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This study quantifies the state of the art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multimodel dataset of retrospective seasonal predictions of September Arctic sea ice is created and analyzed, consisting of community contributions from 17 statistical models and 17 dynamical models. Prediction skill is compared over the period 2001–20 for predictions of pan-Arctic sea ice extent (SIE), regional SIE, and local sea ice concentration (SIC) initialized on 1 June, 1 July, 1 August, and 1 September. This diverse set of statistical and dynami- cal models can individually predict linearly detrended pan-Arctic SIE anomalies with skill, and a multimodel median prediction has correlation coefficients of 0.79, 0.86, 0.92, and 0.99 at these respective initialization times. Regional SIE predictions have similar skill to pan-Arctic predictions in the Alaskan and Siberian regions, whereas regional skill is lower in the Canadian, Atlantic, and central Arctic sectors. The skill of dynamical and statistical models is generally comparable for pan-Arctic SIE, whereas dynamical models outperform their statistical counterparts for regional and local predictions. The prediction systems are found to provide the most value added relative to basic reference forecasts in the extreme SIE years of 1996, 2007, and 2012. SIE prediction errors do not show clear trends over time, suggesting that there has been minimal change in inherent sea ice predictability over the satellite era. Overall, this study demonstrates that there are bright prospects for skillful operational predictions of September sea ice at least 3 months in advance. 

Abstract The shrinking of Arctic-wide September sea ice extent is often cited as an indicator of modern climate change; however, the timing of seasonal sea ice retreat/advance and the length of the open-water period are often more relevant to stakeholders working at regional and local scales. Here we highlight changes in regional open-water periods at multiple warming thresholds. We show that, in the latest generation of models from the Coupled Model Intercomparison Project (CMIP6), the open-water period lengthens by 63 days on average with 2 °C of global warming above the 1850-1900 average, and by over 90 days in several Arctic seas. Nearly the entire Arctic, including the Transpolar Sea Route, has at least 3 months of open water per year with 3.5 °C warming, and at least 6 months with 5 °C warming. Model bias compared to satellite data suggests that even such dramatic projections may be conservative. 

Abstract As the Arctic continues to warm faster than the rest of the planet, evidence mounts that the region is experiencing unprecedented environmental change. The hydrological cycle is projected to intensify throughout the twenty-first century, with increased evaporation from expanding open water areas and more precipitation. The latest projections from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) point to more rapid Arctic warming and sea-ice loss by the year 2100 than in previous projections, and consequently, larger and faster changes in the hydrological cycle. Arctic precipitation (rainfall) increases more rapidly in CMIP6 than in CMIP5 due to greater global warming and poleward moisture transport, greater Arctic amplification and sea-ice loss and increased sensitivity of precipitation to Arctic warming. The transition from a snow- to rain-dominated Arctic in the summer and autumn is projected to occur decades earlier and at a lower level of global warming, potentially under 1.5 °C, with profound climatic, ecosystem and socio-economic impacts. 

Abstract The sub-kilometre scale distribution of snow depth on Arctic sea ice impacts atmosphere-ice fluxes of energy and mass, and is of importance for satellite estimates of sea-ice thickness from both radar and lidar altimeters. While information about the mean of this distribution is increasingly available from modelling and remote sensing, the full distribution cannot yet be resolved. We analyse 33 539 snow depth measurements from 499 transects taken at Soviet drifting stations between 1955 and 1991 and derive a simple statistical distribution for snow depth over multi-year ice as a function of only the mean snow depth. We then evaluate this snow depth distribution against snow depth transects that span first-year ice to multiyear ice from the MOSAiC, SHEBA and AMSR-Ice field campaigns. Because the distribution can be generated using only the mean snow depth, it can be used in the downscaling of several existing snow depth products for use in flux modelling and altimetry studies. 

