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Rathwell, K.J. 'She is Transforming ...': Inuit Artworks Reflect a Cultural Response to Arctic Sea Ice and Climate Change. Melnikov, V.V. Observations of Annual Walrus (Odobenus rosmarus divergens) Migrations in [...]

The article presents a reply by S. Venkatesh and colleagues to comments made by J. R. Marko and D. B. Fissel about their study, On the Deterioration of Icebergs in the Marginal Ice Zone. According to Venkatesh and colleagues, Marko and Fissel point to the many difficulties and expense in obtaining the necessary data to predict the deterioration of icebergs in an operational time setting. They pointed out that they are confident of the calculated deterioration rates. They said that while the calved iceberg fragments under the existing environmental conditions constitute only 2 to 3% of the original masses, the deterioration rates will increase with increasing water temperatures and sea state conditions.

Abstract: Canada's commercial seal hunt warrants close examination in that it is the largest kill of marine mammals on earth, it exists for commercial reasons, it targets deep diving seals with unique physical adaptations, and it is conducted in a particularly remote and uncontrolled environment amidst unstable sea ice and extreme weather conditions. For these reasons, commercial sealing in Canada has been the subject of regular veterinary scrutiny for more than five decades. In that time, despite repeated recommendations and some changes to the regulations, considerable evidence continues to be presented during each new season of poor welfare outcomes for seals. To add to the discussion we (Butterworth and Richardson) (2013) [1] reviewed multiple studies on commercial sealing, government reports, trade journal articles and recommendation reports, in an attempt to answer the question of why, despite the efforts of veterinary advisors and government to improve the situation, seals continue to die in inhumane ways. In examining the available evidence, the environment in which commercial sealing occurs, and the physical adaptations of seals, the authors concluded that generally accepted principles of humane slaughter cannot be implemented effectively and consistently in the context of commercial sealing. [Copyright &y& Elsevier]

This document is a closure response to a discussion on the prevention of water intake blockage by ice during supercooling events. The authors thank the discussers for their input and acknowledge that the impact of slush ice on intakes, which occurs after the supercooling event, was not covered in the paper. The paper focused exclusively on water intake blockage during supercooling events, as stated in the title and introduction. The authors explain that this focus was necessary due to the large amount of material already included and the need to capture all methods, reliable or not, that have been proposed in the past. The authors also address terminology concerns related to the forms of ice during supercooling events and afterward. They note that a consistent and widely accepted terminology for underwater ice forms does not currently exist. Overall, the paper provides a summary of solutions for water intake blockage during supercooling events and acknowledges that a comprehensive report covering all ice problems at water intakes, including the impacts of slush ice, remains to be written. [Extracted from the article]

The MET Norway Ice Service (NIS) celebrated its fiftieth year as a formal operational sea ice information provider in 2020. Prior to the 1970's, support to navigation had started off with ad-hoc observations from coastal stations on Svalbard in the 1930's, before developing as a research programme in the 1960's. Activity in the region has steadily increased, and now the NIS also supports a large number of research, tourist, and resource exploration vessels, in addition to the ice chart archive being a resource for climate change research. The Ice Service has always been at the forefront in the use of satellite Earth Observation technologies, beginning with the routine use of optical thermal infrared imagery from NASA TIROS and becoming a large user of Canadian RADARSAT-2 Synthetic Aperture Radar (SAR), and then European Copernicus Sentinel-1, in the 2000's and 2010's. Initially ice charts were a weekly compilation of ice information using cloud-free satellite coverage, aerial reconnaissance, and in situ observations, drawn on paper at the offices of the Norwegian Meteorological Institute (MET Norway) in Oslo. From 1997 production moved to the Tromsø office using computer-based Geographical Information System (GIS) software and the NIS developed the ice charting system Bifrost. This allowed the frequency of production to be increased to every weekday, with a greater focus on detailed sea ice concentrations along the ice edge and coastal zones in Eastern Greenland and in the Svalbard fjords. From 2010, the NIS has also provided a weekly austral summer ice chart for the Weddell Sea and Antarctic Peninsula. To further develop its capabilities, NIS engages in a number of national and international research projects and led the EU Horizon 2020 project, Key Environmental monitoring for Polar Latitudes and European Readiness (KEPLER). This paper summarises the overall mandate and history of the NIS, and its current activities including the current state of routine production of operational ice charts at the NIS for maritime safety in both the Arctic and Antarctic, and future development plans. [ABSTRACT FROM AUTHOR]

Aiming at the characteristics that the signal noise ratio (SNR) gradually decreases from the near to far range of the swath, an adaptive phase filtering algorithm based on Goldstein filtering and combined with multiple quality-guided graphs was proposed. Firstly, the components used to determine the filtering parameters were obtained through residue density, pseudo-coherence coefficient and pseudo-SNR, the three quality-guided graphs. Then, the filter parameters were calculated by weighting the three components. Finally, the size of filtering window was determined according to the account of residues, and the interferometric phase noise was removed in frequency domain. Simulated data, TSX/TDX data and airborne interferometric imaging radar altimeter data were used to verify the performance of the new algorithm. Compared with the results of Goldstein filtering and its improved algorithms, the results showed that the proposed algorithm can effectively filter out phase noise while maintaining the edge characteristics of interferometric fringe. The section of filtering result can well match with the section of simulated pure interfeometric phase. Moreover, the algorithm proposed in this paper can effectively remove the noise in the interferogram of TSX/TDX sea ice data, and the residues' filtering rate was above 86%, which can effectively remove the phase residues of the sea ice surface while maintaining the characteristics of the sea ice edge. Experimental results showed that the new algorithm provides an effective phase noise filtering method for imaging radar altimeter data processing. [ABSTRACT FROM AUTHOR]

The Fengyun-4B (FY-4B) satellite is currently the primary operational geostationary meteorological satellite in China, replacing the previous FY-4A satellite. The advanced geostationary radiation imager (AGRI) aboard the FY-4B satellite provides an operational sea surface temperature (SST) product with a high observation frequency of 15 min. This paper conducts the first data quality assessment of operational SST products from the FY-4B/AGRI using quality-controlled measured SSTs from the in situ SST quality monitor dataset and foundation SSTs produced by the operational sea surface temperature and sea ice analysis (OSTIA) system from July 2023 to January 2024. The FY-4B/AGRI SST product provides a data quality level flag on a pixel-by-pixel basis. Accuracy evaluations are conducted on the FY-4B/AGRI SST product with different data quality levels. The results indicate that the FY-4B/AGRI operational SST generally has a negative mean bias compared to in situ SST and OSTIA SST, and that the accuracy of the FY-4B/AGRI SST, with an excellent quality level, can meet the needs of practical applications. The FY-4B/AGRI SST with an excellent quality level demonstrates a strong correlation with in situ SST and OSTIA SST, with a correlation coefficient R exceeding 0.99. Compared with in situ SST, the bias, root mean square error (RMSE), and unbiased RMSE (ubRMSE) of the FY-4B/AGRI SST with an excellent quality level are −0.19, 0.66, and 0.63 °C in daytime, and −0.15, 0.70, and 0.68 °C at night, respectively. Compared with OSTIA SST, the bias, RMSE, and ubRMSE of the FY-4B/AGRI SST with an excellent data quality level are −0.10, 0.64, and 0.63 °C in daytime, and −0.13, 0.68, and 0.67 °C at night. The FY-4B/AGRI SST tends to underestimate the sea water temperature in mid–low-latitude regions, while it tends to overestimate sea water temperature in high-latitude regions and near the edges of the full disk. The time-varying validation of FY-4B/AGRI SST accuracy shows weak fluctuations with a period of 3–4 months. Hourly accuracy verification shows that the difference between the FY-4B/AGRI SST and OSTIA SST reflects a diurnal effect. However, FY-4B/AGRI SST products need to be used with caution around midnight to avoid an abnormal accuracy. This paper also discusses the relationships between the FY-4B/AGRI SST and satellite zenith angle, water vapor content, wind speed, and in situ SST, which have an undeniable impact on the underestimation of the FY-4B/AGRI operational SST. The accuracy of the FY-4B/AGRI operational SST retrieval algorithm still needs to be further improved in the future. [ABSTRACT FROM AUTHOR]

