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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]

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.

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]

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]

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]

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 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]

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]

Sea ice motion (SIM) has significant implications for sea–air interactions, thermohaline circulation, and the development of the Arctic passage. This research proposes an improved SIM retrieval method from Fengyun-3D's (FY-3D) microwave radiometer imager's (MWRI) brightness temperature (Tb) data based on the modified classical maximum cross-correlation (MCC) method and the multisource data merging method. This study utilized buoy data to establish the search area range, applied distinct thresholds across various Arctic regions, and merged the buoy data, reanalysis wind data, and SIM retrieved from FY-3D/MWRI Tb data. In 2019, for the final Arctic SIM results retrieved from the MWRI 89 GHz and 36.5 GHz Tb data, the root-mean-square error (RMSE) and the mean average error (MAE) in the east–west direction were 2.07 cm/s and 1.38 cm/s and those in the north–south direction were 1.96 cm/s and 1.15 cm/s, compared to the ice-tethered profiler (ITP) data. Compared with the daily average data of the National Snow and Ice Data Center (NSIDC), the RMSE and MAE of the SIM results obtained in this study were 0.74 cm/s and 0.93 cm/s in the east–west direction, and 0.56 cm/s and 0.72 cm/s in the north–south direction, respectively. The monthly average of the SIM retrieved from the MWRI Tb data in this research also showed a good agreement with the monthly average of the NSIDC SIM product. The comparison showed that the MWRI Tb data could be used to retrieve the Arctic SIM, and the Arctic SIM retrieval method presented in this paper was accurate and general. [ABSTRACT FROM AUTHOR]

Rapid sea ice loss events (RILEs) in a mini-ensemble of regional Arctic coupled climate model scenario experiments are analyzed. Mechanisms of sudden ice loss are strongly related to atmospheric circulation conditions and preconditioning by sea ice thinning during the seasons and years before the event. Clustering of events in time suggests a strong control by large scale atmospheric circulation. Anomalous atmospheric circulation is forcing ice flow and providing warm air affecting winter ice growth. Even without a seasonal preconditioning during winter, ice drop events can be initiated by anomalous inflow of warm air from the Atlantic sector during summer. It is shown that RILE events can be generated solely based on atmospheric circulation changes without possible competing mechanisms, such as anomalous seasonal radiative forcing or short-lived forcers (e.g. soot). Such forces do merely play minor roles or no role at all in our model. Mechanisms found are qualitatively in line with observations of the 2007 RILE. [ABSTRACT FROM AUTHOR]

A large part of the Pacific Arctic basin experiences ice-free conditions in summer as a result of sea ice cover steadily decreasing over the last decades. To evaluate the impact of ice retreat on the Arctic ecosystem, we investigated phytoplankton communities from coastal sites (Chukchi shelf) to northern deep basins (up to 86°N), during year 2008 of high melting. Pigment and taxonomy in situ data were acquired under different ice regime: the ice -free basins (IFB, 74°-77°-N), the marginal ice zone (MIZ, 77°-80°-N) and the heavy ice covered basins (HIB, >80°-N). Our results suggest that extensive ice melting provided favorable conditions to chrysophytes and prymnesiophytes growth and more hinospitable to pico-sized prasinophytes and micro-sized dinoflagellates. Larger cell diatoms were less abundant in the IFB while dominant in the MIZ of the deep Canadian basin. Our data were compared to those obtained during more icy years, 1994 and to a lesser extent, 2002. Freshening, stratification, light and nutrient availability are discussed as possible causes for observed phytoplankton communities under high and low sea ice cover. [ABSTRACT FROM AUTHOR]

The governance of the water, energy, and food (WEF) nexus is significant in the Arctic, where environmental changes are occurring at an accelerated pace, intensifying resource dynamics and geopolitical implications. Against the backdrop of a rapidly evolving Arctic landscape shaped by the global climate change, melting ice, and resource exploration, the WEF nexus emerges as a vital framework for understanding and addressing the region's complex resource interdependencies. Nonetheless, legal research in this context is still in its early stages, and, specifically in the context of the Arctic, we did not find any such research. This study assesses a nexus approach to WEF in Arctic's transdisciplinary and multifaceted environment from an international law perspective to address the intricate dynamics that shape the resilience and security of WEF resources in an increasingly interconnected and accessible Arctic. Our objective in this study is to introduce international law as an overarching network of international rules and principles, legal instruments, and relevant institutions as a starting point to address the WEF governance intricacies in the Arctic, facilitating the harmonization of diverse interests, ensuring equitable access to resources, and promoting sustainable development. We argue that international law constitutes the essential means to address a nexus approach to WEF and its issues and complexities in a transboundary context within the Arctic. By examining existing international legal frameworks applicable to the Arctic and related instruments, policies, journals, and other publications, this paper seeks to canvas how international law is in support of a nexus approach to WEF in this region. [ABSTRACT FROM AUTHOR]

Melting of sea ice in the Arctic has accelerated due to global warming. The Fram Strait (FS) serves as a crucial pathway for sea ice export from the Arctic to the North Atlantic Ocean. Monitoring sea ice drift (SID) in the FS provides insight into how Arctic sea ice responds to the climate change. The SID has been retrieved from Sentinel-1 synthetic aperture radar (SAR), Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and further exploration is needed for the retrieval of SID using optical imagery. In this paper, we retrieve SID in the FS using the Chinese HaiYang1-D (HY-1D) satellite equipped with the Coastal Zone Imager (CZI). A multi-template matching technique is employed to calculate the cross-correlation, and subpixel estimation is used to locate displacement vectors from the cross-correlation matrix. The dataset covering March to May 2021 was divided into hourly and daily intervals for analysis, and validation was performed using Copernicus Marine Environment Monitoring Service (CMEMS) SAR-based product and International Arctic Buoy Programme (IABP) buoy. A comparison with the CMEMS SID product revealed a high correlation with the daily interval dataset; however, due to the spatial and temporal variability in the sea ice motion, differences are observed with the hourly interval dataset. Additionally, validation with the IABP buoys yielded a velocity bias of -0.005 m s -1 and RMSE of 0.031 m s -1 for the daily interval dataset, along with a flow direction bias of 0.002 rad and RMSE of 0.009 rad, respectively. For the hourly interval dataset, the velocity bias was negligible (0 m s -1), with a RMSE of 0.036 m s -1 , while the flow direction bias was 0.003 rad, with a RMSE of 0.010 rad. In addition, during the validation with buoys, we found that the accuracy of retrieving the SID flow direction is distinctly interrelated with the sea ice displacement. [ABSTRACT FROM AUTHOR]

Polar sea ice extent exhibits a highly dynamic nature. This paper investigates the sea ice extent retrieval on a fine (6.25 km) grid based on the 12.5 km sampling data from the China France Ocean Satellite Scatterometer (CSCAT), which is generated by an adapted Bayesian sea ice detection algorithm. The CSCAT 12.5 km sampling data are analyzed, a corresponding sea ice GMF model is established, and the important calculation procedures and parameter settings of the adapted Bayesian algorithm for CSCAT 12.5 km sampling data are elaborated on. The evolution of the sea ice edge and extent based on CSCAT 12.5 km sampling data from 2020 to 2022 is introduced and quantitatively compared with sea ice extent products of Advanced Microwave Scanning Radiometer 2 (AMSR2) and the Advanced Scatterometer onboard MetOp-C (ASCAT-C). The results suggest the sea ice extent of CSCAT 12.5 km sampling data has good consistency with AMSR2 at 15% sea ice concentration. The sea ice edge accuracy between them is about 7 km and 10 km for the Arctic and Antarctic regions, and their sea ice extent difference is 0.25 million km2 in 2020 and 0.5 million km2 in 2021 and 2022. Compared to ASCAT-C 12.5 km sampling data, the sea ice edge Euclidean distance (ED) of CSCAT 12.5 km data is 14 km (2020 and 2021) and 12.5 km (2022) for the Arctic region and 14 km for the Antarctic region. The sea ice extent difference between them is small except for January to May 2020 and 2021 for the Arctic region. There are significant deviations in the sea ice extents of CSCAT 12.5 km and 25 km sampling data, and their sea ice extent difference is 0.3–1.0 million km2. [ABSTRACT FROM AUTHOR]

