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1. Trends in Northern Hemispheric Snow Presence

   https://doi.org/10.1175/JHM-D-22-0182.1  

   Jia, Yisu; Lund, Robert; Kong, Jiajie; Dyer, Jamie; Woody, Jonathan; Marron, J. S. (June 2023, Journal of Hydrometeorology)

   Abstract This paper develops a mathematical model and statistical methods to quantify trends in presence/absence observations of snow cover (not depths) and applies these in an analysis of Northern Hemispheric observations extracted from satellite flyovers during 1967–2021. A two-state Markov chain model with periodic dynamics is introduced to analyze changes in the data in a cell by cell fashion. Trends, converted to the number of weeks of snow cover lost/gained per century, are estimated for each study cell. Uncertainty margins for these trends are developed from the model and used to assess the significance of the trend estimates. Cells with questionable data quality are explicitly identified. Among trustworthy cells, snow presence is seen to be declining in almost twice as many cells as it is advancing. While Arctic and southern latitude snow presence is found to be rapidly receding, other locations, such as eastern Canada, are experiencing advancing snow cover. Significance StatementThis project quantifies how the Northern Hemisphere’s snow cover has recently changed. Snow cover plays a critical role in the global energy balance due to its high albedo and insulating characteristics and is therefore a prominent indicator of climate change. On a regional scale, the spatial consistency of snow cover influences surface temperatures via variations in absorbed solar radiation, while continental-scale snow cover acts to maintain thermal stability in the Arctic and subarctic regions, leading to spatial and temporal impacts on global circulation patterns. Changing snow presence in Arctic regions could influence large-scale releases of carbon and methane gas. Given the importance of snow cover, understanding its trends enhances our understanding of climate change. 

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2. Future Changes of Snow in Alaska and the Arctic under Stabilized Global Warming Scenarios

   https://doi.org/10.3390/atmos13040541  

   Bigalke, Siiri; Walsh, John E. (April 2022, Atmosphere)

   Manifestations of global warming in the Arctic include amplifications of temperature increases and a general increase in precipitation. Although topography complicates the pattern of these changes in regions such as Alaska, the amplified warming and general increase in precipitation are already apparent in observational data. Changes in snow cover are complicated by the opposing effects of warming and increased precipitation. In this study, high-resolution (0.25°) outputs from simulations by the Community Atmosphere Model, version 5, were analyzed for changes in snow under stabilized global warming scenarios of 1.5 °C, 2.0 °C and 3.0 °C. Future changes in snowfall are characterized by a north–south gradient over Alaska and an east–west gradient over Eurasia. Increased snowfall is projected for northern Alaska, northern Canada and Siberia, while milder regions such as southern Alaska and Europe receive less snow in a warmer climate. Overall, the results indicate that the majority of the land area poleward of 55°N will experience a reduction in snow. The approximate threshold of global warming for a statistically significant increase in temperature over 50% of the pan-Arctic land area is 1.5 °C. The corresponding threshold for precipitation is approximately 2.0 °C. The global warming threshold for the loss of high-elevation snow in Alaska is approximately 2.0 °C. The results imply that limiting global warming to the Paris Agreement target is necessary to prevent significant changes in winter climates in Alaska and the Arctic. 

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3. Unpiloted Aerial Vehicle Retrieval of Snow Depth Over Freshwater Lake Ice Using Structure From Motion

   https://doi.org/10.3389/frsen.2021.675846  

   Gunn, Grant E.; Jones, Benjamin M.; Rangel, Rodrigo C. (July 2021, Frontiers in Remote Sensing)

   null (Ed.)