This paper presents theoretical foundations, numerical implementation and examples of application of a two-dimensional Discrete-Element bonded-particle Sea Ice model DESIgn. In the model, sea ice is represented as an assemblage of objects of two types: disk-shaped "grains", and semi-elastic bonds connecting them. Grains move on the sea surface under the influence of forces from the atmosphere and the ocean, as well as interactions with surrounding grains through a direct contact (Hertzian contact mechanics) and/or through bonds. The model has an option of taking into account quasi-three-dimensional effects related to space- and time-varying curvature of the sea surface, thus enabling simulation of ice breaking due to stresses resulting from bending moments associated with surface waves. Examples of the model's application to simple sea ice deformation and breaking problems are presented, with an analysis of the influence of the basic model parameters ("microscopic" properties of grains and bonds) on the large-scale response of the modeled material. The model is written as a toolbox suitable for usage with the open-source numerical library LIGGGHTS. The code, together with a full technical documentation and example input files, is freely available with this paper and on the Internet. [ABSTRACT FROM AUTHOR]

A newly developed global climate model FESOM-ECHAM6 with an unstructured mesh and high resolution is applied to investigate to what degree the area-thickness distribution of new ice formed in open water affects the ice and ocean properties. A sensitivity experiment is performed which reduces the horizontal-to-vertical aspect ratio of open-water ice growth. The resulting decrease in the Arctic winter sea-ice concentration strongly reduces the surface albedo, enhances the ocean heat release to the atmosphere, and increases the sea-ice production. Furthermore, our simulations show a positive feedback mechanism among the Arctic sea ice, the Atlantic Meridional Overturning Circulation (AMOC), and the surface air temperature in the Arctic, as the sea ice transport affects the freshwater budget in regions of deep water formation. A warming over Europe, Asia and North America, associated with a negative anomaly of Sea Level Pressure (SLP) over the Arctic (positive phase of the Arctic Oscillation (AO)), is also simulated by the model. For the Southern Ocean, the most pronounced change is a warming along the Antarctic Circumpolar Current (ACC), especially for the Pacific sector. Additionally, a series of sensitivity tests are performed using an idealized 1-D thermodynamic model to further investigate the influence of the open-water ice growth, which reveals similar results in terms of the change of sea ice and ocean temperature. In reality, the distribution of new ice on open water relies on many uncertain parameters, for example, surface albedo, wind speed and ocean currents. Knowledge of the detailed processes is currently too crude for those processes to be implemented realistically into models. Our sensitivity experiments indicate a pronounced uncertainty related to open-water sea ice growth which could significantly affect the climate system. [ABSTRACT FROM AUTHOR]

This paper studies a new concept of using global navigation satellite system (GNSS) signals coherently reflected over relatively smooth ocean and ice surfaces from very low elevation angles (below ∼8°) and received by low Earth orbit (LEO) satellites to retrieve the tropospheric information. This approach can provide horizontal profiles of tropospheric zenith delay and total column water vapor (TCWV) with centimeter‐level high precision and spatial resolutions of tens of km by ∼1 km, depending on the elevation angle, with a sampling spacing of ∼100 m. This approach can potentially be applied to most sea ice and calm ocean areas and provide tropospheric sensing data, which can complement and augment existing observation systems. A few case studies are conducted in this paper using the Spire grazing‐angle GNSS‐R data. The retrieved TCWV is compared to ERA5 products and the Sentinel‐3 Ocean and Land Color Instrument measurements and shows promising performances. The errors associated with the GNSS‐R tropospheric measurements are also discussed. Plain Language Summary: The atmospheric water vapor is an important component for the weather and climate systems and is difficult to measure, especially over ocean and ice surfaces. This paper studies a new approach to measuring atmospheric water vapor using global navigation satellite system (GNSS) signals reflected off ocean and ice surfaces. If the reflection is from a low elevation angle (below ∼8°) and the reflected signal is coherent (all signal rays are reflected in the same direction), this approach can provide very high precision observation of the horizontal gradients of the tropospheric delay and the vertically integrated atmospheric water vapor with good spatial resolutions. This paper presents the methodology of the proposed approach and a few case studies to demonstrate the feasibility and performance by comparing the GNSS‐R retrieved water vapor measurements with models and the Sentinel‐3 satellite radiometry measurements. The errors associated with the GNSS Reflectometry (GNSS‐R) tropospheric measurements are also discussed. Key Points: A new tropospheric sensing concept is studied that relies on coherent‐reflection global navigation satellite system (GNSS) signals off ocean and ice surfacesAlgorithms are developed and demonstrated using Spire grazing‐angle GNSS‐R data to retrieve tropospheric delay and water vaporThe presented approach provides high‐precision tropospheric delay and total column water vapor horizontal profiles, as validated using the Sentinel‐3 Ocean and Land Color Instrument data [ABSTRACT FROM AUTHOR]

Studies have indicated that the decrease in the extent of Arctic sea ice in recent years has had a significant impact on the Arctic ecosystem and global climate. In order to understand the evolution of sea ice, it is becoming increasingly imperative to have continuous observations of Arctic-wide sea ice with high spatial resolution. Passive microwave sensors have the benefit of being less susceptible to weather, wider coverage, and higher temporal resolution. However, it is challenging to retrieve accurate parameters of sea ice due to the low spatial resolution of passive microwave images. Therefore, improving the spatial resolution of passive microwave images is beneficial for reducing the uncertainty of sea ice parameters. In this paper, four competitive multi-image super-resolution (MISR) networks are selected to explore the applicability of the networks on multi-frequency Advanced Microwave Scanning Radiometer 2 (AMSR2) images of Arctic sea ice. The upsampling factor is set to 4 in the experiment. Firstly, the optimal input lengths of the image sequence for the four MISR networks are found, and then the best network on different frequency band images is further identified. Furthermore, some factors, including seasons, sea ice motion, and polarization mode of images, that may affect the super-resolution (SR) results are analyzed. The experimental results indicate that utilizing images from winter yields superior SR results. Conversely, SR results are the worst during summer across all four MISR networks, exhibiting the largest difference in PSNR of 4.48 dB. Additionally, the SR performance is observed to be better for images with smaller magnitudes of sea ice motion compared to those with larger motions, with the maximum PSNR difference of 2.04 dB. Finally, the SR results for vertically polarized images surpass those for horizontally polarized images, showcasing an average advantage of 4.02 dB in PSNR and 0.0061 in SSIM. In summary, valuable suggestions for selecting MISR models for passive microwave images of Arctic sea ice at different frequency bands are offered in this paper. Additionally, the quantification of the various impact factors on SR performance is also discussed in this paper, which provides insights into optimizing MISR algorithms for passive microwave sea ice imagery. [ABSTRACT FROM AUTHOR]

