air intrusion and rain on snow. However, longer-term brightness temperature changes differ for different frequencies and can only partly be linked with temperature changes. Residuals, not explainable by temperature changes directly, are mostly associated with the natural evolution of snow and ice conditions over the course of the year during the expedition. This includes effects such as sea ice growth and melt, snow accumulation, melt and metamorphism, among others. We will provide a first joined analysis of this combined microwave radiometer dataset. Measurements will be compared with results from microwave emission models forced by snow, ice and environmental conditions measured on the ice floe at the same time. While not representative for a wider region the in-situ observations will be contrasted with the temporal evolution of microwave brightness temperatures measured by space-borne radiometers. Such analysis will support method development and contribute to upcoming satellite missions like CIMR and AMSR3.
Examining the evolution of ice thickness and roughness with ICESat-2
Sinéad Louise Farrell, Kyle Duncan
Corresponding author: Sinéad Louise Farrell
Corresponding author e-mail: sineadf@umd.edu
With the sustained loss of the oldest sea ice, the Arctic is rapidly transitioning to a predominantly seasonal ice cover. In the future, we may expect that ice topography will become dominated by the roughness and thickness characteristics of first- and second-year sea ice. Ice roughness accumulates throughout the growth season, and depending on its location, rougher ice can survive dissipation through melt or advection, leading to further deformation and roughening in subsequent seasons. The representation of ice surface roughness and its variability due to the loss of older Arctic ice is however poorly captured in sea ice models. Leveraging high-resolution, year-round observations provided by ICESat-2, we examine variations in roughness across the Arctic Ocean as a function of both time and geographical area. Surface roughness, as measured by laser altimeters, describes all sources of ice deformation due to convergence and divergence, and includes hummocks as well as wind-driven undulations on the ice surface due to snowdrifts and sastrugi in winter, and the roughness of the surface scattering layer in summer. Tracking the evolution of roughness throughout the winter growth season we find that both mean and modal ice roughness increase by over 50% at the basin scale. In the early growth season (October to January) the roughness distribution is bi-modal but later (February to April) the distribution becomes unimodal, with changes dues to the production and deformation of young ice during the early months of winter. By the time the ice cover reaches its winter maximum, surface roughness and deformation are twice as large in the multiyear ice zone than in the seasonal ice zone, and the distribution of surface roughness is best fit by an exponentially modified Gaussian distribution. However, our results also confirm that deformation varies not only with ice regime but also with geographic location. Localized deformation in the seasonal ice zone, due to convergence against a static land/ice boundary, can result in areas with roughness commensurate with that found in multiyear ice. Moreover, deformation is greatest along the land boundaries of the multiyear ice zone and is a factor of two larger than the deformation characteristics of multiyear ice at more northerly latitudes in the central Arctic. We also examine the covariance of surface roughness with ice age and thickness, to determine the characteristics of deformation for each ice thickness category.
Snow refreeze as one of the mechanisms of Artic sea ice ridge consolidation
Evgenii Salganik, Benjamin A. Lange, Dmitry Divine, Polona Itkin, Christian Katlein, Marcel Nicolaus, Mario Hoppmann, Knut V. Høyland, Mats A. Granskog
Corresponding author: Evgenii Salganik
Corresponding author e-mail: salganikea@gmail.com
During the freezing period, the consolidated part of sea ice ridges is usually up to 1.6–1.8 times thicker than surrounding level ice. Meanwhile, during the melt season, ridges are often observed fully consolidated, but this process is not fully understood. We present the evolution of the morphology and temperature of a first-year ice ridge studied during MOSAiC from its formation to advanced melt. From October to May the draft of first-year ice at the MOSAiC coring site increased from 0.3 m to 1.5 m, while from January to July the ridge consolidated layer thickness reached 3.9 m. We observed several types of ridge consolidation. From the beginning of January until mid-April, the ridge consolidated slowly by heat loss to the atmosphere with a total consolidated layer growth of 0.7 m. From mid-April to mid-June, there was a rapid increase in ridge consolidation rates despite conductive heat fluxes did not increase. In this period, the mean thickness of the consolidated layer increased by 2.2 m. Our observations suggest that this sudden change was related to the transport of snow-slush inside the ridge keel via adjacent open leads that decreased ridge macroporosity which could result in more rapid consolidation. Such observations are important for the mass balance of deformed sea ice and snow.
