Driven by growing impacts of changing precipitation amounts and phase on the Arctic's natural and built environment, we examine seasonal patterns and trends in Arctic precipitation and partitioning between its liquid and solid forms. Use is made of data from ERA5 reanalysis, Automated Surface Observing System stations over land, and a climatology based on present weather reports over the Arctic Ocean. In the Atlantic sector of the Arctic, most precipitation falls in liquid form in all seasons in its southern limits, but snowfall is high over its northern parts. Precipitation over the dry central Arctic Ocean and terrestrial polar deserts almost always falls as snow. Even during the summer, typically 50 % of precipitation over the central Arctic Ocean falls as snow. Over land, nearly all summer precipitation falls in liquid form, except in the Canadian Arctic Archipelago where summer snowfall is still common. Annual precipitation has increased since 1979, primarily in the Barents Sea sector, accompanied by generally downward trends in snowfall and, hence, upward trends in liquid precipitation. Across much of the Arctic, the liquid to total precipitation ratio has increased only in summer and autumn, while in the Atlantic sector, the liquid to total precipitation ratio has increased in fall and winter.

To address research gaps in understanding Arctic Amplification, we use data from ERA5, an observational surface temperature dataset, and sea ice concentration to examine the seasonal, spatial and decadal evolution of Arctic 2 m and lower tropospheric temperatures and lower tropospheric (surface to 850 hPa) static stability over the past 45 years. A Local Amplification Anomaly (LAA) metric is used to examine how spatial patterns of Arctic 2 m temperature anomalies compare to anomalies for the globe as a whole. Pointing to impacts of seasonally-delayed albedo feedback, growing areas of end-of-summer (September) open water largely co-locate with the strongest positive anomalies of 2 m temperatures through autumn and winter and their growth through time; small summer trends reflect the effects of a melting sea ice cover. Because of seasonal ice growth, the association between rising 2 m temperatures and sea ice weakens from autumn into winter, except in the Barents Sea where there have been prominent downward trends in winter ice extent. Imprints of variable atmospheric circulation are prominent in the Arctic temperature evolution. Low-level (surface to 850 hPa) stability over the Arctic increases from autumn through winter, consistent with the greater depth of surface-based atmospheric heating seen in autumn. However, trends towards weaker static stability dominate the Arctic Ocean in autumn and winter, especially over areas of September and wintertime ice loss. Sea ice thinning, leading to increased conductive heat fluxes though the ice, likely also contributes to reduced stability.

What is the relative importance of variability in local evaporation versus moisture convergence from lower latitudes to changes in autumn/winter Arctic Ocean precipitation? Past research has offered sometimes contradictory answers. Here we offer some resolution to this question by addressing two research gaps. First, recognizing that most studies ascribing greater local evaporation (and sea ice loss) to increasing Arctic precipitation have been conducted with climate models, we turn to the ERA5 atmospheric reanalysis to examine a 46-year record (1979-2024) of Arctic precipitation and related moisture, circulation, and radiation variables. Second, we focus attention on precipitation specifically associated with extratropical cyclones, offering insights beyond what can be gained by only looking at Arctic-wide seasonal averages. We find that cyclone-associated precipitation (CAP) over the Arctic Ocean primarily changes in the cold season (October-March), increasing by 5.3% per decade. Spatial patterns of positive CAP trends along the margins of the Arctic Ocean align closely with patterns of sea ice loss and enhanced local evaporation and typically exhibit negative trends in moisture convergence. Conversely, the area around the North Pole, with no significant sea ice loss, has experienced more modest precipitation increases driven by enhanced moisture convergence. For the Arctic Ocean overall, 78% of the increase in cold-season CAP is explained by the increase in local evaporation. A complementary Lagrangian moisture budget analysis of migratory cyclones yields more uncertainty but also shows enhanced local evaporation as the greatest driver of enhanced cold season precipitation.

The Arctic has been warming much faster than the global average, known as Arctic amplification. The active layer is seasonally frozen in winter and thaws in summer. In the 2017 Arctic Boreal Vulnerability Experiment (ABoVE) airborne campaign, airborne L- and P- band synthetic aperture radar (SAR) was used to acquire a dataset of active layer thickness (ALT) and vertical soil moisture profile, at 30 m resolution for 51 swaths across the ABoVE domain. Using a thawing degree day (TDD) model, ALT=K root TDD, we estimated ALT along the ABoVE swaths employing the 2-m air temperature from ERA5. The coefficient (K) calibrated has an R2=0.9783. We also obtained an excellent fit between ALT and K root(TDD/theta) where theta is the soil moisture from ERA5 (R2=0.9719). Output based on shared-social economic pathway (SSP) climate scenarios SSP 1-2.6, SSP 2-4.5, and SSP 5-8.5 from seven global climate models (GCMs), statistically downscaled to 25-km resolution, was used to project the impacts of climate warming on ALT. Assuming ALT=K root TDD, the projections of UKESM1-0-LL GCM resulted in the largest projected ALT, up to about 0.7 m in 2080s under SSP5-8.5. Given that the mean observed ALT of the study sites is about 0.482 m, this implies that ALT will increase by 0.074 to 0.217 m (15% and 45%) in 2080s. This will have substantial impacts on Arctic infrastructure. The projected settlement Iset (cm) of 1 to 7 cm will also impact the infrastructure, especially by differential settlement due to the high spatial variability of ALT and soil moisture, given at local scale the actual thawing will partly depend on thaw sensitivity of the material and potential thaw strain, which could vary widely from location to location.