The new sea ice configuration GSI6.0, used in the Met Office global coupled configuration GC2.0, is described and the sea ice extent, thickness and volume are compared with the previous configuration and with observationally-based datasets. In the Arctic, the sea ice is thicker in all seasons than in the previous configuration, and there is now better agreement of the modelled concentration and extent with the HadISST dataset. In the Antarctic, a warm bias in the ocean model has been exacerbated at the higher resolution of GC2.0, leading to a large reduction in ice extent and volume; further work is required to rectify this in future configurations. [ABSTRACT FROM AUTHOR]

B Professor Adrian E. Raftery b (University of Washington): It is a pleasure to congratulate the authors of these two papers on the important topic of statistical aspects of climate change. For forecasting, numerical weather prediction models did forecast the 2021 heatwave quite successfully even though it was outside the range of all previous experience. They developed new statistical methods for climate problems ranging from the integrated assessment of future global climate change to the detailed modelling of granular atmospheric processes. The purpose is clear, to provide probabilistic forecasts of future water damage for any building in Norway, both with current climate and accounting for future climate change, for insurance purposes. [Extracted from the article]

This paper presents the first results of sea ice detection using the data of Ka- and Ku-band radars at low incidence angles. A classification method based on an unsupervised K-means approach is applied to the arrays of the data for the Arctic and Antarctic regions. Comparison with Advanced Microwave Scanning Radiometer 2 (AMSR-2) data was performed, and the dependence of classification performance was evaluated for incidence angles from 0° to 18.15°. This paper evaluates the classification accuracy of sea ice detection based on Ku-band, Ka-band, and their combination. Preliminary results indicate that the classification based solely on Ku-band data achieves the best performance. [ABSTRACT FROM AUTHOR]

PUBLIC HEALTH Sweden's pandemic chief leaves The controversial chief epidemiologist at Sweden's Public Health Agency has stepped down to become a consultant for the World Health Organization (WHO), focused on pandemic vaccinations. EXPLORATION Endurance preserved in Antarctic depths More than 100 years after it was crushed by ice and sank in the Weddell Sea, the I Endurance i , the famed ship of Antarctic explorer Ernest Shackleton, was discovered last week in near pristine condition. News at a glance: Asia's COVID-19 surge, melting winter sea ice, and "inflammatory" arXiv papers. [Extracted from the article]

Accurately assessing ice loads is a fundamental issue in the field of structural design for ships in ice-covered regions. In this paper, we conducted research on extreme ice load estimation for icebreaking ships, combining stochastic theory with numerical simulation. Firstly, using sea ice data from the Arctic region of the United States National Snow and Ice Data Center, a stochastic ice field model was established under Arctic sea ice conditions using non-parametric estimation and the rejection sampling method, and ice field data were generated stochastically. Then, based on the stochastic ice field data, a three-dimensional numerical model of the interaction between the ice field and the ship hull was established, and the reliability of the numerical model was verified by experimental results. Finally, based on the numerical model of the interaction between the ice field and the ship hull, asymptotic methods were used to study the extreme ice load estimation in different parts of the ship hull, revealing the variation law of the extreme ice load in different parts of the ship hull. This study provides basic theory and technical support for the structural design of ships in polar regions and has engineering application value. [ABSTRACT FROM AUTHOR]

The revolutionary advances of Artificial Intelligence (AI) in the past decade have brought transformative innovation across science and engineering disciplines. Also in the field of Arctic science, we have witnessed an increasing trend in the adoption of AI, especially deep learning, to support the analysis of Arctic big data and facilitate new discoveries. In this paper, we provide a comprehensive review of the applications of deep learning in sea ice remote sensing domains, focusing on problems such as sea ice lead detection, thickness estimation, concentration, sea ice extent forecasting and motion detection as well as sea ice type classification. In addition to discussing these applications, we also summarize technological advances that provide customized deep learning solutions, including new loss functions and learning strategies to better understand sea ice dynamics. To promote the growth of this exciting interdisciplinary field, we further explore several research areas where the Arctic sea ice community can benefit from cutting-edge AI technology. These areas include improving multi-modal deep learning capabilities, enhancing model accuracy in measuring prediction uncertainty, better leveraging AI foundation models, and deepening the integration with physics-based models. We hope that this paper can serve as a cornerstone in the progress of Arctic sea ice research using AI and inspire further advances in this field. [ABSTRACT FROM AUTHOR]

The article offers information on the study conducted by the authors related to the Southern Ocean including a thermodynamic active ice self, with reference to Weddell Sea. It states that the study aims at the importance of sea ice and ice shelf processes in the Southern Ocean, a coupled ocean circulation sea ice cavity model based on the Regional Ocean Model System (ROMS) is used in a periodic circumpolar domain with enhanced resolution in the Weddell Sea.

The article presents a study of the assimilation of observed ice concentration and freeboard information into a global coupled ocean-sea-ice model using an Ensemble Kalman Filter system. It evaluates the efficiency and impact of the data assimilation on ice concentration. Results demonstrate that the simulated Antarctic and Arctic sea-ice are improved using the assimilation of synthetic ice concentration data.

The ice service at the German Federal Maritime and Hydrographic Agency and its predecessors has been committed to the safety and easiness of ship navigation for more than 100 years. Within this paper, an overview of the operational products issued by the German ice service on a daily to weekly basis throughout the northern hemisphere winter season is given. These comprise written reports, ice charts, NAVTEX messages, and messages via the Global Telecommunication System to inform about the sea ice situation in German coastal waters, the Baltic Sea, and worldwide. Furthermore, the ice service has systematically collected ice observation data along the German North Sea and Baltic Sea coast since the winter of 1896/1897. The history of the German ice service is presented to put the sea ice data into context of the observation technologies used in the course of the existence of the ice service. These long-term observations enable climatological analyses of the sea ice cover in German coastal waters necessary for the safe operation of offshore infrastructure. An evaluation of the data shows a recent decline in sea ice occurrence in the Baltic Sea and German Bight. Current work is ongoing to preserve more of the historic data in digital form and also to transform the products to conform to modern standards in digital technologies and interactive solutions for the customers. [ABSTRACT FROM AUTHOR]