This paper describes the new Regional Arctic Ocean/sea ice Reanalysis (RARE) with a domain that spans a subpolar/polar cap poleward of 45°N. Sequential data assimilation constrains temperature and salinity using World Ocean Database profiles as well as in situ and satellite SST, and PIOMAS sea ice thickness estimates. The 41-yr (1980–2020) RARE1.15.2 reanalysis with resolution varying between 2 and 5 km horizontally and 1–10 m vertically in the upper 100 m is examined. To explore the impact of resolution RARE1.15.2 is compared to a coarser-resolution SODA3.15.2, which uses the same modeling and data assimilation system. Improving resolution in the reanalysis system improves agreement with observations. It produces stronger more compact currents, enhances eddy kinetic energy, and strengthens along-isopycnal heat and salt transports, but reduces vertical exchanges and thus strengthens upper ocean haline stratification. RARE1.15.2 and SODA3.15.2 are also compared to the Hadley Center EN4.2.2 statistical objective analysis. In regions of reasonable data coverage such as the Nordic seas the three products produce similar time-mean distributions of temperature and salinity. But in regions of poor coverage and in regions where the coverage changes in time EN4.2.2 suffers more from those inhomogeneities. Finally, the impact on the Arctic of interannual temperature fluctuations in the subpolar gyres on the Arctic Ocean is compared. The influence of the subpolar North Pacific is limited to a region surrounding Bering Strait. The influence of the subpolar North Atlantic, in contrast, spreads throughout the Nordic seas and Barents Sea in all three products within two years. Significance Statement: The Arctic Ocean/sea ice system plays crucial roles in climate variability and change by controlling the northern end of the oceanic overturning circulation, the equator to pole air pressure gradient, and Earth's energy balance. Yet the historical ocean observation set is sparse and inhomogeneous, while ocean dynamics has challengingly fine horizontal and vertical scales. This paper introduces a new Regional Arctic Ocean/sea ice Reanalysis (RARE) whose goal is to use the combined constraints of mesoscale ocean dynamics, historical observations, surface meteorology, and continental runoff in a data assimilation framework to reconstruct historical variability. RARE is used to produce a 41-yr ocean/sea ice reanalysis 1980–2020 whose results are described here. [ABSTRACT FROM AUTHOR]

Arctic sea ice change is one of the critical factors affecting the global climate environment; hence, it is crucial to obtain sea ice thickness with high accuracy while studying polar and global climate change. In the process of using altimetry data to estimate sea ice thickness, the mean sea surface height will bring greater uncertainty to the extraction of sea ice freeboard, which will affect the accuracy of sea ice thickness. Also, the influence of snow cover on radar signal penetration will bring greater uncertainty to sea ice thickness. In this paper, we present a processing chain for sea ice thickness estimation. First, we compare the effect of four different MSS models on the freeboard estimation. Then, considering the incomplete penetration of radar signals and the different speeds of radar signals penetrating the snow layer and the vacuum, the traditional sea ice thickness model is optimized to obtain the sea ice thickness. Compared with the Operation IceBridge (OIB) sea ice thickness, the accuracy of sea ice thickness obtained by the optimized model is better than 0.350 m, with a root mean square error of 0.260 m and a mean bias of 0.048 m. The comparison results show that the combination of the latest DTU18 MSS model and sea ice thickness optimization model effectively improve the accuracy of sea ice thickness. [ABSTRACT FROM AUTHOR]

This paper examines teleconnections between the Arctic and the Baltic Sea region and is based on two cases of Community Earth System Model version 1 large ensemble (CESM-LE) climate model simulations: the stationary case with pre-industrial radiative forcing and the climate change case with RCP8.5 radiative forcing. The stationary control simulation's 1800-year long time series were used for stationary teleconnection and a 40-member ensemble from the period 1920–2100 is used for teleconnections during ongoing climate change. We analyzed seasonal temperature at a 2 m level, sea-level pressure, sea ice concentration, precipitation, geopotential height, and 10 m level wind speed. The Arctic was divided into seven areas. The Baltic Sea region climate has strong teleconnections with the Arctic climate; the strongest connections are with Svalbard and Greenland region. There is high seasonality in the teleconnections, with the strongest correlations in winter and the lowest correlations in summer, when the local meteorological factors are stronger. North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) climate indices can explain most teleconnections in winter and spring. During ongoing climate change, the teleconnection patterns did not show remarkable changes by the end of the 21st century. Minor pattern changes are between the Baltic Sea region temperature and the sea ice concentration. We calculated the correlation between the parameter and its ridge regression estimation to estimate different Arctic regions' collective statistical connections with the Baltic Sea region. The seasonal coefficient of determination, R2 , was highest for winter: for T2m , R2=0.64 ; for sea level pressure (SLP), R2=0.44 ; and for precipitation (PREC), R2=0.35. When doing the same for the seasons' previous month values in the Arctic, the relations are considerably weaker, with the highest R2=0.09 being for temperature in the spring. Hence, Arctic climate data forecasting capacity for the Baltic Sea region is weak. Although there are statistically significant teleconnections between the Arctic and Baltic Sea region, the Arctic impacts are regional and mostly connected with climate indexes. There are no simple cause-and-effect pathways. By the end of the 21st century, the Arctic ice concentration has significantly decreased. Still, the general teleconnection patterns between the Arctic and the Baltic Sea region will not change considerably by the end of the 21st century. [ABSTRACT FROM AUTHOR]

Arctic sea ice plays an important role in Arctic-related research. Therefore, how to identify Arctic sea ice from remote sensing images with high quality in an unavoidable noise environment is an urgent challenge to be solved. In this paper, a constrained energy minimization (CEM) method is applied for Arctic sea ice identification, which only requires the target spectrum. Moreover, an error-accumulation enhanced neural dynamics (EAEND) model with strong noise immunity and high computing accuracy is proposed to aid with the CEM method for Arctic sea ice identification. With the theoretical analysis, the proposed EAEND model possesses a small steady-state error in noisy environments. Finally, compared with other existing models, the proposed EAEND model can not only complete sea ice identification in excellent fashion, but also has the advantages of high efficiency and noise immunity. [ABSTRACT FROM AUTHOR]

Sea ice and freshwater ice can be different in terms of physical and acoustic characteristics, such as density, salinity, etc. In this paper, under-ice ambient noise in the Mudan river (Jilin Province, Northeast of China) is analyzed using the data recorded by autonomous hydrophones to test if the river ice environment is an effective analog for studying under-ice noise of multi-year ice sheets in the Arctic. The noise spectrum level below 250 Hz and above 1 kHz decreases linearly with the increase in the logarithmic frequency in a quiet environment. The ice cracks are detected and extracted, and Pearson correlation analysis between meteorological information and cracks is carried out. Frequency correlation matrixes are calculated to obtain the correlation between pairs of frequencies and evaluate the frequency correlation of ice crack noise of two hydrophones under different depths, different distances, and different times. Finally, the paper compares the experimental results with Arctic under-ice noise in the literature. Similarities with Arctic under-ice noise are observed in the experiment, including noise spectrum, cracks' peak frequency, and correlations between temperature and crack intensity. This paper believes that the study of under-ice noise in freshwater rivers can be used to simulate multi-year ice regions in the Arctic in terms of thermal-induced cracks and meteorological correlation. And future research is needed to prove this judgment further. [ABSTRACT FROM AUTHOR]

