Petteri Uotila

Satellite measurements indicate that the Barents and Kara Seas have experienced some of the most significant sea ice declines and increases in sea surface temperature in the Arctic. Understanding the processes driving these changes is of utmost importance to assess the implications of climate change in the Arctic and globally. Given the observational limitations in these high-latitude areas, coupled models and reanalysis products play a key role. However, it is essential to determine how reliably these products represent the observed sea ice decline and mixed-layer warming. Models are often evaluated on a pan-Arctic scale, but the model skill might differ when considering sub-regions. This study examines two coupled regional climate models (HIRHAM–NAOSIM 2.2 and RASM), two regional ocean reanalyses (RARE 1.15.2 and TOPAZ 4B), one global ocean reanalysis (ORAS5), and OSI SAF satellite observations over the period 1991–2020. We focus on spring (March–May) and autumn (August–October) sea ice area and sea ice concentration, the edge of the sea ice, and the temperature of the mixed layer. We also examine correlations between sea ice and mixed-layer temperature anomalies and five climate indices to assess how the datasets respond to large-scale climate variability. The results show a statistically significant decrease in sea ice area and sea ice concentration in the satellite measurements and in all reanalyses. However, HIRHAM–NAOSIM shows only a near-significant decline in the Barents Sea, RASM shows no long-term change, and none of the two models shows a significant trend in the Kara Sea. Additionally, the reanalyses show a more pronounced warming of the mixed layer than the coupled models, particularly in autumn and in the Kara Sea. ORAS5 and TOPAZ agree most closely with the observed sea ice, partly because assimilated observations constrain their historical states, whereas RARE reproduces the decreasing trends but overestimates sea ice and shows anomalous mixed-layer temperature behaviour in the Barents Sea. The reanalyses also represent the relationships with the climate indices more consistently than the coupled models, particularly for the Atlantic Multidecadal Oscillation and the Northern Hemisphere ocean heat content. Among the coupled models, HIRHAM–NAOSIM represents changes in the Barents Sea better than RASM, but in the Kara Sea, where none of the models captures the decreasing trends, RASM has a more realistic mean sea-ice state. Although the coupled models reproduce interannual variability, the results indicate that in particular the effects of large-scale changes of the ocean circulation are not realistically reproduced in the coupled models.

Snow depth on Antarctic sea ice is a critical climate variable affecting energy and mass balance, yet its observation and modeling remain challenging. We present a systematic intercomparison of snow depth from six ocean reanalysis products, two satellite retrievals, and ship‐based and airborne observational constraints. Results indicate that reanalysis and satellite products show consistent large‐scale climatological snow depth patterns, with the highest depths in the Weddell Sea. However, substantial differences remain in magnitude, seasonal phasing, spatial variability, and trends. The multi‐model mean agrees with satellite‐derived products in some integrated metrics, but tends to smooth regional features and may reflect compensation among reanalysis members. The sensitivity of simulated snow depth to atmospheric forcing and simplified snow processes highlights current limitations in representing wind redistribution and snow‐to‐ice conversion. Improved observations and model physics are needed to better constrain Antarctic sea‐ice snow depth.

Satellite measurements indicate that the Barents and Kara Seas have experienced some of the most significant declines in sea ice concentration and an increase in sea surface temperature in the Arctic. Understanding the processes driving these changes is of utmost importance to assess the implications of climate change in the Arctic and globally. Given the observational limitations in these high-latitude areas, coupled models and reanalysis products play a key role. However, it is essential to better understand the strengths and limitations of such data products. Models are often evaluated on a pan-Arctic scale, but results might differ when considering sub-regions. This study examines two regional coupled ocean-atmosphere models (HIRHAM-NAOSIM 2.2 and RASM), two coupled model intercomparison project, phase 6 (CMIP6) models (CNRM-ESM2_1, NorESM2-MM), two regional ocean reanalyses (RARE 1.15.2 and TOPAZ 4B), one global reanalysis (ORAS5) and OSI-SAF satellite observations over the period 1991–2020. We focus on spring (March–April–May) and autumn (August–September–October) sea ice area and sea ice concentration, the edge of the sea ice, and the temperature of the mixed layer. The results show a statistically significant decrease in sea ice area and sea ice concentration in the satellite measurements and in all reanalyses. However, only one of the coupled models, HIRHAM–NAOSIM, exhibits a statistically significant sea ice decline in the Barents Sea, albeit weaker than in the reanalyses, and no coupled model shows a significant trend in the Kara Sea. Additionally, the reanalyses show a more pronounced warming of the mixed layer than the coupled models, particularly in autumn and in the Kara Sea.