neXtSIM-DG – A next generation discontinuous Galerkin sea ice model
Veronique Dansereau, Christian Lessig, Einar Ólason, Pierre Rampal, Piotr Minakowski, Thomas Richter
Corresponding author: Thomas Richter
Corresponding author e-mail: thomas.richter@ovgu.de
We present neXtSIM-DG, the novel sea ice model that is being created as part of the Scale Aware Sea Ice Project (SASIP). neXtSIM-DG is a continuum sea ice model that combines several new model paradigms at once: besides established rheologies we use Bingham–Maxwell constitutive models and the Maxwell–Elasto–Brittle model. The discretization is based on higher order continuous and discontinuous finite elements and finally, the C++ implementation uses modern data structures that allow for efficient shared-memory parallelization and are ready for GPU acceleration. These aspects all serve to better reflect the different scales of sea ice dynamics in space and time. In this talk, we review the basic features of the modelling, but also present some details of the numerical realization. In particular, we study the effect of high order discretization and the role of different rheologies.
Connor Nelson, Julienne Stroeve, Michel Tsamados, Thomas Lavergne, Jack Landy, Lu Zhou, Rosemary Willatt, Fabrizio Baordo
Corresponding author: Connor Nelson
Corresponding author e-mail: ucfaajn@ucl.ac.uk
Accurate estimations of sea ice thickness are essential for understanding the current state of Earth’s polar regions and predicting their future. Due to their large spatial coverage and short revisit time, satellite altimeters provide the most popular source of information to estimate and monitor sea ice thickness on pan-Arctic and pan-Antarctic scales. However, snow on sea ice inflicts significant errors upon these altimeter-derived estimates, with a lack of knowledge in the depth of snow overlaying the sea ice at the time and location of measurement holding the majority share of the overall thickness uncertainty. Despite methods to obtain estimates of snow depth on sea ice from satellite radiometers existing for decades, there is no current polar-orbiting satellite that includes an altimeter in addition to a radiometer which operates at the conventional frequencies to utilize these methods. In this study, we present the usage of an unconventional combination of K-band and Ka-band brightness temperatures from dual-frequency radiometers onboard Sentinel-3 and AltiKa, to derive along-track snow depth estimates that coincide with their respective altimeter measurements. We then use these estimates in the along-track freeboard to sea ice thickness conversion in an attempt to reduce snow depth-induced uncertainties in sea ice thickness. We compare both the retrieved snow depths and sea ice thicknesses with existing products in the Arctic and Antarctic, and look towards how radiometers on future missions such as CRISTAL may provide additional information with which we can more accurately monitor sea ice thickness from space.
Kinematic effects of sea-ice breakup
Petra Heil, Joey Voermans
Corresponding author: Petra Heil
Corresponding author e-mail: petra.heil@utas.edu.au
Sea ice sits at a three-dimensional interface between ocean and atmosphere and the glacial/ice-sheet/coastal fringe and open ocean. It is an active member in a tightly coupled Earth system, straddling climate and ecosystem components. The marginal ice zone (MIZ) is a highly dynamic region, with a strong seasonal evolution and with active energy and mass exchange between system components. With the recent demise of not only the Arctic sea ice but also the Antarctic summer and winter sea-ice cover, understanding the processes that shape the MIZ is of utmost importance to improve our knowledge and to inform numerical simulations. Ocean waves govern sea ice through stress, ice-floe breakup, tides and surface currents. Sea ice, on the other hand, affects waves through attenuation and reflection. This complex interplay is difficult to observe in situ and remains elusive for a range of remote sensing sensors (i.e. due to predominant cloud cover in the region). Here, we discuss a multi-pronged approach to obtain in situ and remotely sensed observations as well as information obtained from process-based modelling to better understand i) thermodynamic processes in the MIZ and ii) ice-floe break-up. Our study explores the different phases in the seasonal morphology of the Antarctic MIZ.