The special geographical location of the polar regions increases the difficulty of modeling surface emissivity, thus the physical retrieval algorithms of the temperature and humidity profiles for microwave radiometers mainly focus on the regions between 60°S and 60°N. In this paper, the deep neural networks (DNN) and long short-term memory (LSTM) models are first implemented to retrieve atmospheric temperature and humidity profiles in real time from FY-3D/MWHTS in Arctic regions and are compared with the physical retrieval algorithm. The hyperparameters of the machine learning models are determined using the grid search and 10-fold cross-validation. Results show that, compared with the physical retrieval algorithm, the retrieval accuracies of the atmospheric temperature and humidity profiles of the DNN and LSTM models in June 2021 are higher over sea ice, and the maximum retrieval accuracies are improved by about 3.5 K and 42%. Over land, the retrieval accuracies of the atmospheric temperature profiles for the DNN and LSTM models in June 2021 are improved by about 5 K. The retrieved humidity results for these two models are not compared with the physical retrieval algorithm, which fails for the humidity profile retrieval over land. In addition, the retrieval results of the DNN-based and LSTM-based models using the independent validation data in February, April, and September are also evaluated over different surface types. The RMSEs of the retrieved temperature profiles for the two models are within 4 K, except for the near-surface, and the humidity profiles are within 25%, except for in February. The temperature profiles in September and the humidity profiles in February are somewhat reduced compared to other months because of the highly variable emissivity properties in autumn and winter. Overall results show that the machine learning method can well-evaluate the retrieval capability of FY-3D/MWHTS of the atmospheric temperature and humidity profiles in Arctic regions. [ABSTRACT FROM AUTHOR]

Numerical and computer modeling of various physical processes is a modern trend and is a promising way to solve the problem of determining the magnitude of ice impacts on shelf structures and technical facilities in the Arctic. This paper contains a review and analysis of some numerical methods, which have found their application in modeling the ice–structure interaction process. Such methods as the finite element method (FEM), the extended FEM (XFEM), the Galerkin discontinuous method, the smoothed hydrodynamic particle method (SPH), the discrete element method (DEM), the material point method (MPM), and the new promising smoothed particle Galerkin method (SPG) are considered. The advantages and disadvantages of these methods are presented, as well as the results of various researchers' studies showing the approaches applied to ice fracture modeling in numerical methods under consideration. The paper concludes with an assessment of the most frequently used methods and approaches (FEM and DEM) and recommendations on the use of the SPG method for the task of ice–structure interaction modeling are provided. [ABSTRACT FROM AUTHOR]

Modeling and understanding sea ice dynamics in marginal ice zones rely on measurements of sea ice. Lagrangian observations of ice floes provide insight into the dynamics of sea ice, the ocean, and the atmosphere. However, optical satellite images are susceptible to atmospheric noise, leading to gaps in the retrieved time series of floe positions. This paper presents an efficient and statistically accurate nonlinear dynamical interpolation framework for recovering missing floe observations. It exploits a balanced physics‐based and data‐driven construction to address the challenges posed by the high‐dimensional and nonlinear nature of the coupled atmosphere‐ice‐ocean system, where effective reduced‐order stochastic models, nonlinear data assimilation, and simultaneous parameter estimation are systematically integrated. The new method succeeds in recovering the locations, curvatures, angular displacements, and the associated strong non‐Gaussian distributions of the missing floes in the Beaufort Sea. It also accurately estimates floe thickness and recovers the unobserved underlying ocean field with an appropriate uncertainty quantification, advancing our understanding of Arctic climate. Plain Language Summary: Tracking individual ice floes is a unique measurement of areas of the Arctic where the ice cover interacts with the open ocean. Unfortunately, optical satellite images of these areas are frequently obscured by clouds, leading to missing observations of the ice floes. Traditional methods of filling in these gaps in the data set have issues. Linear interpolation, which averages between available observations to fill in missing ones, fails to recover the curvature of the floes. Dynamical interpolation methods, which take into account the physical properties of the ice floes, are very computationally expensive. This paper presents a nonlinear dynamical interpolation framework for recovering missing floe observations, which is both computationally efficient and statistically accurate. The framework incorporates a model of the atmosphere, ocean, and sea ice and systematically develops data‐driven reduced‐order stochastic models, which significantly accelerate the dynamical interpolation while retaining accuracy. In addition, the framework estimates key physical parameters, such the floe thickness. This new method succeeds in recovering the locations, curvatures, angular displacements, and strong non‐Gaussian statistics of the missing floes in a data set of ice floes in the Beaufort Sea. These results can provide complete data sets that advance our understanding of Arctic climate. Key Points: Developed systematic data‐driven reduced‐order stochastic model to significantly lower the computational cost for dynamical interpolationEstimated key physical parameters such as the floe thickness and recovered the unobserved ocean flow field with uncertainty quantificationRecovered important non‐Gaussian distributions of the curvature and angular displacement of the missing floes in the Beaufort Sea [ABSTRACT FROM AUTHOR]

Seabirds along the western Antarctic Peninsula are known to be shifting in abundance and distribution in response to changing sea ice and prey distributions, but the spatial extent of these changes has remained an open question because survey efforts have focused on the more easily accessed northern coastline. We used a yacht-based field expedition (January 5-21, 2013) to complete the first comprehensive penguin ( Pygoscelis spp.) and blue-eyed shag ( Phalacrocorax [ atriceps] bransfieldensis) population survey of the Graham and Loubet Coasts of the western Antarctic Peninsula since the mid-1980s. Our surveys document a sharp transition zone at the northern boundary of Marguerite Bay; north of this boundary zone, we confirm widespread declines in Adélie penguins and increasing populations of gentoo penguins, but south of this zone we find Adélie populations that have remained stable or increased in abundance since the previous surveys by Poncet and Poncet (Br Antarct Surv Bull 77:109-129, ). Marguerite Bay has long been known as a predator 'hotspot,' but our findings suggest that Marguerite Bay has actually been improving for marine predators for at least several decades. Marguerite Bay, which has fundamentally different ocean dynamics than in areas just outside Marguerite Bay, has maintained persistent phytoplankton blooms over the past decade even as summer sea ice extent, which can inhibit access to breeding areas, has declined. This provides further support for the hypothesis that ocean productivity and sea ice dynamics are critical factors regulating Adélie penguin abundance in the region and that Marguerite Bay is now at the front lines of ecological change in this region. [ABSTRACT FROM AUTHOR]

Ocean tides are not explicitly included in many ocean general circulation models, which will therefore omit any interactions between tides and the cryosphere. We present model simulations of the wind and buoyancy driven circulation and tides of the Barents and Kara Seas, using a 25 km x 25 km 3-D ocean circulation model coupled to a dynamic and thermodynamic sea ice model. The modeled tidal amplitudes are compared with tide gauge data and sea ice extent is compared with satellite data. Including tides in the model is found to have little impact on overall sea ice extent but is found to delay freeze up and hasten the onset of melting in tidally active coastal regions. The impact that including tides in the model has on the salt budget is investigated and found to be regionally dependent. The vertically integrated salt budget is dominated by lateral advection. This increases significantly when tides are included in the model in the Pechora Sea and around Svalbard where tides are strong. Tides increase the salt flux from sea ice by 50% in the Pechora and White Seas but have little impact elsewhere. This study suggests that the interaction between ocean tides and sea ice should not be neglected when modeling the Arctic. [ABSTRACT FROM AUTHOR]

The article presents a study that examines the efficiency of model validation and data assimilation scheme to assess physical performance of sea-ice model. The study performs two simulations in sea-ice model used to predict opening and initiation of leads in Arctic ice and remotely observes behaviors like density, which impacts ice strength of ice. Result shows the scheme as consistent with internal model physics and is efficient for initialization of models in lower dimensional features.