The Ku band microwave scatterometer (SCA) and scanning microwave radiometer (SMR) onboard HaiYang-2B (HY-2B) can simultaneously supply active and passive microwave observations over the polar region. In this paper, a polar ice water discrimination model and Arctic sea-ice-type classification model based on the support vector machine (SVM) method were established and used to produce a daily sea ice extent dataset from 2019 to 2021 with data from SCA and SMR. First, suitable scattering and radiation parameters are chosen as input data for the discriminant model. Then, the sea ice extent was obtained based on the monthly ice water discrimination model, and finally, the ice over the Arctic was classified into multiyear ice (MYI) and first-year ice (FYI). The 3-year ice extent and MYI extent products were consistent with the similar results of the National Snow and Ice Data Center (NSIDC) and Ocean and Sea Ice Satellite Application Facility (OSISAF). Using the OSISAF similar product as validation data, the overall accuracies (OAs) of ice/water discrimination and FYI/MYI discrimination are 99% and 97%, respectively. Compared with the high spatial resolution classification results of the Moderate Resolution Imaging Spectroradiometer (MODIS) and SAR, the OAs of ice/water discrimination and FYI/MYI discrimination are 96% and 86%, respectively. In conclusion, the SAC and SMR of HY-2B have been verified for monitoring polar sea ice, and the sea ice extent and sea-ice-type products are promising for integration into long-term sea ice records. [ABSTRACT FROM AUTHOR]

The planktonic and biogeochemical dynamics of the Arctic shelves exhibit a strong variability in response to Arctic warming. In this study, in order to elucidate on the processes regulating the production of phytoplankton (PP) and bacterioplankton (BP) and their interactions, we employ a biogeochemical model coupled to a pan-Arctic ocean-sea ice model (MITgcm) to explicitly simulate and quantify the contribution of usable dissolved organic nitrogen (DON) drained by the major circum-Arctic rivers on PP and BP in a scenario of melting sea ice (1998-2011). Model simulations suggest that on average between 1998 and 2011, the removal of usable RDON by bacterioplankton is responsible of a ~ 26% increase of the annual BP for the whole Arctic Ocean. With respect to total PP, the model simulates an increase of ~ 8 % on an annual basis and of ~ 18% in summer. Recycled ammonium is responsible for the PP increase. The recycling of RDON by bacterioplankton promotes higher BP and PP but there is no significant temporal trend in the BP: PP ratio within the ice-free shelves over the 1998-2011 period. This suggests no significant evolution in the balance between autotrophy and heterotrophy in the last decade with a constant annual flux of RDON into the coastal ocean although changes in RDON supply and further reduction in sea ice cover could potentially alter this delicate balance. [ABSTRACT FROM AUTHOR]

The Ising model, initially proposed about 100 years ago to explain ferromagnetism and phase transitions, has become a central pillar of statistical physics and a powerful tool for diverse applications in other fields including environmental studies. In this paper, we introduce continuous spin values between −1 and +1 to a two-dimensional Ising model and utilize the generalized Ising lattice to simulate the dynamics of sea ice/water transition for a large area of 1500 km by 1500 km in the Arctic region. The simulation process follows the Metropolis-Hastings algorithm and incorporates an innovative factor to account for the inertia of spin value changes. Using the sea ice concentration data collected by the National Snow and Ice Data Center, our results exhibit striking similarity between the simulated and the observed ice melting and freezing dynamics, and two numerical measures from the simulation—the ice coverage percentage and the ice extent—match closely with the data statistics. Moreover, the model's best-fit parameters demonstrate the substantial impact of the external forces, which can be further enriched and linked to the environmental factors in other climate change research. [ABSTRACT FROM AUTHOR]

We present a detailed description of TOPAZ4, the latest version of TOPAZ - a coupled ocean-sea ice data assimilation system for the North Atlantic Ocean and Arctic. It is the only operational, large-scale ocean data assimilation system that uses the ensem- ble Kalman filter. This means that TOPAZ features a time-evolving, state-dependent estimate of the state error covariance. Based on results from the pilot MyOcean reanalysis for 2003-2008, we demonstrate that TOPAZ4 produces a realistic estimate of the ocean circulation and the sea ice. We find that the ensemble spread for temperature and sea-level remains fairly constant throughout the reanalysis demonstrating that the data assimilation system is robust to ensemble collapse. Moreover, the ensemble spread for ice concentration is well correlated with the actual errors. This indicates that the ensemble statistics provide reliable state-dependent error estimates - a feature that is unique to ensemble-based data assimilation systems. We demonstrate that the quality of the reanalysis changes when different sea surface temperature products are assimilated, or when in situ profiles below the ice in the Arctic Ocean are assimilated. We find that data assimilation improves the match to independent observations compared to a free model. Improvements are particularly noticeable for ice thickness, salinity in the Arctic, and temperature in the Fram Strait, but not for transport estimates or underwater temperature. At the same time, the pilot reanalysis has revealed sev20 eral flaws in the system that have degraded its performance. Finally, we show that a simple bias estimation scheme can effectively detect the seasonal or constant bias in temperature and sea-level. [ABSTRACT FROM AUTHOR]

Sea ice plays an important role in the air-ice-ocean interaction, but it is often represented simply in many regional atmospheric models. The Noah sea ice model, which has been widely used in the Weather Research and Forecasting (WRF) model, exhibits cold bias in simulating the Arctic sea ice temperature when validated against the Surface Heat Budget of the Arctic Ocean (SHEBA) in situ observations. According to sensitivity tests, this bias is attributed not only to the simulation of snow depth and turbulent fluxes but also to the heat conduction within snow and ice. Compared with the Noah sea ice model, the high-resolution thermodynamic snow and ice model (HIGHTSI) has smaller bias in simulating the sea ice temperature. HIGHTSI is further coupled with the WRF model to evaluate the possible added value from better resolving the heat transport and solar penetration in sea ice from a complex thermodynamic sea ice model. The cold bias in simulating the surface temperature over sea ice in winter by the original Polar WRF is reduced when HIGHTSI rather than Noah is coupled with the WRF model, and this also leads to a better representation of surface upward longwave radiation and 2 m air temperature. A discussion on the impact of specifying sea ice thickness in the WRF model is presented. Consistent with previous research, prescribing the sea ice thickness with observational information would result in the best simulation among the available methods. If no observational information is available, using an empirical method based on the relationship between sea ice concentration and sea ice thickness could mimic the large-scale spatial feature of sea ice thickness. The potential application of a thermodynamic sea ice model in predicting the change in sea ice thickness in a RCM is limited by the lack of sea ice dynamic processes in the model and the coarse assumption on the initial value of sea ice thickness. [ABSTRACT FROM AUTHOR]