Arctic rain-on-snow (ROS) events can have significant impacts on Arctic wildlife and socio-economic systems. This study addresses the meteorology of two different Arctic ROS events. The first, occurring near Nuuk, Greenland, generated significant impacts, including slush avalanches. The second, less severe, event occurred within the community of Iqaluit, Nunavut, Canada. This research utilizes atmospheric reanalysis, automated surface observation station data and atmospheric soundings to determine the meteorological conditions driving these events and the differences between each case. In both cases, atmospheric blocking played a leading role in ROS initiation, with atmospheric rivers – narrow bands of high water vapor transport, typically originating from the tropics and subtropics – having both direct and indirect effects. Cyclone-induced low-level jets and resultant ‘warm noses’ of higher air temperatures and moisture transport were other key features in ROS generation. To our knowledge, our study is the first to visualize how the varying strength and manifestation of these coupled features contribute to differences in the severity of Arctic ROS events. The meteorological drivers identified here find support from other studies on Arctic ROS events and are similar to weather features associated with Arctic precipitation events of extreme magnitude.

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 h21. 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. Projec-tions 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.

Arctic rain on snow (ROS) deposits liquid water onto existing snowpacks. Upon refreezing, this can form icy crusts at the surface or within the snowpack. By altering radar backscatter and microwave emissivity, ROS over sea ice can influence the accuracy of sea ice variables retrieved from satellite radar altimetry, scatterometers, and passive microwave radiometers. During the Arctic Ocean MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, there was an unprecedented opportunity to observe a ROS event using in situ active and passive microwave instruments similar to those deployed on satellite platforms. During liquid water accumulation in the snowpack from rain and increased melt, there was a 4-fold decrease in radar energy returned at Ku- and Ka-bands. After the snowpack refroze and ice layers formed, this decrease was followed by a 6-fold increase in returned energy. Besides altering the radar backscatter, analysis of the returned waveforms shows the waveform shape changed in response to rain and refreezing. Microwave emissivity at 19 and 89 GHz increased with increasing liquid water content and decreased as the snowpack refroze, yet subsequent ice layers altered the polarization difference. Corresponding analysis of the CryoSat-2 waveform shape and backscatter as well as AMSR2 brightness temperatures further shows that the rain and refreeze were significant enough to impact satellite returns. Our analysis provides the first detailed in situ analysis of the impacts of ROS and subsequent refreezing on both active and passive microwave observations, providing important baseline knowledge for detecting ROS over sea ice and assessing their impacts on satellite-derived sea ice variables.

Given growing interest in extreme high-latitude weather events, we use records from nine meteorological stations and atmospheric reanalysis data to examine extreme daily precipitation events (leading, 99th and 95th percentile) over Arctic Canada. Leading events span 90 mm at Cape Dyer, along the southeast coast of Baffin Island, to 26 mm at Sachs Harbour, on the southwest coast of Banks Island. The 95th percentiles range from 20 to 30% of leading event sizes. Extreme events are most common on or near the month of climatological peak precipitation. Contrasting with Eurasian continental sites having a July precipitation peak corresponding to the seasonal peak in precipitable water, seasonal cycles in precipitation and the frequency of extremes over Arctic Canada are more varied, reflecting marine influences. At Cape Dyer and Clyde River, mean precipitation and the frequency of extremes peak in October when the atmosphere is quickly cooling, promoting strong evaporation from Baffin Bay. At all stations, leading events involved snowfall and strong winds and were associated with cyclone passages (mostly of relatively strong storms). They also involved strong vapour fluxes, sometimes associated with atmospheric rivers or their remnants. The most unusual sequence of events identified here occurred at Clyde River, where the three largest recorded precipitation events occurred in April of 1977. Obtaining first-hand accounts of this series of events has proven elusive. Identified links between extreme events and atmospheric rivers demonstrates the need to better understand how the characteristics of such features will change in the future.