During the Multidisciplinary Drifting Observatory for the Study of Arctic Climate expedition, a tethered balloon system was operated with a turbulence probe attached to study the lower troposphere in the high Arctic. Overall, measurements were conducted on 34 days between December 2019 and May 2020, resulting in 47 quality-assured sampling records consisting of vertical profiles and constant-altitude measurements. The continuous profiles extend from the surface, i.e., the sea ice floe, to a height of several hundred meters typically. The high-resolution wind velocity measurements using a hot-wire anemometer and temperature measurements using a thermocouple provide a comprehensive basis for examining the dynamical processes and thermodynamic stratification in the Arctic atmospheric boundary layer under cloudless and cloudy conditions. This paper provides a detailed technical description of the turbulence payload, including calibration and quality assurance, and a general overview of the data. A particular focus of this work is the estimation of local energy dissipation rates. The data are freely available from the World Data Center PANGAEA. [ABSTRACT FROM AUTHOR]

Space observations (1979–2020) have shown that, over the past 40 years, years with a decrease in the area of summer ice and their thickness prevailed. Over 10 years, negative trends of anomalies in the area and thickness of the ice are –13 and –15%, respectively. A rapid reduction in the area of old ice (>4-year-old) is also noted, because in 1985 it was estimated at 2.7 million km2, while in March 2010 it was 0.34 million km2. The paper analyses paleo sea ice extent during the Holocene (the last 12 000 years) based on empirical IP25 biomarkers (a sea ice proxy with 25 carbon atoms synthesized by the specific Arctic sea ice diatoms Hasleaspp, which have been proven to be a suitable proxy for paleo-sea ice reconstructions) obtained from deep-sea cores from the North Atlantic. The data showed that, during the warm periods of the Early and Middle Holocene, the area of summer sea ice was reduced to a minimum. This confirms the conclusion made earlier in (Kinnard et al., 2011) that the current trend of reducing the area and thickness of ice is unprecedented over the past 1500 years. There is no complete analogue of the climate in the past corresponding to the current level of the CO2 concentration in the atmosphere. The period with CO2 concentrations in the atmosphere similar to the current level was the warm part of the Middle Pliocene between 3 and 4 million years ago with level of the CO2 concentration 450–500 ppm against approximately 420 ppm at present. Paleo-climate reconstructions for this period estimate the global temperature to be 3.0–3.5 ± 0.5°C higher than at the end of the 19th century. Summer air temperatures in the high latitudes of the Northern Hemisphere exceeded the current ones by 8–10°C, and the sea ice in the Arctic shelf seas was completely absent in the summer. Empirical data and model simulations have shown that presently the main driver of the reduction of the Arctic sea ice area is the increase in concentration of CO2 in the atmosphere. At the present time, old sea ice tends to be replaced by seasonal ice, demonstrating a natural shift from the predominance of permanent ice to an ice-free Arctic. In the case of a continuous increase in CO2 concentration in the atmosphere despite emission control measures, one of the scenarios that happened in the past may occur again. [ABSTRACT FROM AUTHOR]

Ambient noise plays a crucial role in influencing the observation quality at seismic stations. By studying the distribution patterns of ambient noise, we can gain initial insights into the noise conditions within a specific research area. This paper investigates the properties of ambient noise in different frequency bands under environmental settings in the Chukchi Sea region, utilizing data collected from ocean bottom seismometers (OBSs) deployed during the Ninth Chinese National Arctic Scientific Survey. The probability density function (PDF) method is used to reveal the distinctive features of ambient noise. In addition, by comparing the crowed number values of ambient noise in the Chukchi Sea area with the global new low-noise model (NLNM) and new high-noise model (NHNM), a more comprehensive understanding of the patterns, distribution characteristics, and sources of ambient noise in the Arctic Chukchi Sea area is gained. The study suggests that the overlying sea ice in the Arctic Chukchi Sea area can suppress the microseismic band ambient noise, and the overall level of ambient noise in the Chukchi Sea area lies between the land seismic ambient noise level and the ambient noise level in the middle- and low-latitude sea areas. Meanwhile, an abnormal power spectrum caused by different levels of natural earthquakes is observed. This study fills the gap by using seafloor seismic instruments to investigate ambient noise in the Chukchi Sea area. [ABSTRACT FROM AUTHOR]

The satellite-based techniques for the monitoring of extreme ice features (EIFs) in the Canadian Arctic were investigated and demonstrated using synthetic aperture radar (SAR) and electro-optical data sources. The main EIF types include large ice islands and ice-island fragments, multiyear hummock fields (MYHF) and other EIFs, such as fragments of MYHF and large, newly formed hummock fields. The main objectives for the paper included demonstration of various satellite capabilities over specific regions in the Canadian Arctic to assess their utility to detect and characterize EIFs. Stereo pairs of very-high-resolution (VHR) imagery provided detailed measurements of sea ice topography and were used as validation information for evaluation of the applied techniques. Single-pass interferometric SAR (InSAR) data were used to extract ice topography including hummocks and ice islands. Shape from shading and height from shadow techniques enable us to extract ice topography relying on a single image. A new method for identification of EIFs in sea ice based on the thermal infrared band of Landsat 8 was introduced. The performance of the methods for ice feature height estimation was evaluated by comparing with a stereo or InSAR digital elevation models (DEMs). Full polarimetric RADARSAT-2 data were demonstrated to be useful for identification of ice islands. [ABSTRACT FROM AUTHOR]

Using L-band microwave radiative transfer theory to retrieve ice and snow parameters is one of the focuses of Arctic research. At present, due to limitations of frequency and substrates, few operational microwave radiative transfer models can be used to simulate L-band brightness temperature (TB) in Arctic sea ice. The snow microwave radiative transfer (SMRT) model, developed with the support of the European Space Agency in 2018, has been used to simulate high-frequency TB in polar regions and has obtained good results, but no studies have shown whether it can be used appropriately in the L-band. Therefore, in this study, we systematically evaluate the ability of the SMRT model to simulate L-band TB in the Arctic sea ice and snow environment, and we show that the results are significantly optimized by improving the simulation method. In this paper, we first consider the thermal insulation effect of snow by adding the thermodynamic equation, then use a reasonable salinity profile formula for multi-layer model simulation to solve the problem of excessive L-band penetration in the SMRT single-layer model, and finally add ice lead correction to resolve the large influence it has on the results. The improved SMRT model is evaluated using Operation IceBridge (OIB) data from 2012 to 2015 and compared with the snow-corrected classical L-band radiative transfer model for Arctic sea ice proposed in 2010 (KA2010). The results show that the SMRT model has better simulation results, and the correlation coefficient (R) between SMRT-simulated TB and Soil Moisture and Ocean Salinity (SMOS) satellite TB is 0.65, and the RMSE is 3.11 K. Finally, the SMRT model with the improved simulation method is applied to the whole Arctic from November 2014 to April 2015, and the simulated R is 0.63, and the RMSE is 5.22 K. The results show that the SMRT multi-layer model is feasible for simulating L-band TB in the Arctic sea ice and snow environment, which provides a basis for the retrieval of Arctic parameters. [ABSTRACT FROM AUTHOR]