Seasonal and interannual variability in sinking flux of biogenic particles was reported by the multi-year bottom-tethered sediment trap measurements in the Northwind Abyssal Plain (Station NAP: 75°N, 162°W, 1975m water depth) of the western Arctic Chukchi Borderland. Whereas the trapped particle flux had an obvious peak with the dominance of sea ice-related diatom valve in August 2011, the observed particle flux was considerably suppressed throughout the summer season in 2012. In the present study, response of ice algal production and biomass to wind-driven changes in physical environments was addressed using a pan-Arctic sea ice-ocean modeling approach. Sea ice ecosystem with ice algae was newly incorporated into the lower-trophic marine ecosystem model, which was previously coupled with a high-resolution (i.e., horizontal grid size of 5 km) ocean general circulation model. Seasonal experiments covering two year-long mooring periods indicated that primary productivity of ice algae around the Chukchi Borderland depended on basin-scale wind pattern through various processes. Easterly wind in the southern part of distinct Beaufort High supplied high abundance of nutrient for euphotic zones of the NAP region via both surface Ekman transport of Chukchi shelf water and vertical turbulent mixing with underlying nutricline water as in 2011. In contrast, northwesterly wind flowing in the northern part of extended Siberian High transported oligotrophic water within the Beaufort Gyre circulation toward the NAP region as in 2012. The modeled ice algal biomass during the summer season certainly reflected the differences in nutrient distribution. The sinking flux of Particulate Organic Nitrogen (PON) was comparable with the time series obtained from the sediment trap data in summer 2011. On the other hand, lateral advection of shelf-origin ice algal patch during a great cyclone event might have caused a model bias on the PON flux in 2012. The extension of year-long measurements is expected to help the illustration of more general features on the Arctic marine biological pump. [ABSTRACT FROM AUTHOR]

We analysed hydrographic data from the northwestern Weddell Sea continental shelf of three austral winters (1989, 1997 and 2006) and two summers following the last winter cruise. During summer a thermal front exists at ~64° S separating cold southern waters from warm northern waters that have similar characteristics as the deep waters of the central basin of the Bransfield Strait. In winter, the whole continental shelf exhibits southern characteristics with high Neon (Ne) concentrations, indicating a significant input of glacial melt water. The comparison of the winter data at the tip of the Antarctic Peninsula, spanning a period of 17 years, shows a salinity decrease of 0.09 for the whole water column. We interpret this freshening as a reduction in salt input to the water masses being advected northward on the western Weddell Sea continental shelf. Possible causes for the reduced winter salinification are a southward retreat of the summer sea ice edge together with more precipitation in this sector. However, the latter might have happened in conjunction with an increase in ice shelf mass loss, counteracting an enhanced salt input due to sea ice formation in coastal areas formerly occupied by Larsen A and B ice shelves. [ABSTRACT FROM AUTHOR]

The Arctic is undergoing rapid changes due to global warming, including the expansion of the marginal ice zone (MIZ), a zone of mixed ice and open water surfaces. To predict the atmospheric interaction with these surfaces, a critical process in climate models, this paper examines a simplified theoretical framework to non-dimensionalize the dynamics of the atmospheric boundary layer (ABL) over a mixed ice-water surface (MIZ–ABL). A heterogeneity Richardson number, Ri h , is proposed to account for the difference in temperature between the ice and water surface in relation to the synoptic pressure gradient forcing. With the wind angle relative to the ice-water interface, α , this framework hypothesizes that these two dimensionless numbers, regardless of individual dimensional variables (surface temperature and geostrophic wind speed) are sufficient to predict the MIZ–ABL dynamics. To test this framework, large-eddy simulations were employed over half-ice and half-water surfaces, with varying surface temperatures and geostrophic wind velocities. While the surface heat fluxes over ice, water, and the aggregate surface seem to be captured reasonably well by α and Ri h , the mean wind and turbulent kinetic energy (TKE) profiles were not, suggesting that not only the difference in stability between the two surface, but also the individual stabilities over each surface influence the dynamics. The wind angle had a significant impact on the results, both in terms of heat fluxes at the surface, turbulent and dispersive fluxes in the MIZ–ABL, and the structure of the secondary circulations. When wind blows perpendicular to the water-ice interface, internal boundary layers are favoured except at the highest Ri h simulated. For cases with wind parallel to the interface, large rolls parallel to the shore emerge. The paper raises at least as many questions as it answers, highlighting the need for further studies of the MIZ–ABL. [ABSTRACT FROM AUTHOR]

Scatterometers are dedicated to monitoring sea surface wind vectors, but they also provide valuable data for polar applications. As a new type of scatterometer, the rotating fan beam scatterometer delivers a higher diversity of incidence angles and more azimuth sampling. The paper takes the first rotating fan beam scatterometer, the China France Oceanography Satellite scatterometer (CSCAT), as an example to explore the effectiveness of this new type of scatterometer in polar sea ice detection. In this paper, a Bayesian method with consideration of geometric characteristics of CSCAT is developed for sea ice detection. The implementation of this method includes the definition of CSCAT backscatter space, an estimation of the sea ice Physical Model Function (GMF), a calculation of the sea ice backscatter distance to the sea ice GMF, a probability distribution function (PDF) estimation of the square distance to the GMF (sea ice GMF and wind GMF), and a calculation of the sea ice Bayesian posterior probability. This algorithm was used to generate a daily CSCAT polar sea ice mask during the CSCAT mission period (2019–2022) (by setting a 55% threshold on the Bayesian posterior probability). The sea ice masks were validated against passive microwaves by quantitatively comparing the sea ice edges and extents. The validation suggests that the CSCAT sea ice edge and extent show good agreement with the sea ice concentration distribution (i.e., sea ice concentration ≥ 15%) of the Advanced Microwave Scanning Radiometer 2 (AMSR2). The average Euclidean distance of the sea ice edges was basically less than 12.5 km, and the deviation of the sea ice extents was less than 0.3 × 106 km2. [ABSTRACT FROM AUTHOR]

The oil and natural gas resources of the Bohai Sea are mainly marginal oil fields, and there are currently a large number of structures that are approaching or have reached the end of their service life called aging structures. The interactions between ice and offshore structures could lead to significant ice-induced vibration. Ice-induced vibrations may evoke fatigue damage in tubular joints, which results in severe dangers for offshore platforms in the Bohai Sea. Dynamic ice force models and sea ice fatigue environmental parameters have not been well developed in the current design codes. It is not accurate to evaluate the fatigue damage of structures only with numerical simulation. In this paper, a faster method for evaluating fatigue damage on aging structures is proposed. Firstly, the approximate linear relationship between the fatigue hot spot stress and the vibration response of the deck structure has been discovered using dynamic analysis for jacket platform of Bohai Sea. Then, the procedure of the fatigue damage evaluation of the aging structures in the Bohai Sea is established. Finally, the numerical simulation of the structure is carried out considering ice thickness, ice velocity, ice direction, and action height of sea ice. Fatigue damage is calculated by the fatigue hot spot stress and the Palmgren–Miner rule. The measured data on the platform in the Bohai Sea are selected to obtain the fatigue hot spot stress using a mathematical model. The fatigue damage results considering the actual ice conditions of a jacket structure in the Bohai Sea are compared using the proposed method and finite element analysis. The comparison of the results verifies the rationality of the method proposed in this work. [ABSTRACT FROM AUTHOR]