Impacts of recent Antarctic sea-ice extremes
Petra Heil, Edward Doddridge, Will Hobbs, long list of co-authors
Corresponding author: Petra Heil
Corresponding author e-mail: petra.heil@utas.edu.au
Antarctic sea ice has experienced five extreme events in the last decade: three record lows and two record highs. These extreme sea ice events have wide ranging impacts on the ocean, other cryopsheric components, the Southern Ocean ecosystem as well as far-field repercussions. Extreme low summer sea ice results in an increased loss of multiyear fast ice, increases in coastal exposure and change the seasonality of the sea-ice cycle. Surface ocean warming during the summer is observed due to the ice-albedo feedback, resulting in changes to the rate of water-mass transformation. We find that ice-shelf calving is correlated with sea-ice area, so that years with less sea ice show increased calving. Within the annual cycle, prolonged open water affects the seasonality of surface phytoplankton blooms. In addition, changes to the sea-ice seasonal cycle alter the input of iron from melting sea ice, subsequently modifying primary productivity. Under-ice algae are strongly affected by changes to the sea-ice coverage, and years with less ice show substantially reduced under-ice primary productivity. The impacts on higher trophic levels are complex but include habitat loss and impacts on prey availability. The loss of coastal fast ice in the summertime causes logistical challenges for Antarctic fieldwork and resupply missions for Antarctic research stations. Changes in the sea-ice and fast-ice seasonality as well as in the physical properties of the ice have profound effects on coastal and ice-infested water operations, requiring increased observations and analysis of the ice conditions. Changing accessibility of the Southern Ocean may lead to renewed tensions around Antarctic treaty negotiations.
Torbjørn Eltoft, Sebastian Gerland, CIRFA 2022 cruise shipboard scientific team
Corresponding author: Torbjørn Eltoft
Corresponding author e-mail: torbjorn.eltoft@uit.no
In April/May 2022, RV Kronprins Haakon was the platform for Norway’s first ship-based Arctic research expedition with a focus on satellite remote sensing of floating ice, visiting the western Fram Strait to collect ground truth data for the validation of satellite remote-sensing products. The cruise was a main activity of the Centre for Integrated Remote Sensing and Forecasting for Arctic Operations (CIRFA). The expedition’s main goal was to collect ground-truth data for validating remote sensing products for sea ice, icebergs and ocean. The science team consisted of 33 scientists and engineers from Norway and France. In addition to the planned studies in conjunction with satellite remote sensing, several other synergetic projects addressed changes in sea ice and ocean. Validation of sea ice remote sensing products tells us more about how accurate and reliable their information is. To retrieve ground-truth validation data at a multitude of spatial scales, especially for synthetic aperture radar (SAR) satellite imagery, the science team collected data and samples with surface information ranging in scale from micrometres, inferred from snow pits and sea ice coring sites, to kilometres, inferred from transects and drone data. In addition, autonomous sensors were deployed in sea ice and ocean to reveal sea ice and ocean changes and dynamics. Relevant validation parameters such as surface roughness, temperature, density, salinity and internal microscopic structure of snow and sea ice were measured during stops in the ice. Ice and snow thickness was measured with transects walking along lines on the ice. A laser roughness profiler was used to reveal surface topography characteristics, and analysis of snow pit measurements and ice cores revealed the physical properties of snow and sea ice. Validation of satellite remote sensing requires that the ground-based measurements are geographically co-located with satellite acquisitions and coincide in time. During the expedition, this was regularly achieved. A whole suite of satellite images was acquired, including scenes from the European Space Agency’s Sentinel-1 and the Canadian RADARSAT-2 satellites. The combined ground truth and satellite measurements will allow future studies to address important research questions in Arctic remote sensing and development of new technologies. Here, we will give an overview on the expedition and show some preliminary results from the data and sample analyses.