The two Polar Regions Arctic and Antarctica are geographically different, the Arctic, an ocean covered by ice and Antarctica, a landmass surrounded by waters of the Southern Ocean. The Arctic is governed by the 'Arctic Council', comprising the five Arctic littoral countries who have their respective national jurisdictions over the Arctic region and function under various international treaties and conventions. The Antarctic continent does not belong to any single country as per the 'Antarctic Treaty'; it "freezes" territorial claims of the continent and devotes Antarctica to peace and science. Though the Treaty takes a "bifocal" approach to neither recognise nor deny territorial claims, however there are currently 55 contracting parties associated to research activities on the continent. Though the Polar Regions are increasingly getting securitised due to their natural wealth and resources, this paper concludes that the regions should be a place of peace and cooperation to preserve its vulnerable and unique environment for humanity. [ABSTRACT FROM AUTHOR]

The latest IPCC report clearly stated that the human influence is the main reason of sea ice reduction in the Arctic. Importance of sea ice monitoring from space is increasing. In addition, the heat flux of ice in thin ice areas is strongly affected by the ice thickness difference. Therefore, ice thickness is one of the important parameters of sea ice. The authors have been studying on extracting thin ice areas using optical sensor such as MODIS for years. In this paper, the authors summarized the procedure of our study starting from comparing in-situ measurement of ice thickness with high resolution optical sensor RSI data, and finally developing the thin ice area extraction algorithm using MODIS. Estimating ice thickness from optical sensor data is not easy. However, through our study, the authors have verified the possibility of extracting thin ice areas using optical sensor data observed from satellites. In this study, the authors define "thin ice areas" as ice which thickness is less than about 30 cm with reflectance much lower than thick ice. The basic idea of the algorithm is to use the scatterplots of MODIS band 1 & 2 reflectance and extract thin ice areas using the distribution difference of thin ice against water, thick ice, clouds. Not all but most of the thin ice areas could be extracted using the algorithm. [ABSTRACT FROM AUTHOR]

The Beaufort Sea High is a high‐pressure system located in the Beaufort Sea that influences ocean circulation in the western Arctic known as the Beaufort Gyre. Wrangel Island, located in the western Chukchi Sea, typically experiences easterly sea ice motion due to the Beaufort Gyre. We find that under these climatological conditions, moving ice is blocked by the island and accumulates on its eastern side, while ice on its western side continues to drift leaving an area of open water and reduced ice thickness along the western side of the island. This results in an ice thickness dipole across the island. A reversal in the atmospheric circulation across the western Arctic results in a dipole with the opposing sign. We find the dipole is present throughout the year and is strongest in January when the difference in ice thickness between the eastern and western sides of the island is approximately 1 m. During the spring, it is associated with the transient opening of a polynya to the west of the island. The dipole is the result of opposing ice divergence and convergence across the western Arctic and may impact ocean circulation and ecosystems within the Chukchi Sea. Plain Language Summary: The Arctic climate is rapidly changing with many important environmental consequences prompting increased scientific study. In this paper, we examine the interaction of drifting sea ice and Wrangel Island, which is located in the western Arctic Ocean's Chukchi Sea. We find that ice typically drifts from the east and is blocked by the island causing the ice to accumulate on its eastern side. Ice continues to drift away from the western side of the island, thus a contrast or "dipole" in ice thickness is created. This dipole is present throughout the year and is strongest in January when the ice thickness difference is around 1 m. We find that the formation of the dipole is associated with strong westward winds at the island. These winds are associated with a strong high‐pressure system called the Beaufort Sea High that results in anti‐cyclonic winds, ice motion, and surface currents throughout the region. A reversal from easterly to westerly winds results in a dipole of opposing sign. The dipole is associated with ice thickness anomalies across the western Arctic and may impact ocean circulation and ecosystems across the region. Key Points: Ice motion in the Beaufort and Chukchi Seas can result in a sea ice thickness dipole in the vicinity of Wrangel IslandA reversal in wind direction and sea‐level pressure anomalies across the western Arctic Ocean can cause the signal of the dipole to reverseThe dipole is the result of ice motion divergence and convergence across the region and may impact ocean circulation and ecosystems [ABSTRACT FROM AUTHOR]

The decline of sea ice in the Arctic region is a critical indicator of rapid global warming and can also influence the feedback processes in the Arctic, so the prediction of sea ice extent and thickness plays an important role in climate modeling and prediction. This paper uses machine learning methods to predict the sea ice extent, and by adjusting the methods and factors, which include the climate variables, the past sea ice extent, and the simple linear-regression-simulated sea ice extent, then we found the best combination to give the result with the highest R2 score. We noticed that with longer periods of past sea ice extent data and shorter periods of climate data, the results appeared to be better. This might be related to the difference in climate and ocean memory. The sub-region sea ice extent prediction shows that the regions with whole-year ice cover are easier to predict and that those regions with sudden weather changes and significant seasonal variability appear to have lower R2 scores in the sea ice extent prediction. [ABSTRACT FROM AUTHOR]

The on-going reduction of sea-ice in the Arctic is now facilitating maritime activities in areas previously considered inaccessible. Numerous statistics indicate that fishing and tourism are clearly gaining momentum within the wider region under discussion. Furthermore, a certain number of private companies and state-affiliated actors are setting into motion plans for promoting the use of the so-called arctic passages, while certain interesting business projects are already underway; the Yamal LNG Project is for example clearly standing out. As human presence and operations are expected to intensify within that inherently risky region, the first aim of this paper is to qualitatively identify certain business opportunities associated with the Arctic and then highlight their interrelation with the prevailing patterns of maritime traffic. Additionally, on the basis of the report titled 'Arctic Shipping Status Report – Heavy Fuel Oil (HFO) Use by Ships in the Arctic 2019' (ASSR #2) that was released during October 2020 by the Arctic Council's Working Group on the Protection of the Arctic Marine Environment (PAME), it explains the use of the various types of fuels in the region under discussion and highlights certain environmental risks. Finally, it briefly assesses the overall effectiveness of a (proposed) regulatory intervention of completely banning the use of HFO in the Arctic. This initiative can indeed have a positive contribution to protecting the region's pristine environment, but any regulations of this type must also consider the issue of fishing vessels, which are not covered under the scope of International Maritime Organization's (IMO) International Convention for the Safety of Life at Sea (SOLAS) and the International Convention for the Prevention of Pollution from Ships (MARPOL). [ABSTRACT FROM AUTHOR]

Due to the existence of seasonal or perennial sea ice cover, the determination of the Arctic sea surface is more difficult than that of mid-low latitudinal oceans. Focusing on the sea surface height in the ice-covered region, this paper constructs a new Arctic mean sea surface (MSS) model, named SUST22, by combining the measurements from ICESat and Cryosat-2 missions. The lead detection methods of ICESat and Cryosat-2 are first studied and modified to acquire sea surface measurements with better accuracy. The results have shown that the standard deviation of Cryosat-2-derived Arctic sea surface height is about 3–4 cm in 10-km resolution grids, while the value of ICESat is 5–6 cm. Then the MSS construction procedure is discussed and the SUST22 MSS model is constructed. The new model is compared with the other four Arctic MSS models. The best agreement is found between SUST22 and DTU21 with an average difference of −4.0 ± 5.2 cm. These models are also validated by ICESat-2 samples. The average difference between ICESat-2 and SUST22 is 15.8 ± 7.4 cm, which shows that the new model SUST22 presents better consistency with the ICESat-2 than any of the other models. [ABSTRACT FROM AUTHOR]