This study assesses the response of phytoplankton assemblages to recent climate change, especially with regard to the shrinking of sea ice in the northern Chukchi Sea of the western Arctic Ocean. Distribution patterns of phytoplankton groups in the late summers of 2008-2010 were analyzed based on HPLC pigment signatures and, the following four major algal groups were inferred via multiple regression and cluster analyses: prasinophytes, diatoms, haptophytes and dinoflagellates. A remarkable interannual difference in the distribution pattern of the groups was found in the northern basin area. Haptophytes dominated and dispersed widely in warm surface waters in 2008, whereas prasinophytes dominated in cold water in 2009 and 2010. A difference in the onset date of sea ice retreat was evident among years -- the sea ice retreat in 2008 was 1-2 months earlier than in 2009 and 2010. The spatial distribution of early sea ice retreat matched the areas in which a shift in algal community composition was observed. Steel-Dwass's multiple comparison tests were used to assess the physical, chemical and biological parameters of the four clusters. We found a statistically significant difference in temperature between the haptophyte-dominated cluster and the other clusters, suggesting that the change in the phytoplankton communities was related to the earlier sea ice retreat in 2008 and the corollary increase in sea surface temperatures. Longer periods of open water during the summer, which are expected in the future, may affect food webs and biogeochemical cycles in the western Arctic due to shifts in phytoplankton community structure. [ABSTRACT FROM AUTHOR]

It is of great significance to explore the ocean environment and strategic deployment under the polar ice layer. In this paper, the evolution laws of the water entry cavity of projectiles passing through ice holes with different shapes and sizes are studied, and the motion states of projectiles passing through holes are described. The case of zero-gap contact motion between a projectile and a hole is considered. The results show that the initial resistance drag of the projectile passing through the circular ice hole is the largest in the case of zero-gap contact, and the cavity collapse is serious, while almost no cavity appears at the shoulder of the projectile when passing through the square hole. The intersection of splash crowns is formed at the square and triangular ice holes as the hole size increases, a diffused cavity is formed at the bottom of the hole edge, and the formation of the jet appears multiple times at each stage. Some unique vortices appear near the hole when the projectile passes through the hole. The variations of force and velocity of the projectile passing through the triangular hole are stable, but the velocity drop is the largest. [ABSTRACT FROM AUTHOR]

We introduce and document the first version of the Centre National de Recherches Météorologiques Earth system model (CNRM-ESM1). This model is based on the physical core of the CNRM-CM5 model and employs the Interactions between Soil, Biosphere and Atmosphere (ISBA) module and the Pelagic Interaction Scheme for Carbon and Ecosystem Studies (PISCES) as terrestrial and oceanic components of the global carbon cycle. We describe a preindustrial and 20th century climate simulation following the CMIP5 protocol. We detail how the various carbon reservoirs were initialized and analyze the behavior of the carbon cycle and its prominent physical drivers. CNRM-ESM1 reproduces satisfactorily several aspects of the modern carbon cycle. On land, the model reasonably captures the carbon cycling through vegetation and soil, resulting in a net terrestrial carbon sink of 2.2 PgCy-1. In the ocean, the large-scale distribution of hydrodynamical and biogeochemical tracers agrees well with a modern climatology from the World Ocean Atlas. The combination of biological and physical processes induces a net CO2 uptake of 1.7 PgCy-1 that falls within the range of recent estimates. Our analysis shows that the atmospheric climate of CNRM-ESM1 compares well with that of CNRM-CM5. Biases in precipitation and shortwave radiation over the Tropics generate errors in gross primary productivity and ecosystem respiration. Compared to CNRM-CM5, the revised ocean-sea ice coupling has modified the sea-ice cover and ocean ventilation, unrealistically strengthening the flow of North Atlantic deep water (26.1±2 Sv). It results in an accumulation of anthropogenic carbon in the deep ocean. [ABSTRACT FROM AUTHOR]

In the Chukchi Sea, due to the recent drastic reduction of sea-ice during the summer, an increasing formation of atmospheric turbulence has been reported. However, the importance and effects of atmospheric turbulence on the marine ecosystem are not fully understood in this region. To evaluate the effect of atmospheric turbulence on the marine ecosystem, high-frequent sampling (two to four times per day) on the mesozooplankton community and the gut pigment of dominant copepods were made at a fixed station in the Chukchi Sea from 10 to 25 September 2013. During the study period, a strong wind event (SWE) was observed on 18 September. After the SWE, the standing stock of chlorophyll a (chl a) was increased, especially for micro-size (> 10 µm) fractions. Zooplankton abundance ranged 23 610-56 809 ind. m-2 and exhibited no clear changes with SWE. In terms of abundance, calanoid copepods constituted the most dominated taxa (mean: 57%), followed by barnacle larvae (31%). Within the calanoid copepods, small-sized Pseudocalanus spp. (65%) and large-sized Calanus glacialis (30%) dominated. In the population structure of C. glacialis, copepodid stage 5 (C5) dominated, and the mean copepodid stage did not vary with SWE. The dominance of accumulated lipids in C5 and C6 females with immature gonads indicated that they were preparing for seasonal diapause. The gut pigment of C. glacialis C5 was higher at night and was correlated with ambient chl a, and a significant increase was observed after SWE (2.6 vs. 4.5 ng pigment ind.-1). Assuming C : Chl a ratio, the grazing impact by C. glacialis C5 was estimated to be 4.14 mg C m-2 day-1, which corresponded to 0.5-4.6% of the standing stock of micro-size phytoplankton. Compared with the metabolic food requirement, their feeding on phytoplankton accounted for 12.6% of their total food requirement. These facts suggest that C. glacialis could not maintain their population on solely phytoplankton food, and other food sources (i.e., microzooplankton) are important in autumn. As observed for the increase in gut pigment, temporal phytoplankton bloom, which is enhanced by the atmospheric turbulence (SWE) in autumn, may have a positive effect on copepod nutrition. However, because of the relatively long generation length of copepods, a smaller effect was detected for their abundance, population structure, lipid accumulation and gonad maturation within the short-term period (16 days). [ABSTRACT FROM AUTHOR]

To address the challenge of achieving both temporal consistency and spatial continuity in Earth observation data of polar regions, this paper proposes an innovative concept of Moon-based/Highly Elliptical Orbit (HEO) Spaceborne Bistatic Synthetic Aperture Radar (MH-BiSAR), with transmitters on the Moon and receivers on HEO satellites. By utilizing ephemeris data and an orbit propagator, this study explores MH-BiSAR's geometric coverage capabilities in polar regions and conducts a preliminary analysis of its characteristics. The findings reveal that MH-BiSAR could provide continuous multi-day revisit observations of polar regions within each sidereal month, presenting a significant advantage for monitoring high-dynamic and large-scale scientific phenomena, such as polar sea ice observations. This innovative observational method offers a new perspective for polar monitoring and is expected to deepen our understanding of polar phenomena. [ABSTRACT FROM AUTHOR]

Sea ice, a significant component in polar regions, plays a crucial role in climate change through its varying conditions. In Global Navigation Satellite System-Reflectometry (GNSS-R) studies, the observed surface reflectivity Γ serves as a tool to examine the physical characteristics of sea ice covers. This facilitates the large-scale estimation of first-year ice thickness using a two-layer sea ice-seawater medium model. However, it is important to note that when Sea Ice Thickness (SIT) becomes thicker, the accuracy of SIT retrieval via this two-layer model begins to decline. In this paper, we present a novel application of a spaceborne GNSS-R technique to retrieve SIT based on a three-layer model using the data from Fengyun-3E (FY-3E). Soil Moisture Ocean Salinity (SMOS) data are treated as the reference. The performance of the proposed three-layer model is evaluated against a previously established two-layer model for SIT retrieval. The analysis used the sea ice data from 2022 and 2023 with SITs less than 1.1 m. By comparing the retrieved SITs against reference values, the three-layer model achieved a Root Mean Square Error (RMSE) of 0.149 m and Correlation Coefficient (r) of 0.830, while the two-layer model reported the RMSE of 0.162 m and r value of 0.789. A scheme incorporating both models yielded superior results than either individual model, with the RMSE of 0.137 m and r reaching up to 0.852. This study is the first application of FY-3E for GNSS-R SIT retrieval, combining the advantages of a two-layer model and a three-layer model and extending the precision of GNSS-R retrieval for SIT to within 1.1 m. This provides a good reference for the future studies on GNSS-R SIT retrieval. [ABSTRACT FROM AUTHOR]