Abstract. Arctic rain-on-snow (ROS) deposits liquid water onto existing snowpacks. Upon refreezing, this can form icy crusts at the surface or within the snowpack. By altering radar backscatter and microwave emissivity, ROS over sea ice can influence the accuracy of sea ice variables retrieved from satellite radar altimetry, scatterometers, and passive microwave radiometers. During the Arctic Ocean MOSAiC Expedition, there was an unprecedented opportunity to observe a ROS event using in situ active and passive microwave instruments similar to those deployed on satellite platforms. During liquid water accumulation in the snowpack, there was a four-fold decrease in radar energy returned at Ku- and Ka-bands. After the snowpack refroze and ice layers formed, this decrease was followed by a six-fold increase in returned energy. Besides altering the radar backscatter, analysis of the returned waveforms shows the waveform shape changed in response to rain and refreezing. Microwave emissivity at 19 and 89 GHz increased with increasing liquid water content and decreased as the snowpack refroze, yet subsequent ice layers altered the polarization difference. Corresponding analysis of CryoSat-2 waveform shape and backscatter as well as AMSR2 brightness temperatures further shows the rain/refreeze was significant enough to impact satellite returns. Our analysis provides the first detailed in situ analysis of the impacts of ROS and subsequent refreezing on both active and passive microwave observations, providing important baseline knowledge for detecting ROS over sea ice and assessing their impacts on satellite-derived sea ice variables.

Lagrangian detection and tracking algorithms are frequently used to study the development, distribution, and trends of extratropical cyclones. Past research shows that results from these algorithms are sensitive to both spatial and temporal resolution of the gridded input fields, with coarser resolutions typically underestimating cyclone frequency by failing to capture weak, small, and short-lived systems. The fifth-generation atmospheric reanalysis from the European Centre for Medium-Range Weather Forecasts (ERA5) offers finer resolution, and therefore more precise information regarding storm locations and development than previous global reanalyses. However, our sensitivity tests show that using ERA5 sea-level pressure fields at their finest possible resolution does not necessarily lead to better cyclone detection and tracking. If a common number of nearest neighbors is used when detecting minima in sea-level pressure (like past studies), finer spatial resolution leads to noisier fields that unrealistically break up multi-center cyclones. Using a common search distance instead (with more neighbors at finer resolution) resolves the issue without smoothing inputs. Doing this also makes cyclone frequency, lifespan, and average depth insensitive to refining spatial resolution beyond 100 km. Results using 6-h and 3-h temporal resolutions have only minor differences, but using 1-h temporal resolution with a maximum allowed propagation speed of 150 km h-1 leads to unrealistic track splitting. This can be counteracted by increasing the maximum propagation speed, but modest sensitivity to temporal resolution persists for several cyclone characteristics. Therefore, we recommend caution if applying existing algorithms to temporal resolutions finer than 3-h and careful evaluation of algorithm settings.

We utilize statistically modeled ocean heat transports through the Bering Strait along with additional predictors to create skillful predictions of sea ice retreat and advance dates in the Chukchi Sea. Interannual variability of June and September oceanic heat transports through the strait can be captured using modeled Ekman transports, surface winds, and sea surface temperatures. At one‐month leads, our models can explain 41% and 79% of sea ice retreat and advance date variance with root mean squared errors (RMSEs) of 10.2 and 12.8 days respectively. At 4‐month leads, our models can respectively capture 37% and 73% of sea ice retreat and advance date variance with RMSEs of 8.5 and 14.6 days. These findings offer a path toward operational forecasts of sea ice retreat and advance dates in the Chukchi Sea in the absence of direct, readily available observations of heat transports in the strait.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).This article is licensed under a Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0/).Corresponding author: Michael Steele, mas@apl.washington.edu

Description A cold-weather enthusiast confronts connections between the cryosphere and human culture A cold-weather enthusiast confronts connections between the cryosphere and human culture

When rain falls on an existing cover of snow, followed by low temperatures, or falls as freezing rain, it can leave a hard crust. These Arctic rain on snow (ROS) events can profoundly influence the environment and in turn, human livelihoods. Impacts can be immediate (e.g. on human travel, herding, or harvesting) or evolve or accumulate, leading to massive starvation-induced die-offs of reindeer, caribou, and musk oxen, for example. We provide here a review and synthesis of Arctic ROS events and their impacts, addressing human-environment relationships, meteorological conditions associated with ROS events, and challenges in their detection. From our assessment of the state of the science, we conclude that while (a) systematic detection of ROS events, their intensity, and trends across the Arctic region can be approached by combining data from satellite remote sensing, atmospheric reanalyses, and meteorological station records; (b) obtaining knowledge and information most germane to impacts, such as the thickness of ice layers, how ice layers form within a snowpack, and antecedent conditions that can amplify impacts, necessitates collaboration and knowledge co-production with community members and indigenous knowledge-holders.