Seasonal cycles of snow algal blooms intensify surface melting on Antarctic ice shelves by Dong Liang, Lu Zhang, Qing Cheng, Qi Zhu, Yiming Liu, Barjeece Bashir, Weidong Kong, Lingyi Kong

“…The study also provides a workflow for snow algae and snowmelt analysis at high resolution over large areas, contributing to a deeper understanding of snowmelt and global sea-level rise.…”
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The Impact of Snow Cover on River Discharge Simulation: Insights from the Barandozchay River Basin by Haleh Hashemi, Hossein Rezaie, Keivan Khalili, Amin Amini

“…This study presents a comprehensive analysis aimed at predicting the discharge of the Barandozchay River using machine learning algorithms and meteorological data from both satellite and ground sources over the period from 2002 to 2022. The research highlights the significance of incorporating snow cover data in enhancing predictive accuracy, particularly during the spring and summer seasons. …”
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Quantifying cross-country ski–snow friction using real-time kinematic positioning by Kalle Kalliorinne, Joakim Sandberg, Gustav Hindér, Hans-Christer Holmberg, Matej Supej, Roland Larsson, Andreas Almqvist

“…Over the years, researchers have found many ways of quantifying ski–snow friction, but there are only a few methods that consider the glide of real-sized skis under natural conditions during both accelerating and decelerating movements. …”
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Automated Snow Avalanche Monitoring and Alert System Using Distributed Acoustic Sensing in Norway by Antoine Turquet, Andreas Wuestefeld, Guro K. Svendsen, Finn Kåre Nyhammer, Espen Lauvlund Nilsen, Andreas Per-Ola Persson, Vetle Refsum

“…The automated alert system identifies avalanches affecting the road and estimates accumulated snow. The system provides continuous, real-time monitoring with competitive sensitivity and accuracy over large areas (up to 170 km) and for multiple sites on parallel. …”
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Tracking the Ghosts of the Himalayas: Snow Leopard Conservation Insights From Satellite Collar Data by Pratistha Shrestha, Dayaram Pandey, Pemba Sherpa, Prakash Shah, Dipesh Kumar Sharma

“…Home ranges, estimated over a 5–21 month tracking period, were larger than those observed in previously studied snow leopards and included crossings of international boundaries from Nepal into China and India. …”
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A Spatially‐Distributed Machine Learning Approach for Fractional Snow Covered Area Estimation by Shalini Mahanthege, William Kleiber, Karl Rittger, Balaji Rajagopalan, Mary J. Brodzik, Edward Bair

“…Spatial estimates of fractional snow covered area (fSCA) at 30m are available every 16 days from the series of multispectral scanning instruments on Landsat platforms. …”
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Automated snow cover detection on mountain glaciers using spaceborne imagery and machine learning by R. Aberle, E. Enderlin, S. O'Neel, C. Florentine, L. Sass, A. Dickson, H.-P. Marshall, A. Flores

“…<p>Tracking the extent of seasonal snow on glaciers over time is critical for assessing glacier vulnerability and the response of glacierized watersheds to climate change. …”
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Calculating of snow cover characteristics on a plain territory using the model SPONSOR and data of reanalyses (by the example of Moscow region) by D. V. Turkov, V. S. Sokratov

“…The above characteristics of the snow cover on the test area of the Moscow region were calculated using this method over the period 1979–1996. …”
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Snow depth estimation on leadless landfast ice using Cryo2Ice satellite observations by M. Saha, J. Stroeve, J. Stroeve, D. Isleifson, J. Yackel, V. Nandan, V. Nandan, J. C. Landy, H. M. Lam

“…While previous studies have combined CryoSat-2- and ICESat-2-derived freeboards to estimate snow depth over Arctic sea ice, these approaches require leads within the ice pack to estimate the freeboard heights above the sea surface. …”
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Improving Knowledge about Snow by Crossing Qualitative and Quantitative Data from the Everest Region (Nepal) by Ornella Puschiasis, Marie Savéan, Pierre Chevallier, Joëlle Smadja, Olivia Aubriot, François Delclaux

“…In the Nepalese region of Mount Everest, snow data is fragmentary and unreliable, as in many mountainous regions of the world. …”
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Spatiotemporal Patterns of Intermittent Snow Cover From PlanetScope Imagery Using Deep Learning by Zhaocheng Wang, Jaya Venkatesh Jaya Baskar, Maneesh Sarma Sistla Naga Sai, Bohumil Svoma, Enrique R. Vivoni