Accurate detection of sea ice leads is essential for safe navigation in polar regions. In this paper, a shape-aware (SA) network, SA-DeepLabv3+, is proposed for automatic lead detection from synthetic aperture radar (SAR) images. Considering the fact that training data are limited in the task of lead detection, we construct a dataset fusing dual-polarized (HH, HV) SAR images from the C-band Sentinel-1 satellite. Taking the DeepLabv3+ as the baseline network, we introduce a shape-aware module (SAM) to combine multi-scale semantic features and shape information and, therefore, better capture the shape characteristics of leads. A squeeze-and-excitation channel-position attention module (SECPAM) is designed to enhance lead feature extraction. Segmentation loss generated by the segmentation network and shape loss generated by the shape-aware stream are combined to optimize the network during training. Postprocessing is performed to filter out segmentation errors based on the aspect ratio of leads. Experimental results show that the proposed method outperforms the existing benchmarking deep learning methods, reaching 96.82% for overall accuracy, 93.01% for F1-score, and 91.48% for mIoU. It is also found that the fusion of dual-polarimetric SAR channels as the input could effectively improve the accuracy of sea ice lead detection. [ABSTRACT FROM AUTHOR]

The cloud feedback may result in amplification or damping of Arctic warming. Two common techniques used to diagnose the top‐of‐the‐atmosphere cloud feedback are the Adjusted Cloud Radiative Effect (AdjCRE) method and the Cloud Radiative Kernel (CRK) method. We apply both to CMIP5 and CMIP6 model data, finding that the AdjCRE calculated Arctic shortwave cloud feedback is twice as correlated with sea ice loss in CMIP5, and four times in CMIP6, as the CRK method. We find that the CRK method produces Arctic all‐sky residual percentages exceeding 20% in 15 of 18 models. We use the CRK method to decompose the feedback in CMIP5 and CMIP6 finding that its median value changed from negative to positive driven by a less‐negative cloud optical depth feedback. Despite its lack of closure, we conclude that the CRK method is better suited for Arctic SW feedbacks as it is less impacted by surface albedo changes. Plain Language Summary: The cloud feedback is the process by which cloud property changes in a warming climate can either further enhance warming or damp it. The Arctic is warming faster than the rest of the globe, and one of the largest sources of uncertainty in its climate projections is the cloud feedback. There are two popular methods to calculate the cloud feedback: the Adjusted Cloud Radiative Effect technique, and the Cloud Radiative Kernel technique. In this paper we compare the two methods in a suite of climate models by considering the extent to which changes in Arctic sea ice impact the cloud feedbacks. From this analysis we conclude that the Cloud Radiative Kernel method is less affected by sea ice loss. We then apply the Cloud Radiative Kernel technique to data from the two most recent generations of global climate models to investigate how polar day Arctic cloud feedbacks have changed between these generations. We find that the median value of these Arctic feedbacks is slightly positive in the newest generation of models, a change from slightly negative in the previous generation that is largely fueled by a weakening of the feedback associated with changes in cloud optical depth. Key Points: The Cloud Radiative Kernel method is less sensitive to surface albedo changes than the Adjusted Cloud Radiative Effect techniqueThe Cloud Radiative Kernel method provides poor radiative closure in a suite of global climate modelsThe median shortwave Arctic cloud feedback in recent climate models is slightly positive due to a weakened cloud optical depth feedback [ABSTRACT FROM AUTHOR]

Introduction: This study focused on a Chinese Antarctic krill vessel utilising continuous pumping fishing technology. The resistance characteristics of Antarctic krill ships trawling in floating ice areas is of great significance for the navigation and fishing of krill ships in ice areas. Methods: Firstly, MATLAB programming using discrete elements combined with genetic algorithms was used to construct a normal distribution ice flow model. Secondly, a fluid-structure coupling interface is created through the contact between the fluid and the trawl grid, and the displacement and resistance of the trawl grid are evaluated on the shared interface. Finally, the effects of ice density and ship sailing speed on ice resistance were studied. Results and discussion: The results of the calculations results show that ice resistance is positively related to the concentration and speed of floating ice, moreover, there is a special speed point where ice resistance increases rapidly. As the speed increases, the proportion of trawl resistance to the total resistance continues to increase, while the proportion of ice resistance continues to decrease. This paper provides a reference for the navigation and fishing resistance assessment of Antarctic krill ships in floating ice areas. [ABSTRACT FROM AUTHOR]

Accurate prediction of ocean surface currents is important for marine safety, ship routing, tracking of pollutants and in coupled forecasting. Presently, velocity observations are not routinely assimilated in global ocean forecasting systems, largely due to the sparsity of the observation network. Several satellite missions are now being proposed with the capability to measure Total Surface Current Velocities (TSCV). If successful, these would substantially increase the coverage of ocean current observations and could improve accuracy of ocean current forecasts through data assimilation. In this paper, Observing System Simulation Experiments (OSSEs) are used to assess the impact of assimilating TSCV in the Met Office's global ocean forecasting system. Synthetic observations are generated from a high-resolution model run for all standard observation types (sea surface temperature, profiles of temperature and salinity, sea level anomaly and sea ice concentration) as well as TSCV observations from a Sea surface KInematics Multiscale monitoring (SKIM) like satellite. The assimilation of SKIM like TSCV observations is tested over an 11 month period. Preliminary experiments assimilating idealised single TSCV observations demonstrate that ageostrophic velocity corrections are not well retained in the model. We propose a method for improving ageostrophic currents through TSCV assimilation by initialising Near Inertial Oscillations with a rotated incremental analysis update (IAU) scheme. The OSSEs show that TSCV assimilation has the potential to significantly improve the prediction of velocities, particularly in the Western Boundary Currents, Antarctic Circumpolar Current and in the near surface equatorial currents. For global surface velocity the analysis root-mean-squareerrors (RMSEs) are reduced by 23% and there is a 4-day gain in forecast RMSE. There are some degradations to the subsurface in the tropics, generally in regions with complex vertical salinity structures. However, outside of the tropics, improvements are seen to velocities throughout the water column. Globally there are also improvements to temperature and sea surface height when TSCV are assimilated. The TSCV assimilation largely corrects the geostrophic ocean currents, but results using the rotated IAU method show that the energy at inertial frequencies can be improved with this method. Overall, the experiments demonstrate significant potential benefit of assimilating TSCV observations in a global ocean forecasting system. [ABSTRACT FROM AUTHOR]