Abstract. Wind-driven redistribution of snow on sea ice alters itstopography and microstructure, yet the impact of these processes on radarsignatures is poorly understood. Here, we examine the effects of snowredistribution over Arctic sea ice on radar waveforms and backscattersignatures obtained from a surface-based, fully polarimetric Ka- and Ku-bandradar at incidence angles between 0∘ (nadir) and 50∘.Two wind events in November 2019 during the Multidisciplinary drifting Observatory forthe Study of Arctic Climate (MOSAiC) expedition are evaluated. During both events, changes in Ka- andKu-band radar waveforms and backscatter coefficients at nadir are observed,coincident with surface topography changes measured by a terrestrial laserscanner. At both frequencies, redistribution caused snow densification atthe surface and the uppermost layers, increasing the scattering at theair–snow interface at nadir and its prevalence as the dominant radar scattering surface. The waveform data also detected the presence of previousair–snow interfaces, buried beneath newly deposited snow. The additionalscattering from previous air–snow interfaces could therefore affect therange retrieved from Ka- and Ku-band satellite altimeters. With increasingincidence angles, the relative scattering contribution of the air–snowinterface decreases, and the snow–sea ice interface scattering increases.Relative to pre-wind event conditions, azimuthally averaged backscatter atnadir during the wind events increases by up to 8 dB (Ka-band) and 5 dB (Ku-band). Results show substantial backscatter variability within the scanarea at all incidence angles and polarizations, in response to increasingwind speed and changes in wind direction. Our results show that snowredistribution and wind compaction need to be accounted for to interpretairborne and satellite radar measurements of snow-covered sea ice.

 

Abstract The timing of melt onset in the Arctic plays a key role in the evolution of sea ice throughout Spring, Summer and Autumn. A major catalyst of early melt onset is increased downwelling longwave radiation, associated with increased levels of moisture in the atmosphere. Determining the atmospheric moisture pathways that are tied to increased downwelling longwave radiation and melt onset is therefore of keen interest. We employed Self Organizing Maps (SOM) on the daily sea level pressure for the period 1979–2018 over the Arctic during the melt season (April–July) and identified distinct circulation patterns. Melt onset dates were mapped on to these SOM patterns. The dominant moisture transport to much of the Arctic is enabled by a broad low pressure region stretching over Siberia and a high pressure over northern North America and Greenland. This configuration, which is reminiscent of the North American-Eurasian Arctic dipole pattern, funnels moisture from lower latitudes and through the Bering and Chukchi Seas. Other leading patterns are variations of this which transport moisture from North America and the Atlantic to the Central Arctic and Canadian Arctic Archipelago. Our analysis further indicates that most of the early and late melt onset timings in the Arctic are strongly related to the strong and weak emergence of these preferred circulation patterns, respectively. 

Arctic communities are experienced with severe weather, but impacts can still be serious, particularly when the intensity or persistence of hazardous conditions is extreme. Such was the case for the community of Clyde River (Kangiqtugaapik), Nunavut, Canada, which experienced 33 blizzard days during winter 2021/22—likely the most at Clyde River since at least 1978/79. Blizzard conditions resulted from unusually frequent high winds rather than excessive snowfall. The most severe stretch included eight blizzard days over an 11-day period, with top wind gusts of 98 km h⁻¹. Winds caused severe drifting, covering homes and blocking streets. Broken heavy equipment, including snow-clearing machines, compounded the impacts, leaving homes without essential services like water delivery and sewage pump-out for days. Residents reported the storms and resulting impacts as some of the worst in memory. The drifting and volume of snow, combined with the lack of available resources to manage it, obliged the community to declare a state of emergency. Projections of increased Arctic precipitation and extreme weather events points to the need for communities to have proper resources and supports, including preparedness and adaptation and mitigation strategies, so they can be better equipped to handle storm and blizzard impacts such as those experienced at Clyde River in the winter of 2021/22. Additional steps that can be implemented to better support and prepare communities include investing in preparedness planning, expanded and enhanced weather information and services, community land-based programming to transfer Inuit knowledge and skills, assessing the usefulness of current forecasts, and new approaches to community planning.

In this study, we consider the winter of 2021/22, during which the community of Clyde River (Kangiqtugaapik), Nunavut experienced 33 days with blizzard conditions—more than any other year since at least 1978/79. Blizzards are characterized by strong winds and blowing snow. Low visibility impedes travel, and drifting snow blocks roads and can bury equipment and buildings. In this case, broken snow-clearing equipment and other infrastructure challenges also hampered the community’s ability to respond, and residents went days without essential services. Several studies suggest that extreme winds will become more common in the Baffin Bay region in the future. This study demonstrates the need for proper resourcing of communities for preparedness, response, and adaptation strategies, especially with the possibility of extreme winter weather becoming more common.