   The presence and thickness of snow overlying lake ice affects both the timing of melt and ice-free conditions, can contribute to overall ice thickness through its insulative capacity, and fosters the development of variable ice types. The use of UAVs to retrieve snow depths with high spatial resolution is necessary for the next generation of ultra-fine hydrological models, as the direct contribution of water from snow on lake ice is unknown. Such information is critical to the understanding of the physical processes of snow redistribution and capture in catchments on small lakes in the Arctic, which has been historically estimated from its relationship to terrestrial snowpack properties. In this study, we use a quad-copter UAV and SfM principles to retrieve and map snow depth at the winter maximum at high resolution over a the freshwater West Twin Lake on the Arctic Coastal Plain of northern Alaska. The accuracy of the snow depth retrievals is assessed using in-situ observations ( n = 1,044), applying corrections to account for the freeboard of floating ice. The average snow depth from in-situ observations was used calculate a correction factor based on the freeboard of the ice to retrieve snow depth from UAV acquisitions (RMSE = 0.06 and 0.07 m for two transects on the lake. The retrieved snow depth map exhibits drift structures that have height deviations with a root mean square (RMS) of 0.08 m (correlation length = 13.8 m) for a transect on the west side of the lake, and an RMS of 0.07 m (correlation length = 18.7 m) on the east. Snow drifts present on the lake also correspond to previous investigations regarding the variability of snow on lakes, with a periodicity (separation) of 20 and 16 m for the west and east side of the lake, respectively. This study represents the first retrieval of snow depth on a frozen lake surface from a UAV using photogrammetry, and promotes the potential for high-resolution snow depth retrieval on small ponds and lakes that comprise a significant portion of landcover in Arctic environments. 

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4. Prediction of Northern Hemisphere Regional Sea Ice Extent and Snow Depth Using Stratospheric Ozone Information

   https://doi.org/10.1029/2019JD031770  

   Stone, Kane A.; Solomon, Susan; Kinnison, Douglas E. (November 2020, Journal of Geophysical Research: Atmospheres)

   Abstract The forecast potential of springtime ozone on April surface temperatures at particular locations in the Northern Hemisphere has been previously reported. Evidence suggests that early springtime Arctic stratospheric ozone acts as a proxy for extreme events in the winter polar vortex. Here, using a state‐of‐the‐art chemistry‐climate model, reanalysis and observations, we extend the forecast potential of ozone on surface temperatures to aspects of the Northern Hemisphere cryosphere. Sea ice fraction and sea ice extent differences between years of March high and low Arctic stratospheric ozone extremes show excellent agreement between an ensemble of chemistry‐climate model simulations and observations, with differences occurring not just in April but extending through to the following winter season in some locations. Large snow depth differences are also obtained in regional locations in Russia and along the southeast coast of Alaska. These differences remain elevated until early summer, when snow cover diminishes. Using a conditional empirical model in a leave‐three‐out cross validation method, March total column ozone is able to accurately predict the sign of the observed sea ice extent and snow depth anomalies over 70% of the time during an ozone extreme year, especially in the region of the Bering strait and the Greenland Sea, which could be useful for shipping routes and for testing climate models. 

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5. Sublimation measurements of tundra and taiga snowpack in Alaska

   https://doi.org/10.5194/tc-19-1739-2025  

   Stockert, Kelsey A; Euskirchen, Eugénie S; Stuefer, Svetlana L (May 2025, The Cryosphere)

   na (Ed.)

   Abstract. Snow sublimation plays a fundamental role in the winter water balance. To date, few studies have quantified sublimation in tundra and boreal forest snow by direct measurements. Continuous latent heat data collected with eddy covariance (EC) measurements from 2010–2021 were used to calculate snow sublimation at six locations in northern Alaska: three Arctic tundra sites at distinct topographical and vegetation communities in the Imnavait Creek watershed on the North Slope underlain by continuous permafrost, and three lowland boreal forest/taiga sites in discontinuous permafrost in interior Alaska near Fairbanks. Mean surface sublimation rates range from 0.08–0.15 mm d−1 and 15–27 mm yr−1 at the six sites, representing, on average, 21 % of the measured solid precipitation and 8 %–16 % of the cumulative annual water vapor flux to the atmosphere (evaporation plus sublimation). The mean daily sublimation rates of the lowland boreal forest sites are higher than those of the tundra sites, but the longer snow cover period of the tundra sites leads to greater mean annual sublimation rates. We examined the potential controls, drivers, and trends of the sublimation rates by using meteorological data collected in conjunction with EC measurements. This research improves our understanding of how site conditions affect sublimation rates and highlights the fact that sublimation is a substantial component of the winter hydrologic cycle. In addition, the study contributes to the sparse literature on tundra and boreal sublimation measurements, and the measured rates are comparable to sublimation estimates in other northern climates. 

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