“…Abstract Monitoring snow cover in regions with intermittent dynamics is a significant challenge due to the rapid changes occurring in snow accumulation and ablation over complex terrain. …”
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30-years (1991-2021) Snow Water Equivalent Dataset in the Po River District, Italy by Matteo Dall’Amico, Stefano Tasin, Federico Di Paolo, Marco Brian, Paolo Leoni, Francesco Tornatore, Giuseppe Formetta, John Mohd Wani, Riccardo Rigon, Gaia Roati

“…Additionally, satellite snow cover maps have been compared with simulated snow depth maps, as a function of elevation and aspect. 2D Validation shows accurate values over time and space, expressed in terms of snowline along the cardinal directions.…”
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Insoluble fractions of aerosols and heavy metals in fresh snow in the North-West of the Kola Peninsula in 2018 by M. V. Mityaev, M. V. Gerasimova, I. V. Ryzhik, T. G. Ishkulova

“…The average concentration of solid aerosol particles in freshly fallen snow is 4.04±0.24 mg/l (n = 47). Over the winter period of 2018 (120 days), about 1.85-2.37 thousand tons of aerosol substance precipitated on the underlying surface of the area under investigation. …”
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Estimation of snow load and avalanche hazard assessment in Southeastern Afghanistan through remote sensing techniques by Nazir Khan Mohammadi, Mohammad Gul Arabzai, Zikui Wang

“…The Snow Avalanche Frequency Estimation (SAFE) model, which employs Landsat satellite data, to emphasize remote sensing’s role in assessing climatic has successfully mapped zones susceptible to avalanches over a span of 32 years. …”
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Using Commercial Satellite Imagery to Reconstruct 3 m and Daily Spring Snow Water Equivalent by Justin M. Pflug, Kehan Yang, Nicoleta Cristea, Emma T. Boudreau, Carrie M. Vuyovich, Sujay V. Kumar

“…SWE reconstruction biases were then improved to within 0.04 m, on average, by calibrating snowmelt rates to track the spring temporal evolution of fractional snow cover observed by PlanetScope, including fractional snow cover over the full modeling domain, and across domain subsections where snowmelt rates may differ. …”
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Evaluation and Mapping of Snow Characteristics Using Remote Sensing Data in Astore River Basin, Pakistan by Ihsan Ullah Khan, Mudassar Iqbal, Zeshan Ali, Abu Bakar Arshed, Mo Wang, Rana Muhammad Adnan

“…The snowmelt runoff generated from high-altitude areas of the UIB provides inflow into the Indus river system that boosts the water supply. Snow accumulation during the winter period in the highlands in the watershed(s) becomes a source of water inflow during the snow-melting period, which is described according to characteristics like snow depth, snow density, and snow water equivalent. …”
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Estimates of recent changes in snow storage in the river Northern Dvina basin from observations and modeling by V. V. Popova, D. V. Turkov, O. N. Nasonova

“…The variability of snow accumulation in the Northern Dvina River basin at the end of March 1980-2016 was studied using data on the snow water equivalent of (SWE) obtained from archives of the Russian Institute of HydroMeteorological Information-World Data Center (RIHMI-WCD) as well as calculated by models of the local heat and moisture exchange SWAP and SPONSOR using the WATCH reanalysis (WFDEI) as input data. …”
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Holocene hydrological evolution of subglacial Lake Snow Eagle, East Antarctica, implied by englacial radiostratigraphy by Shuai Yan, Michelle R. Koutnik, Donald D. Blankenship, Jamin S. Greenbaum, Duncan A. Young, Jason L. Roberts, Tas van Ommen, Bo Sun, Martin J. Siegert

“…A major subglacial lake, Lake Snow Eagle (LSE), was identified in East Antarctica by airborne geophysical surveys. …”
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Visual Snow Syndrome is unstable: A longitudinal investigation of VSS symptoms in a Naïve population by Amy Claire Thompson, Patrick T. Goodbourn, Jason D. Forte

“…However, the impact of perceptual experiences was low and did not change over time, rank ICC = 0.71, 95% CI [0.59, 0.82]. …”
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Avalanche feeding of the Djankuat Glacier by V. V. Popovnin, T. V. Pylayeva

“…A case study was realized for 1998/99 balance year when accumulation value was the closest to its long-term mean over the 46-year-long monitoring period. Snow avalanche feeding turned out to be only 2.8 per cent of total accumulation that is about an order of magnitude smaller than assumed hitherto.…”
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