The sea ice albedo can amplify global climate change and affect the surface energy in the Arctic. In this paper, the data from Visible and Infra-Red Radiometer (VIRR) onboard Fengyun-3C satellite are applied to derive the Arctic sea ice albedo. Two radiative transfer models, namely, 6S and FluxNet, are used to simulate the reflectance and albedo in the shortwave band. Clear sky sea ice albedo in the Arctic region (60°~90°N) from 2016 to 2019 is derived through the physical process, including data preprocessing, narrowband to broadband conversion, anisotropy correction, and atmospheric correction. The results are compared with aircraft measurements and AVHRR Polar Pathfinder-Extended (APP-x) albedo product and OLCI MPF product. The bias and standard deviation of the difference between VIRR albedo and aircraft measurements are −0.040 and 0.071, respectively. Compared with APP-x product and OLCI MPF product, a good consistency of albedo is shown. And analyzed together with melt pond fraction, an obvious negative relationship can be seen. After processing the 4-year data, an obvious annual trend can be observed. Due to the influence of snow on the ice surface, the average surface albedo of the Arctic in March and April can reach more than 0.8. Starting in May, with the ice and snow melting and melt ponds forming, the albedo drops rapidly to 0.5–0.6. Into August, the melt ponds begin to freeze and the surface albedo increases. [ABSTRACT FROM AUTHOR]

Automated sea ice charting from synthetic aperture radar (SAR) has been researched for more than a decade, and we are still not close to unlocking the full potential of automated solutions in terms of resolution and accuracy. The central complications arise from ground truth data not being readily available in the polar regions. In this paper, we build a data set from 20 near-coincident x-band SAR acquisitions and as many airborne laser scanner (ALS) measurements from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), between October and May. This data set is then used to assess the accuracy and robustness of five machine-learning-based approaches by deriving classes from the freeboard, surface roughness (standard deviation at 0.5 m correlation length) and reflectance. It is shown that there is only a weak correlation between the radar backscatter and the sea ice topography. Accuracies between 44 % and 66 % and robustness between 71 % and 83 % give a realistic insight into the performance of modern convolutional neural network architectures across a range of ice conditions over 8 months. It also marks the first time algorithms have been trained entirely with labels from coincident measurements, allowing for a probabilistic class retrieval. The results show that segmentation models able to learn from the class distribution perform significantly better than pixel-wise classification approaches by nearly 20 % accuracy on average. [ABSTRACT FROM AUTHOR]

Sea ice, as an important component of the Earth's ecosystem, has a profound impact on global climate and human activities due to its thickness. Therefore, the inversion of sea ice thickness has important research significance. Due to environmental and equipment-related limitations, the number of samples available for remote sensing inversion is currently insufficient. At high spatial resolutions, remote sensing data contain limited information and noise interference, which seriously affect the accuracy of sea ice thickness inversion. In response to the above issues, we conducted experiments using ice draft data from the Beaufort Sea and designed an improved GBDT method that integrates feature-enhancement and active-learning strategies (IFEAL-GBDT). In this method, the incident angle and time series are used to perform spatiotemporal correction of the data, reducing both temporal and spatial impacts. Meanwhile, based on the original polarization information, effective multi-attribute features are generated to expand the information content and improve the separability of sea ice with different thicknesses. Taking into account the growth cycle and age of sea ice, attributes were added for month and seawater temperature. In addition, we studied an active learning strategy based on the maximum standard deviation to select more informative and representative samples and improve the model's generalization ability. The improved GBDT model was used for training and prediction, offering advantages in dealing with nonlinear, high-dimensional data, and data noise problems, further expanding the effectiveness of feature-enhancement and active-learning strategies. Compared with other methods, the method proposed in this paper achieves the best inversion accuracy, with an average absolute error of 8 cm and a root mean square error of 13.7 cm for IFEAL-GBDT and a correlation coefficient of 0.912. This research proves the effectiveness of our method, which is suitable for the high-precision inversion of sea ice thickness determined using Sentinel-1 data. [ABSTRACT FROM AUTHOR]

Multisensor data fusion (MDF) is a process/technique of combining observations from multiple sensors to provide a more robust, accurate and complete description of the concerned object, environment or process. In this paper we introduce a new MDF method, multisensor optimal data fusion (MODF), to fuse different operational sea ice observations around Svalbard. The overall MODF includes regridding, univariate multisensor optimal data merging (MODM), multivariate check of consistency, and generation of new variables. For MODF of operational sea ice observations around Svalbard, the AMSR2 sea ice concentration (SIC) is firstly merged with the Norwegian Meteorological Institute ice chart. Then the daily SMOS sea ice thickness (SIT) is merged with the weekly CS2SMOS SIT to form a daily CS2SMOS SIT, which is further refined to be consistent with the SIC through consistency check. Finally sea ice volume (SIV) and its uncertainty are calculated based on the merged SIC and fused SIT. The fused products provide an improved, united, consistent and multifaceted description for the operational sea ice observations, they also provide consistent descriptions of sea ice edge and marginal ice zone. We note that uncertainties may vary during the regridding process, and therefore correct determination of the observation uncertainties is critically important for MDF. This study provides a basic framework for managing multivariate multisensor observations. [ABSTRACT FROM AUTHOR]

This paper describes the modification of a simple land snow cover module of the INM RAS climate model. The possible liquid water and refreezing of meltwater in the snow layer are taken into account by the proposed parameterization. This is particularly important for modelling the transition season, as this phenomenon is mainly observed during the formation and melting of the snow cover when the surface temperature fluctuates around 0   ° C. The snow density evolution simulation is also added. This parameterization is implemented in the INM-CM snow module and verified on observation data using the ESM-SnowMIP-like protocol. As a result, the INM-CM mean climate snow melt periods are refined, particularly in middle and high latitudes. The snow-covered area according to the model is also improved. In the future, a modified version of the land snow module can be used, coupled with a snow albedo model that takes into account snow metamorphism. This module can also be applied to sea ice snow. [ABSTRACT FROM AUTHOR]

The AutoICE challenge, organized by multiple national and international agencies, seeks to advance the development of near-real-time sea ice products with improved spatial resolution, broader spatial and temporal coverage, and enhanced consistency. In this paper, we present a detailed description of our solutions and experimental results for the challenge. We have implemented an automated sea ice mapping pipeline based on a multi-task U-Net architecture, capable of predicting sea ice concentration (SIC), stage of development (SOD), and floe size (FLOE). The AI4Arctic dataset, which includes synthetic aperture radar (SAR) imagery, ancillary data, and ice-chart-derived label maps, is utilized for model training and evaluation. Among the submissions from over 30 teams worldwide, our team achieved the highest combined score of 86.3 %, as well as the highest scores on SIC (92.0 %) and SOD (88.6 %). Notably, the result analysis and ablation studies demonstrate that instead of model architecture design, a collection of strategies/techniques we employed led to substantial enhancement in accuracy, efficiency, and robustness within the realm of deep-learning-based sea ice mapping. Those techniques include input SAR variable downscaling, input feature selection, spatial–temporal encoding, and the choice of loss functions. By highlighting the various techniques employed and their impacts, we aim to underscore the scientific advancements achieved in our methodology. [ABSTRACT FROM AUTHOR]