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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]

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]

Revolutionary advances in artificial intelligence (AI) in the past decade have brought transformative innovation across science and engineering disciplines. 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, sea ice concentration and extent forecasting, motion detection, and 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 multimodal deep learning capabilities, enhancing model accuracy in measuring prediction uncertainty, better leveraging AI foundation models, and deepening 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 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]

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]

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]

The retreat of Arctic sea ice has opened new maritime routes, offering faster shipping opportunities; however, these routes present significant navigational challenges due to the harsh ice conditions. To address these challenges, this paper proposes a deep learning-based Arctic ice risk management architecture with multiple modules, including ice classification, risk assessment, ice floe tracking, and ice load calculations. A comprehensive dataset of 15,000 ice images was created using public sources and contributions from the Canadian Coast Guard, and it was used to support the development and evaluation of the system. The performance of the YOLOv8n-cls model was assessed for the ice classification modules due to its fast inference speed, making it suitable for resource-constrained onboard systems. The training and evaluation were conducted across multiple platforms, including Roboflow, Google Colab, and Compute Canada, allowing for a detailed comparison of their capabilities in image preprocessing, model training, and real-time inference generation. The results demonstrate that Image Classification Module I achieved a validation accuracy of 99.4%, while Module II attained 98.6%. Inference times were found to be less than 1 s in Colab and under 3 s on a stand-alone system, confirming the architecture's efficiency in real-time ice condition monitoring. [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.

Ice-coring auger machines can cost thousands of dollars and are generally made for vertical extraction from sea ice or glaciers. This project required specimens from ice accreted onto vertical piles at the Port of Alaska (POA) in Anchorage, Alaska, which meant the extraction was horizontal and had to be completed during the short low-tide window. In this paper, we describe the development of a method for economically harvesting and processing the accreted ice from the POA into cylindrical cores and shear beams. The ice was harvested by cutting large cubes out of the in situ mass with a chainsaw and then lifting these onto the port deck using a crane. The cubes were then transported to a laboratory walk-in freezer to be processed. Ice cores were drilled from the cubes using a custom-fabricated core bit made from metal tubing and hole saws. This simple core bit quickly produced smooth ice surfaces, provided there was a mechanism for evacuating the cut ice chips during drilling. To facilitate this, an alignment template was used to locate and drill two adjoining evacuation holes prior to coring. These evacuation holes had to be precisely located to be adjacent, parallel, and connected with the outside diameter of the forthcoming core, but were not allowed to impinge on the core. With this new method, an ice block can be converted into up to a dozen test-ready compression ice cores within a few hours. The variability in the diameter of the ice cores was found to be small, with a coefficient of variation of < 0.4%. [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.

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]

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]

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]

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 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]

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]

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 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]

Maritime historical documentary sources of weather and state of sea surface including sea ice can aid in filling a known climate knowledge gap for the Southern Ocean and Antarctica for the first half of the 20th century. This study presents a data set of marine climate, sea ice and icebergs recovered from a collection of logbooks from mainly Norwegian whaling factory ships that operated in the Southern Ocean during 1929–1940. The data set comprises some 8000 weather and 4000 sea ice/open sea records from austral summers of the study period. This paper further discusses the structure and content of most common Norwegian maritime documentary sources of the period along with the practices of logging information relevant for the study, such as time keeping, positioning and making weather observations. An emphasis was made on recovery of notes on sea ice and icebergs and their interpretation in terms of WMO categories of sea ice concentration. Data, including ship‐related metadata from all individual documents are homogenized and structured to a common machine‐readable format that simplifies its ingestion into relevant climate data depositories. [ABSTRACT FROM AUTHOR]