Satellite measurements indicate that the Barents and Kara Seas have experienced some of the most significant declines in sea ice concentration and an increase in sea surface temperature in the Arctic. Understanding the processes driving these changes is of utmost importance to assess the implications of climate change in the Arctic and globally. Given the observational limitations in these high-latitude areas, coupled models and reanalysis products play a key role. However, it is essential to better understand the strengths and limitations of such data products. Models are often evaluated on a pan-Arctic scale, but results might differ when considering sub-regions. This study examines two regional coupled ocean-atmosphere models (HIRHAM-NAOSIM 2.2 and RASM), two coupled model intercomparison project, phase 6 (CMIP6) models (CNRM-ESM2_1, NorESM2-MM), two regional ocean reanalyses (RARE 1.15.2 and TOPAZ 4B), one global reanalysis (ORAS5) and OSI-SAF satellite observations over the period 1991–2020. We focus on spring (March–April–May) and autumn (August–September–October) sea ice area and sea ice concentration, the edge of the sea ice, and the temperature of the mixed layer. The results show a statistically significant decrease in sea ice area and sea ice concentration in the satellite measurements and in all reanalyses. However, only one of the coupled models, HIRHAM–NAOSIM, exhibits a statistically significant sea ice decline in the Barents Sea, albeit weaker than in the reanalyses, and no coupled model shows a significant trend in the Kara Sea. Additionally, the reanalyses show a more pronounced warming of the mixed layer than the coupled models, particularly in autumn and in the Kara Sea.

Understanding of the local effects of sea-ice concentration (SIC) variations on the Arctic atmosphere is a prerequisite for assessing the role of Arctic sea-ice decline in the climate system, including its influence on mid-latitudes. In this study, we analysed the relationships between SIC and both temperature and specific humidity at the surface and 2 m level, as well as at 950, 850, 750, and 600 hPa across the circumpolar Arctic. The role of wind speed and direction in the relationships between SIC and both temperature and specific humidity is discussed. We applied linear ordinary-least-square-regression analysis to detrended anomalies of monthly means of data from the NCEP/CFSR atmospheric reanalysis for 1980–2021. The results show the strongest correlations between SIC and temperature, as well as between SIC and specific humidity, in the marginal ice zone during the cold seasons (November–April) with the coefficient of determination ( R ² ) around 0.6 at the surface and near-surface levels and around 0.3 at 950 and 850 hPa. We interpret the statistical results for these cold seasons so that SIC affects air temperature and specific humidity, while the effects of air temperature variations are limited. SIC correlates somewhat better with specific humidity than with temperature, which can be attributed to the exponential dependence of saturation specific humidity on temperature. In the Central Arctic, physical conditions are favourable for high R ² values, but low variability in SIC reduces the correlations. In contrast, in regions such as the northern Barents Sea, increased November–April SIC variability from 1980–2000 to 2001–2021 strengthens the correlations, even though previous studies showed that surface heat and moisture fluxes become less sensitive to SIC in a warming climate. This finding suggests that statistical effects can outweigh the physical sensitivity in shaping observed relationships. During the warm seasons (May–October), high enough air temperatures reduce SIC via melting, while the effect of SIC on air temperature and specific humidity cannot be large, as the surface temperature of the sea ice is very close to that of the open ocean. The relationships between SIC and both temperature and specific humidity are generally weaker during these warm seasons with R ² at the surface and near-surface levels around 0.4 over the marginal ice zone during May–July and across the entire sea-ice zone during August–October.

Short-term changes in Arctic sea-ice concentration (SIC) are largely driven by weather, and strong ice loss typically occurs during intense Arctic cyclones causing unusually warm and stormy conditions. Such conditions are prolonged when several cyclones follow rapidly on each other. Here, we analyze changes in SIC for such periods of serial cyclone clustering utilizing satellite observations and reanalysis data from 1979-2024. While cyclones generally decrease SIC compared to non-cyclone conditions, cyclone clusters impact the ice approximately 2.5 times longer and cause two times stronger overall SIC-reductions than solitary cyclones. The amount of SIC-loss due to cyclone clusters scales with the intensity and number of clustered cyclones, and intensified SIC-loss occurs from 2004-2024 compared to 1979-1999, even within fixed SIC-categories. These findings highlight the relevance of accumulated impacts of clustered weather events for Arctic sea-ice variability and emphasize the need to understand drivers of serial cyclone clustering in the Arctic.