Arctic cyclone activity is an important component of the local climate, and the frequent occurrence of extreme summer storms has raised widespread scientific interest. In this paper, we investigated the distinctive structural characteristics of intense summer Arctic cyclones by utilizing ERA‐Interim reanalysis data and employing a deep learning algorithm for cyclone detection. We found that the northern edge of Eurasia (i.e., the marginal ice zone (MIZ)) and the Alpha Ridge of Arctic Ocean (AR, i.e. central Arctic) are the two most active regions for intense Arctic cyclone activities in summer (from June to September). However, the surface conditions and coupling frequency between surface cyclone and tropopause polar vortices (TPVs) are distinct over these two regions. By further analysis of 100 intense cyclone activities in these two areas, respectively, we found that cyclones in MIZ are often smaller in size but higher in intensity at their maximum intensity, and their life cycles are generally shorter. MIZ cyclones are typically accompanied by a large Eady growth rate and frontal structure in the lower troposphere and their intensification primarily attributed to the thermal‐baroclinic process. In contrast, cyclones in AR are more frequently associated with higher potential vorticity (PV) values and pronounced PV downward intrusion from the stratosphere, as well as notable "upper warm‐lower cold" structures. The downward intrusion of TPVs and stratosphere vortices contribute to a decrease in the upper and column air mass deficit, leading to the intensification of surface Arctic cyclones in these regions. Plain Language Summary: In this study, we researched intense summer storms in the Arctic. We found that there are two main areas where these storms occur: the marginal ice zone (MIZ) near Eurasia and the Alpha Ridge (AR) in the central Arctic. However, storms in these two areas have different characteristics. In the MIZ, the storms are smaller but stronger, and they do not last as long. They are mainly driven by instability in the lower troposphere. On the other hand, the storms in AR respond more to the downward intrusion of potential vorticity from the stratosphere. These storms have a unique structure where the upper air is warmer than their surroundings, and the lower air is colder than their surroundings, especially in AR. This structure makes them more intense and longer‐lasting. Exploring these differences helps us understand how Arctic storms work, and how they might be affected by climate change. Key Points: Both the marginal ice zone (MIZ) and Alpha Ridge exhibit active summer Arctic cyclone activities, especially for intense stormsIn the MIZ, baroclinic instability plays a more prominent role in the intensification and maintenance of cyclonesCyclones in Alpha Ridge are more commonly accompanied by potential vorticity downward intrusion, and "upper warm‐lower cold" structures [ABSTRACT FROM AUTHOR]

In this paper, the 1978–2022 series of northern (NHSI) and southern (SHSI) hemisphere sea ice extent are submitted to singular spectral analysis (SSA). The trends are quasi-linear, decreasing for NHSI (by 58,300 km 2 /yr) and increasing for SHSI (by 15,400 km 2 /yr). The amplitude of annual variation in the Antarctic is double that in the Arctic. The semi-annual components are in quadrature. The first three oscillatory components of both NHSI and SHSI, at 1, 1/2, and 1/3 yr, account for more than 95% of the signal variance. The trends are respectively 21 (Antarctic) and 4 times (Arctic) less than the amplitudes of the annual components. We next analyze variations in pole position (PM for polar motion, coordinates m 1 , m 2 ) and length of day (lod). Whereas the SSA of the lod is dominated by the same first three components as sea ice, the SSA of the PM contains only the 1-yr forced annual oscillation and the Chandler 1.2-yr component. The 1-yr component of NHSI is in phase with that of the lod and in phase opposition with m1, while the reverse holds for the 1-yr component of SHSI. The semi-annual component appears in the lod and not in m 1 . The annual and semi-annual components of NHSI and SHSI are much larger than the trends, leading us to hypothesize that a geophysical or astronomical forcing might be preferable to the generally accepted forcing factors. The lack of modulation of the largest (SHSI) forced component does suggest an alternate mechanism. In Laplace's theory of gravitation, the torques exerted by the Moon, Sun, and planets play the leading role as the source of forcing (modulation), leading to changes in the inclination of the Earth's rotation axis and transferring stresses to the Earth's envelopes. Laplace assumes that all masses on and in the Earth are set in motion by astronomical forces; more than variations in eccentricity, it is variations in the inclination of the rotation axis that lead to the large annual components of melting and re-freezing of sea-ice. [ABSTRACT FROM AUTHOR]

Fjord systems are transition zones between land and sea, resulting in complex and dynamic environments. They are of particular interest in theArctic as they harbour ecosystems inhabited by a rich range of species and provide many societal benefits. The key drivers of change in the European Arctic (i.e., Greenland, Svalbard, and Northern Norway) fjord socio-ecological systems are reviewed here, structured into five categories: cryosphere (sea ice, glacier mass balance, and glacial and riverine discharge), physics (seawater temperature, salinity, and light), chemistry (carbonate system, nutrients), biology (primary production, biomass, and species richness), and social (governance, tourism, and fisheries). The data available for the past and present state of these drivers, aswell as futuremodel projections, are analysed in a companion paper. Changes to the two drivers at the base of most interactions within fjords, seawater temperature and glacier mass balance, will have the most significant and profound consequences on the future of European Arctic fjords. This is because even though governance may be effective at mitigating/adapting to local disruptions caused by the changing climate, there is possibly nothing that can be done to halt the melting of glaciers, the warming of fjord waters, and all of the downstream consequences that these two changes will have. This review provides the first transdisciplinary synthesis of the interactions between the drivers of changewithinArctic fjord socio-ecological systems. Knowledge of what these drivers of change are, and how they interact with one another, should provide more expedient focus for future research on the needs of adapting to the changing Arctic. [ABSTRACT FROM AUTHOR]

Satellite altimetry missions flying over the ice-covered Arctic Ocean have opened the possibility of further understanding changes in the ocean beneath the sea ice. This requires complex processing of satellite signals emerging from the sea surface in leads within the sea ice, with efforts to generate consistent Arctic-wide datasets of sea surface height ongoing. The aim of this paper is to provide and assess a novel gridded dataset of sea surface height anomaly and geostrophic velocity, which incorporates both the ice-covered and open ocean areas of the Arctic. Data from the CryoSat-2 mission in the period 2011–2020 were gridded at monthly intervals, up to 88 ∘ N, using the Data-Interpolating Variational Analysis (DIVA) method. To examine the robustness of our results, we compare our dataset to independent satellite data, mooring time series and Arctic-wide hydrographic observations. We find that our dataset is well correlated with independent satellite data at monthly timescales. Comparisons to in situ ocean observations show that our dataset provides reliable information on the variability of sea surface height and surface geostrophic currents over geographically diverse regions of the Arctic Ocean and different dynamical regimes and sea ice states. At all comparison sites we find agreement with in situ observed variability at seasonal to interannual timescales. Furthermore, we find that our geostrophic velocity fields can resolve the variability of boundary currents wider than about 50 km, a result relevant for studies of Arctic Ocean circulation. Additionally, large-scale seasonal features emerge. Sea surface height exhibits a wintertime Arctic-wide maximum, with the highest amplitude over the shelves. Also, we find a basin-wide seasonal acceleration of Arctic slope currents in winter. We suggest that this dataset can be used to study not only the large-scale sea surface height and circulation, but also the regionally confined boundary currents. The dataset is available in netCDF format from PANGAEA at 10.1594/PANGAEA.931869. [ABSTRACT FROM AUTHOR]