CryoSat‐2 has been successful in observing sea ice thickness from space by providing ice freeboard information. The initial estimate of the ice freeboard, called radar freeboard, is obtained by analyzing the observed waveform using a retracker. A series of corrections are needed to convert the radar freeboard to the ice freeboard. Those are the physical effects (e.g., changes in wave propagation speed and the distribution of scattering at snow and ice surfaces, etc.) and the bias of the retracker; however, traditionally, only the wave speed correction has been applied due to lack of enough information to perform the complete correction. Here, an alternative correction method for the CryoSat‐2 radar freeboard derived using the Threshold First‐Maximum Retracker Algorithm with a 50% threshold (TFMRA50) is proposed. Snow depth was used as a predictor for the correction, similar to the traditional wave speed correction, but the coefficients were empirically determined by performing a direct comparison of the radar freeboard from CryoSat‐2 and the ice freeboard from airborne observations. Consequently, this new empirical correction treats the physical effects and the retracker bias as a whole, which have been difficult to separate in the retrieval process. In this paper, we demonstrate that the retrieval accuracy of snow and ice variables and the consistency of the two independent retrieval methods are improved when the new correction is applied. The result of this study emphasizes the importance of compatibility between the retracker and the freeboard correction method. Plain Language Summary: Sea ice thickness and snow depth are considered essential climate variables because they are crucial for understanding climate change. The satellite CryoSat‐2 has successfully contributed to obtaining those variables by estimating the elevation of the sea ice surface from space. However, the estimation of the sea ice elevation can be affected by several error sources related to snow and ice conditions. Traditionally, it was challenging to perform a complete correction because there has not been enough detailed information on the snow and ice conditions. Considering the complex nature of sea ice, an alternative simple empirical correction method is proposed based on actual CryoSat‐2 and reference airborne observations. Accordingly, the proposed correction doesn't require detailed information on the surface conditions. We verify that the estimation of the snow and ice variables is improved when the new correction is applied. Additionally, the new correction also increases the consistency of two independent products. Based on its robustness and simplicity, we expect this new method to enhance our understanding of climate change by improving the quality of satellite snow and sea ice data. Key Points: The behavior of the CryoSat‐2 radar freeboard from the widely used retracker was found to be incompatible with conventional correctionAn alternative empirical method for improving the CryoSat‐2 radar‐to‐ice freeboard correction for a threshold retracker was developedThe new method can be generally applied to existing retrieval methods to improve the quality of snow depth and ice thickness retrievals [ABSTRACT FROM AUTHOR]

Sea ice surface patterns encode more information than can be represented solely by the ice fraction. The aim of this paper is thus to establish the importance of using a broader set of surface characterization metrics and to identify a minimal set of such metrics that may be useful for representing sea ice in Earth system models. Large-eddy simulations of the atmospheric boundary layer over various idealized sea ice patterns, with equivalent ice fractions and average floe areas, demonstrate that the spatial organization of ice and water can play a crucial role in determining boundary layer structures. Thus, various methods used to quantify heterogeneity in categorical lattice-based spatial data, such as those used in landscape ecology and Geographic Information System (GIS) studies, are employed here on a set of recently declassified high-resolution sea ice surface images. It is found that, in conjunction with ice fraction, patch density (representing the fragmentation of the surface), the splitting index (representing variability in patch size), and the perimeter–area fractal dimension (representing the tortuosity of the interface) are all required to describe the two-dimensional pattern exhibited by a sea ice surface. For surfaces with anisotropic patterns, the orientation of the surface relative to the mean wind is also needed. Finally, scaling laws are derived for these relevant landscape metrics, allowing for their estimation using aggregated spatial sea ice surface data at any resolution. The methods used in and the results gained from this study represent a first step toward developing further methods for quantifying variability in polar sea ice surfaces and for parameterizing mixed ice–water surfaces in coarse geophysical models. [ABSTRACT FROM AUTHOR]

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The Northern Sea Route (NSR) is a seasonal route. Its use by merchant ships that are not structurally adapted to navigation in heavy ice makes sense when it is free of ice along its entire length and can be used without the costly assistance of icebreakers. In the paper, ice cover maps were analyzed. The number of the Julian day of the year was determined on the first day on which the transit shipping season began, on the last day of the year after which this season ended, and the length of the ice-free period along the whole NSR was calculated. The analysis was carried out for the eastern and western parts of the NSR. Despite the high inter-year variability of the opening and closing times of the transit shipping season, it is possible, 2-3 months in advance, to obtain approximate information about the conditions of "ice-free" navigation on this route. For this purpose, average monthly sea ice extent of the Kara Sea in May of a given year should be used. [ABSTRACT FROM AUTHOR]