Future projection of ice-algal production in the Arctic Ocean: model intercomparison
Yuanxin Zhang, Eiji Watanabe, Hakase Hayashida
Corresponding author: Yuanxin Zhang
Corresponding author e-mail: yxzhang@jamstec.go.jp
Ice algae (IA) play a fundamental role in the polar biogeochemical cycle. IA not only regulate the carbon cycle but also act as an important food source for zooplankton and benthos in the marginal sea-ice zone. The response of the IA community to remarkable Arctic sea ice retreat is of great research interest. Due to limited observational data, regional differences and long-term variation of IA are not understood well. An international project, the Ice Algae Moel Intercomparison Project phase 2 (IAMIP2) is ongoing to address these scientific questions and estimate the uncertainties among different models and future climate scenarios. Historical (1958–2018) and future projection experiments (2015–2100) were conducted by a global sea-ice–ocean model (ACCESS-OM2, (AO)) and an Arctic Ocean regional model (COCO-Arctic NEMURO (CN)), respectively. The research target region is the entire Arctic Ocean. For atmospheric forcing, JRA55-do and EC-Earth3 output under the shared socioeconomic pathway (SSP5-8.5) were used in historical and future projection experiments, respectively. In this study, we analyze three phases of the entire experiment period (1958–2100): phase 1 (1979–2018), phase 2 (2021–60), phase 3 (2061–2100) in four major subregions (Chukchi Sea, Canada Basin, Eurasian Basin, Barents Sea). The two models show similar spatial pattern of ice-algal production (ice-PP), which is high in the Arctic shelf areas and low in the central basins in all phases. The highest ice-PP is simulated in the Chukchi Sea and the lowest ice-PP in the Barents Sea among four subregions. The AO model presents higher ice-PP than the CN model, this difference caused by higher nitrate concentration both in sea ice and ocean surface in the AO model. Both AO and CN models show the fastest ice-PP decline in phase 2, caused by the rapid decrease in sea ice and ocean nitrate concentration. Sea ice concentration in spring does not show significant decrease during phases 1-3, indicating that the ice-PP decline is not caused by habitat loss. In spite of the different light condition between two models, its impact on ice-PP variation is less significant than nitrate. Therefore, it is suggested that nitrate concentration is the dominant factor for future changes in ice-PP.
Marc Oggier, Bonnie Light, Kristin Timm, Niels Fuchs, Cody C. Owen, Madison M. Smith, Amy Lauren, MOSAiC Sea Ice Coring Consortium
Corresponding author: Marc Oggier
Corresponding author e-mail: moggier@alaska.edu
During the MOSAiC Expedition drift, we follow the evolution of both first-year (FYI) and second-year (SYI) ice. We tracked a suite of physical and ecological properties derived from discrete samples obtained by coring. The cores collected in parallel for stratigraphy analysis allow the creation of a continuous record of the evolution of the sea ice microstructure and will support the analysis of the collocated properties. While sea ice structural properties occur over a wide range of scales, their foundation lies in the arrangement of ice crystals and inclusions of brine, gas, and entrained impurities. We are using a combination of vertical and horizontal, thick (~5 mm thick) and thin (~<0.5 mm thick) sections to quantify the size and orientation distribution of crystal and both brine and gas inclusions, map the ice texture (granular, columnar, lamellar, platelet), and characterize the transition zone between textural domains or strong micro-structural gradient. Following a month-long laboratory work, we used the ColorIce algorithm for the segmentation and classification of thin sections. Here, we present preliminary results for early and late growth, late growth and melt season for both SYI and FYI.