To assess the effect of ocean‐atmosphere coupling in the climate response to forced sea ice loss, the Polar Amplification Model Intercomparison Project protocol includes centennial coupled atmosphere‐ocean general circulation model simulations with imposed sea ice loss. The protocol, which specifies sea ice concentration and thickness distribution targets, does not prescribe a method for achieving them. Although different methods for imposing sea ice loss (or growth) in models have been documented, testing of the method‐dependence of the resulting climate responses has been limited. Achieving the targeted sea ice state has proven to be challenging using the so‐called ghost‐flux nudging method, which induces ice melt from below, as this method does not constrain the partitioning between thickness and concentration. We propose, describe and test a simple method that combines the advantages of direct sea ice nudging and ghost‐flux nudging. The hybrid nudging method better captures the partitioning between thickness and concentration while conserving total water content. We document how this novel sea ice constraining method reaches specific targets, enhances surface turbulent heat flux responses to sea ice loss, and induces tropospheric warming for both polar regions. Plain Language Summary: The Arctic is warming faster than the global average due to several processes that, once combined, lead to so‐called Arctic Amplification. Part of this anomalous polar warming comes from an intense reduction in ice cover allowing heat into the ocean, warming the Arctic ocean near the surface, hence melting more ice. A joint effort by several climate modeling groups called the Polar Amplification Model Intercomparison Project (PAMIP) aims at better understanding Arctic Amplification through a coordinated set of climate simulations. Among this ensemble of simulations is a set of centennial simulations performed with fully coupled state‐of‐the‐art climate models. In these experiments, Arctic (and Antarctic) sea ice are forced to reach specific states in order to better isolate Arctic Amplification and sea ice loss from the rest of anthropogenic global warming. In this paper, we propose a simple technique to nudge sea ice models to specific states such as prescribed by PAMIP. This new method combines advantages from existing techniques to improve the control over the extent and the thickness of the ice. We document how our novel method produces atmospheric warming and circulation responses that are more consistent with previously published results than the existing techniques. Key Points: Already established sea ice nudging method leads to issues in the partitioning between sea ice concentration (SIC) and sea ice thickness (SIT)New hybrid nudging method significantly improves capture of both SIC and SIT targets for Polar Amplification Model Intercomparison Project, in particular for Arctic sea iceHybrid scheme increases Arctic turbulent heat flux and warming [ABSTRACT FROM AUTHOR]

This paper is an intervention on the understanding of state identity in relation to (anticipatory) changes that have occurred, are taking place, and are expected to happen in the Arctic. Focusing specifically on the Finnish state's approach to the Arctic, we offer the concept of 'anticipatory state identity' in order to comprehend the role of 'anticipation' in developing and projecting a 'state identity.' In so doing, we argue that what drives Finland's vision to project itself to be(come) an 'Arctic state' is fuelled not only by placing a firm foothold in a region of increasing geopolitical importance but also by a consensus among wide‐ranging actors in prioritising Finnish Arcticness in its foreign policy. As such, we first shed light on the concept of 'anticipatory state identity.' Then we discuss the global and regional shifts that eventually drove Finland to focus on its Arcticness. Third, we delve into the components and enactments through which Finland projects its Arctic identity. Finally, we conclude that anticipatory state identity bridges the gap between a state's imagination of itself in the future and how such imaginations are materialised and embedded within state policies through a repetitive deployment of narratives and discourses by numerous practitioners in the present. Accordingly, the applicability of the concept moves beyond the Arctic context as it enables reading of (re)forming state identity in line with its anticipatory vision. With 'anticipatory state identity', we argue that what drives Finland's vision to project itself to be(come) an 'Arctic state' is fuelled not only by placing a firm foothold in a region of increasing geopolitical importance but also by a consensus among wide‐ranging actors in prioritising Finnish Arcticness in its foreign policy. [ABSTRACT FROM AUTHOR]

The Arctic is warming at more than twice the rate of the global average. This warming is influenced by clouds, which modulate the solar and terrestrial radiative fluxes and, thus, determine the surface energy budget. However, the interactions among clouds, aerosols, and radiative fluxes in the Arctic are still poorly understood. To address these uncertainties, the Ny-Ålesund Aerosol Cloud Experiment (NASCENT) study was conducted from September 2019 to August 2020 in Ny-Ålesund, Svalbard. The campaign's primary goal was to elucidate the life cycle of aerosols in the Arctic and to determine how they modulate cloud properties throughout the year. In situ and remote sensing observations were taken on the ground at sea level, at a mountaintop station, and with a tethered balloon system. An overview of the meteorological and the main aerosol seasonality encountered during the NASCENT year is introduced, followed by a presentation of first scientific highlights. In particular, we present new findings on aerosol physicochemical and molecular properties. Further, the role of cloud droplet activation and ice crystal nucleation in the formation and persistence of mixed-phase clouds, and the occurrence of secondary ice processes, are discussed and compared to the representation of cloud processes within the regional Weather Research and Forecasting Model. The paper concludes with research questions that are to be addressed in upcoming NASCENT publications. [ABSTRACT FROM AUTHOR]

One of the most urgent problems on which current studies of Arctic and subarctic territories are focused is how permafrost thawing can affect organic carbon fluxes and how these fluxes can influence the geochemistry of the surface and ground water. In addition to disturbing the carbon balance, permafrost thawing provokes the release of a significant amount of other chemical elements entering natural waters. The paper presents original data obtained by studying surface water in 2020 in the Yamalo–Nenets Autonomous District, which is situated in the Arctic zone of the Russian Federation. Permafrost is widespread in the study area, as also are facilities of the oil and gas industry. This predetermines the importance of research on the chemical composition of natural water, its formation, and ecological–geochemical status, which are critical aspects for assessing the anthropogenic load and predicting the influence of climate changes on the biogeochemical cycles of chemical elements. In the course of our fieldwork, 47 surface water samples were taken in the basins of the Taz, Pur, Ob, and Nadym rivers: 23 samples from rivers and streams and 24 samples from lakes and thaw depressions. The sampling sites were chosen to as comprehensively as possible cover the lake–stream–river system in the catchment areas of major rivers of the Yamalo–Nenets Autonomous District. The chemical composition of the water samples was analyzed at a certified laboratory using methods conventionally applied in solving such problems. The data were processed using statistical methods, including the principal component analysis (PCA). Data analysis demonstrates that surface water in the study area is ultrafresh, with neutral or weakly alkaline pH values. Hydrocarbonate, calcium, and magnesium ions dominate in the ionic composition of the water, and ammonium contents are high in the waters of the lakes and thaw depressions. In addition, the ammonium concentration strongly positively correlates with the content of dissolved organic carbon (DOC) and the values of chemical oxygen demand (COD) and permanganate index (PI). It was found out that the streams (springs and rivers) differ from the lakes and the water of the thaw depressions in higher concentrations of main ions that are brought to the water mainly by natural factors (these are , Ca2+, Mg2+, and Na+) and higher total dissolved solids (TDS) and pH values. In contrast, the water of the thaw depressions is characterized by the highest concentrations of DOC and the values of other parameters related to organic matter (N– , COD, and PI). It was shown that the main factors that control the chemical composition of the water are its interaction with organic matter from organic (peat) soil horizons and the mineral components of the underlying rocks and soils. The former factor most significantly impacts the water of the thaw depressions, and the latter one affects mainly the chemical composition of the rivers and streams. The relatively high contents of the chloride and sodium ions in the water of the largest lakes are probably caused by the anthropogenic load. [ABSTRACT FROM AUTHOR]