We present an overview of the UK's Global Sea Ice model configuration version 9 (GSI9), the sea ice component of the latest Met Office Global Coupled model, GC5. The GC5 configuration will, amongst other uses, form the physical basis for the HadGEM3 (Hadley Centre Global Environment Model version 3) climate model and UKESM2 (UK Earth System Model version 2) Earth system model that will provide the Met Office Hadley Centre/UK model contributions to CMIP7 (Coupled Model Intercomparison Project Phase 7). Although UK ocean model configurations have been developed for many years around the NEMO (Nucleus for European Modelling of the Ocean) ocean modelling framework, the GSI9 configuration is the first UK sea ice model configuration to use the new native NEMO sea ice model, SI3 (Sea Ice modelling Integrated Initiative). This replaces the CICE (Community Ice CodE) model used in previous configuration versions. In this paper we document the physical and technical options used within the GSI9 sea ice configuration. We provide details of the implementation of SI3 into the Met Office coupled model and the adaptations required to work with our "conductivity coupling" approach and provide a thorough description of the GC5 coupling methodology. A brief evaluation of sea ice simulated by the GC5 model is included, with results compared to observational references and a previous Global Coupled model version (GC3.1) used for CMIP6, to demonstrate the scientific credibility of the results. [ABSTRACT FROM AUTHOR]

In light of the rapid Arctic warming and continuous reduction in Arctic Sea ice, the complex two-way Arctic–midlatitudes connection has become a focal point in recent climate research. In this paper, we review the current understanding of the interactive influence between midlatitude atmospheric variability and Arctic Sea ice or thermal conditions on interannual timescales. As sea ice diminishes, in contrast to the Arctic warming (cooling) in boreal winter (summer), Eurasia and North America have experienced anomalously cold (warm) conditions and record snowfall (rainfall), forming an opposite oscillation between the Arctic and midlatitudes. Both statistical analyses and modeling studies have demonstrated the significant impacts of autumn–winter Arctic variations on winter midlatitude cooling, cold surges, and snowfall, as well as the potential contributions of spring–summer Arctic variations to midlatitude warming, heatwaves and rainfall, particularly focusing on the role of distinct regional sea ice. The possible physical processes can be categorized into tropospheric and stratospheric pathways, with the former encompassing the swirling jet stream, horizontally propagated Rossby waves, and transient eddy–mean flow interaction, and the latter manifested as anomalous vertical propagation of quasi-stationary planetary waves and associated downward control of stratospheric anomalies. In turn, atmospheric prevailing patterns in the midlatitudes also contribute to Arctic Sea ice or thermal condition anomalies by meridional energy transport. The Arctic–midlatitudes connection fluctuates over time and is influenced by multiple factors (e.g., continuous melting of climatological sea ice, different locations and magnitudes of sea ice anomalies, internal variability, and other external forcings), undoubtedly increasing the difficulty of mechanism studies and the uncertainty surrounding predictions of midlatitude weather and climate. In conclusion, we provide a succinct summary and offer suggestions for future research. [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]

Earth's climate exhibits internal modes of variability on various time scales. Here we investigate multi-decadal variability of the Atlantic meridional overturning circulation (AMOC) in the control runs of an ensemble of CMIP5 models. By decomposing global- mean-temperature (GMT) variance into contributions of the AMOC and Northern Hemisphere sea-ice extent using a graph-theoretical statistical approach, we find the AMOC to contribute 8% to GMT variability in the ensemble mean. Our results highlight the importance of AMOC sea-ice feedbacks that explain 5% of the GMT variance, while the contribution solely related to the AMOC is found to be about 3 %. As a consequence of multi-decadal AMOC variability, we report substantial variations in North Atlantic deepocean heat content with trends of up to 0.7×1022 J decade-1 that are of the order of observed changes over the last decade and consistent with the reduced GMT warming trend over this period. Although these temperature anomalies are largely density-compensated by salinity changes, we find a robust negative correlation between the AMOC and North Atlantic deep-ocean density with density lagging the AMOC by 5 to 11 yr in most models. While this would in principle allow for a self-sustained oscillatory behavior of the coupled AMOC-deep-ocean system, our results are inconclusive about the role of this feedback in the model ensemble. [ABSTRACT FROM AUTHOR]