Renée Mie Fredensborg Hansen, Henriette Skourup, Eero Rinne, Knut Vilhelm H&oring;yland, René Forsberg
Corresponding author: Renée Mie Fredensborg Hansen
Corresponding author e-mail: rmfha@space.dtu.dk
In July 2020, the European Space Agency (ESA) raised the orbit of CryoSat-2 to align periodically with NASA’s ICESat-2. This campaign was dubbed CRYO2ICE and allowed for near-coincident radar and laser altimetry separated by approximately 3 hours. For sea ice, one important aspect is deriving snow depth on sea ice through the difference in snowpack penetration. Former studies have achieved this on monthly scales and at pan-Arctic coverage, but CRYO2ICE will allow this along the satellite orbit. This is especially interesting for the upcoming launch of CRISTAL (the Copernicus Polar Ice and Snow Topography Altimeter) in 2027, which will carry the first-ever dual-frequency altimeter in space, and where snow depth on sea ice is one of the main mission objectives. Therefore, utilizing CRYO2ICE and investigating the possibility of deriving snow depth on sea ice at orbit-scales is of high priority. The CRYO2ICE phase 1 campaign ran for 2 years focusing on the Northern Hemisphere and in the summer of 2022, the orbit was altered yet again for CRYO2ICE phase 2, now focusing on the Southern Hemisphere. In December 2022, the first ever airborne under-flight beneath a CRYO2ICE track was obtained through the CryoVEx/DEFIANT projects in the Weddell Sea, which provides an excellent opportunity to compare near-coincident radar and laser altimetry. The airborne campaign carried amongst other a laser scanner, Ku/Ka-band radar, and a snow radar, all of which will be relevant to compare with the spaceborne observations and will allows us for the first time to investigate how well we can estimate snow depth on sea ice along the satellite orbit. This study leverages the airborne data from CRYO2ICE/DEFIANT Antarctic 2022 campaign. We use current methodologies and operational products available, which are perceived mature for the Arctic, but are challenging for the Antarctic due to the different sea ice regime. We also use freeboards observations (the elevation of sea ice above the local sea level) providing information about the sea ice topography, along with derivation of snow on sea ice, and these will be compared with the airborne observations. Here, we investigate how well the current methods are at obtaining Antarctic sea ice topography, and how well we can derive snow depth from dual-frequency satellite observations over this particular sea ice pack.
Sea ice thickness in the western Ross Sea
Daniel Price, Wolfgang Rack, Christian Haas, Pat Langhorne, Greg Leonard, Petra Heil, Steven Fons, Nathan Kurz
Corresponding author: Daniel Price
Corresponding author e-mail: daniel.pric@canterbury.ac.nz
Using airborne measurements, we provide a first direct glimpse of the sea ice thickness distribution in the western Ross Sea, Antarctica, where the distinguishing sea ice process is the regular occurrence of the Ross Sea, McMurdo Sound, and Terra Nova Bay polynyas. Two flights in November 2017 over a length of 800 km reveal a heavily deformed ice regime with a mean thickness of 2.0 ± 1.6 m. Supported by satellite image analysis, we identify regional variability in ice thickness based on formation history. Sea ice thickness gradients are highest within 100 and 200 km of the Terra Nova Bay and McMurdo Sound polynyas, respectively, where the mean thickness of the thickest 10% of ice is 7.6 m. Overall, about 80% of the ice is heavily deformed, concentrated in ridges with thicknesses of 3.0–11.8 m. This is evidence that sea ice is much thicker than in the central Ross Sea. We compare near-coincident CryoSat-2 satellite altimeter data to the EM thickness measurements, which indicates that the altimetry method is underestimating the true sea ice thickness distribution by ~50%.
Multidisciplinary Arctic system studies: a tribute to Dr David G. Barber
John Yackel, Feiyue Wang
Corresponding author: John Yackel
Corresponding author e-mail: yackel@ucalgary.ca
Dr David G. Barber was one of Canada’s most influential and accomplished Arctic researchers, who passed away unexpectedly in April 2021. Dr Barber was first known for his ground-breaking work on snow over sea ice and application of satellite technologies for their characterization. Throughout his career, Dr Barber also championed a systems approach that crossed disciplines, sectors and knowledge systems. In doing so, he built and led many major research teams, networks and infrastructure projects in tackling some of the most pressing issues related to climate and environmental changes in the Arctic, their implications to Inuit and other Indigenous peoples, and teleconnections with other regions. In this presentation, we honour the memory of Dr Barber by reflecting on some of his work and legacy.