Satellite measurements indicate that the Barents and Kara Seas have experienced some of the most significant declines in sea ice concentration and an increase in sea surface temperature in the Arctic. Understanding the processes driving these changes is of utmost importance to assess the implications of climate change in the Arctic and globally. Given the observational limitations in these high-latitude areas, coupled models and reanalysis products play a key role. However, it is essential to better understand the strengths and limitations of such data products. Models are often evaluated on a pan-Arctic scale, but results might differ when considering sub-regions. This study examines two regional coupled ocean-atmosphere models (HIRHAM-NAOSIM 2.2 and RASM), two coupled model intercomparison project, phase 6 (CMIP6) models (CNRM-ESM2_1, NorESM2-MM), two regional ocean reanalyses (RARE 1.15.2 and TOPAZ 4B), one global reanalysis (ORAS5) and OSI-SAF satellite observations over the period 1991–2020. We focus on spring (March–April–May) and autumn (August–September–October) sea ice area and sea ice concentration, the edge of the sea ice, and the temperature of the mixed layer. The results show a statistically significant decrease in sea ice area and sea ice concentration in the satellite measurements and in all reanalyses. However, only one of the coupled models, HIRHAM–NAOSIM, exhibits a statistically significant sea ice decline in the Barents Sea, albeit weaker than in the reanalyses, and no coupled model shows a significant trend in the Kara Sea. Additionally, the reanalyses show a more pronounced warming of the mixed layer than the coupled models, particularly in autumn and in the Kara Sea.

Identifying the full suite of processes that drive the melting of Antarctic sea ice each summer is crucial to improving the currently-poor ability of contemporary models to accurately simulate the climatological retreat phase of the annual sea-ice cycle. This is critical to (1) understanding and attributing observed trends and recent abrupt changes in sea-ice coverage and (2) the more robust prediction of future sea-ice conditions and impacts. This paper identifies wave-driven processes that can accelerate the seasonal melting of sea ice both in the marginal ice zone (MIZ) and in open-water areas within the interior sea-ice zone (SIZ). It builds on the long-held view that seasonal Antarctic sea-ice ablation is primarily driven by ice-floe lateral and basal melting enhanced in the MIZ by wave breakup of ice floes, by demonstrating that ocean waves play important additional roles in generating surface and interior melting (termed “wave melting”) via three sets of processes: “wave flooding”, “wave pulverisation”, and “wave greening” (involving algal proliferation in wave-modified ice). Based on existing observations and simple one-dimensional modelling, these wave processes are estimated to reduce ice albedo by 0.38–0.64 compared to snow-covered ice, resulting in vertical melt-rate enhancements of 0.9–5.2 cm d⁻¹ amplified by wave greening to 1.1–6.1 cm d⁻¹. The study also identifies five positive feedback and sub-feedback mechanisms that likely accelerate the ice melting further. It addresses a gap in current climate and Earth system models, which account for wave effects on floe-size distributions but overlook these coupled wave-driven dynamic, thermodynamic and biological processes that may contribute to explaining why and how Antarctic sea ice can melt back so rapidly each summer. An intention of this foundational study is to stimulate further targeted investigation aimed at quantifying the role of wave melting in the annual sea-ice cycle – as well as the contribution of wave greening to primary production in the sea-ice zone and its role in key biogeochemical processes that feed back to climate. The work has implications for planetary albedo, global climate feedbacks, marine ecosystems, and the accuracy of future sea-ice and climate projections in an increasingly-stormy Southern Ocean, as well as in a changing Arctic.

Satellite measurements indicate that the Barents and Kara Seas have experienced some of the most significant declines in sea ice concentration and an increase in sea surface temperature in the Arctic. Understanding the processes driving these changes is of utmost importance to assess the implications of climate change in the Arctic and globally. Given the observational limitations in these high-latitude areas, coupled models and reanalysis products play a key role. However, it is essential to better understand the strengths and limitations of such data products. Models are often evaluated on a pan-Arctic scale, but results might differ when considering sub-regions. This study examines two regional coupled ocean-atmosphere models (HIRHAM-NAOSIM 2.2 and RASM), two coupled model intercomparison project, phase 6 (CMIP6) models (CNRM-ESM2_1, NorESM2-MM), two regional ocean reanalyses (RARE 1.15.2 and TOPAZ 4B), one global reanalysis (ORAS5) and OSI-SAF satellite observations over the period 1991–2020. We focus on spring (March–April–May) and autumn (August–September–October) sea ice area and sea ice concentration, the edge of the sea ice, and the temperature of the mixed layer. The results show a statistically significant decrease in sea ice area and sea ice concentration in the satellite measurements and in all reanalyses. However, only one of the coupled models, HIRHAM–NAOSIM, exhibits a statistically significant sea ice decline in the Barents Sea, albeit weaker than in the reanalyses, and no coupled model shows a significant trend in the Kara Sea. Additionally, the reanalyses show a more pronounced warming of the mixed layer than the coupled models, particularly in autumn and in the Kara Sea.