Human activities in the Arctic regions have been increasing in recent years due to the impacts of climate change, such as Arctic Sea ice decline. For example, there has been an increase in Arctic shipping routes. A robust navigation system with a high positioning accuracy is required when traversing the extremely challenging Arctic environment to ensure the safety of human activities. However, the high–precision GNSS navigation and the positioning method, e.g., real–time kinematic (RTK), is not available in the polar regions due to the accessibility issues of the required infrastructures. On the other hand, the International GNSS Service (IGS) enables real–time applications; additionally, quick and convenient satellite communication systems are also available. This offers the possibility of real–time precise point positioning (RT–PPP) with multi–GNSS for high-precision navigation in the Arctic. In our paper, we analyzed the performance of multi–GNSS RT–PPP in the Arctic Northeast Passage (NEP), highlighting the following contributions: First, a GNSS device is installed on the M/V TIANHUI, which passed through the NEP from 10 September to 20 September 2019; Second, we quantitatively evaluated the collected GNSS signals in terms of the maximum satellite elevations, number of visible satellites (NSAT), position dilution of precision (PDOP) values, signal–to–noise ratio (SNR), and multipath errors. Third, we evaluated the accuracy of the CLK93 real–time products compared with the Deutsches GeoForschungsZentrum (GFZ) final products GBM. Finally, we carried out experiments for both single– (SF) and dual–frequency (DF) RT–PPP in the NEP during the 11–day testing period. Our experimental results show that meter–level positioning accuracy can be achieved with SF RT–PPP, while the DF RT–PPP model reaches sub–decimeter values and even centimeter–level accuracy. In addition, using the multi–GNSS method, we showed that the average RMS values of DF RT–PPP in the horizontal and vertical directions are 0.080 m and 0.057 m, respectively, demonstrating an improvement of approximately 70% over single–GPS solutions. [ABSTRACT FROM AUTHOR]

Remote-sensing records over the last 40 years have revealed large year-to-year global and regional variability in Antarctic sea ice extent. Sea ice area and extent are useful climatic indicators of large-scale variability, but they do not allow the quantification of regions of distinct variability in sea ice concentration (SIC). This is particularly relevant in the marginal ice zone (MIZ), which is a transitional region between the open ocean and pack ice, where the exchanges between ocean, sea ice and atmosphere are more intense. The MIZ is circumpolar and broader in the Antarctic than in the Arctic. Its extent is inferred from satellite-derived SIC using the 15 %–80 % range, assumed to be indicative of open drift or partly closed sea ice conditions typical of the ice edge. This proxy has been proven effective in the Arctic, but it is deemed less reliable in the Southern Ocean, where sea ice type is unrelated to the concentration value, since wave penetration and free-drift conditions have been reported with 100 % cover. The aim of this paper is to propose an alternative indicator for detecting MIZ conditions in Antarctic sea ice, which can be used to quantify variability at the climatological scale on the ice-covered Southern Ocean over the seasons, as well as to derive maps of probability of encountering a certain degree of variability in the expected monthly SIC value. The proposed indicator is based on statistical properties of the SIC; it has been tested on the available climate data records to derive maps of the MIZ distribution over the year and compared with the threshold-based MIZ definition. The results present a revised view of the circumpolar MIZ variability and seasonal cycle, with a rapid increase in the extent and saturation in winter, as opposed to the steady increase from summer to spring reported in the literature. It also reconciles the discordant MIZ extent estimates using the SIC threshold from different algorithms. This indicator complements the use of the MIZ extent and fraction, allowing the derivation of the climatological probability of exceeding a certain threshold of SIC variability, which can be used for planning observational networks and navigation routes, as well as for detecting changes in the variability when using climatological baselines for different periods. [ABSTRACT FROM AUTHOR]

The application of the horizontal-to-vertical spectral ratio (HVSR) modeling and inversion techniques is becoming more and more widespread for assessing the seismic response and velocity model of soil deposits due to their effectiveness, environmental friendliness, relative simplicity and low cost. Nevertheless, a number of issues related to the use of these techniques in difficult natural conditions, such as in the shelf areas of the Arctic seas, where the critical structures are also designed, remain poorly understood. In this paper, we describe the features of applying the HVSR modeling and inversion techniques to seismic records obtained by ocean-bottom seismographs (OBS) on the outer shelf of the Laptev Sea. This region is characterized by high seismotectonic activity, as well as sparse submarine permafrost distribution and the massive release of bubble methane from bottom sediments. The seismic stations were installed for one year and their period of operation included periods of time when the sea was covered with ice and when the sea was ice-free. The results of processing of the recorded ambient seismic noise, as well as the wave recorder data and ERA5 and EUMETSAT reanalysis data, showed a strong dependence of seafloor seismic noise on the presence of sea ice cover, as well as weather conditions, wind speed in particular. Wind-generated gravity waves, as well as infragravity waves, are responsible for the increase in the level of ambient seismic noise. The high-frequency range of 5 Hz and above is strongly affected by the coupling effect, which in turn also depends on wind-generated gravity waves and infragravity waves. The described seafloor seismic noise features must be taken into account during HVSR modeling and interpretation. The obtained HVSR curves plotted from the records of one of the OBSs revealed a resonant peak corresponding to 3 Hz, while the curves plotted from the records of another OBS did not show clear resonance peaks in the representative frequency range. Since both OBSs were located in the area of sparse distribution of submarine permafrost, the presence of a resonance peak may be an indicator of the presence of a contrasting boundary of the upper permafrost surface under the location of the OBS. The absence of a clear resonant peak in the HVSR curve may indicate that the permafrost boundary is either absent at this site or its depth is beyond the values corresponding to representative seismic sensor frequency band. Thus, HVSR modeling and inversion techniques can be effective for studying the position of submarine permafrost. [ABSTRACT FROM AUTHOR]

This paper examines the processes that drive Arctic anomalous surface warming and sea ice loss during winter-season tropospheric energy flux events, synoptic periods of increased tropospheric energy flux convergence (Ftrop), using the NASA MERRA-2 reanalysis. During an event, a poleward anomaly in Ftrop initially increases the sensible and latent energy of the Arctic troposphere; as the warm and moist troposphere loses heat, the anomalous energy source is balanced by a flux upward across the tropopause and a downward net surface flux. A new metric for the Arctic surface heating efficiency (Etrop) is defined, which measures the fraction of the energy source that reaches the surface. Composites of high-, medium-, and low-efficiency events help identify key physical factors, including the vertical structure of Ftrop and Arctic surface preconditioning. In high-efficiency events (Etrop ≥ 0.63), a bottom-heavy poleward Ftrop occurs in the presence of an anomalously warm and unstratified Arctic—a consequence of decreased sea ice—resulting in increased vertical mixing, enhanced near-surface warming and moistening, and further sea ice loss. Smaller Etrop, and thus weaker surface impacts, are found in events with anomalously large initial sea ice extent and more vertically uniform Ftrop. These differences in Etrop are manifested primarily through turbulent heat fluxes rather than downward longwave radiation. The frequency of high-efficiency events has increased from the period 1980–99 to the period 2000–19, contributing to Arctic surface warming and sea ice decline. [ABSTRACT FROM AUTHOR]