Automated observation of physical snowpack properties in Ny-Ålesund

• Published in: Frontiers in Earth Science
• Main Authors: Scoto, Federico, Pappaccogli, Gianluca, Mazzola, Mauro, Donateo, Antonio, Larose, Catherine, Salzano, Roberto, Monzali, Matteo, de Blasi, Fabrizio, Gallet, Jean-Charles, Decesari, Stefano, Spolaor, Andrea
• Other Authors: CNR Institute of Atmospheric Sciences and Climate (ISAC), National Research Council of Italy, Institute of Polar Sciences Venezia-Mestre (CNR-ISP), Ampère, Département Bioingénierie (BioIng), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institute of Atmospheric Pollution Research (IIA), Alma Mater Studiorum Università di Bologna = University of Bologna (UNIBO), Norwegian Polar Institute
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2023
• Subjects: snow physical properties arctic svalbard automated nivometric station; snow; physical properties; arctic; svalbard; automated nivometric station; [SDE]Environmental Sciences; Arctic; Svalbard; Ny-Ålesund; Svalbard Archipelago; Ny Ålesund; permafrost; Spitzbergen; Tundra
• Online Access: https://hal.science/hal-04291333; https://hal.science/hal-04291333/document; https://hal.science/hal-04291333/file/feart-11-1123981.pdf; https://doi.org/10.3389/feart.2023.1123981

International audience The snow season in the Svalbard archipelago generally lasts 6–10 months a year and significantly impacts the regional climate, glaciers mass balance, permafrost thermal regime and ecology. Due to the lack of long-term continuous snowpack physical data, it is still challenging for the numerical snow physics models to simulate multi-layer snowpack evolution, especially for remote Arctic areas. To fill this gap, in November 2020, an automated nivometric station (ANS) was installed ∼1 km Southwest from the settlement of Ny-Ålesund (Spitzbergen, Svalbard), in a flat area over the lowland tundra. It automatically provides continuous snow data, including NIR images of the fractional snow-cover area (fSCA), snow depth (SD), internal snow temperature and liquid water content (LWC) profiles at different depths with a 10 min time resolution. Here we present the first-year record of automatic snow preliminary measurements collected between November 2020 and July 2021 together with weekly manual observations for comparison. The snow season at the ANS site lasted for 225 days with an annual net accumulation of 117 cm (392 mm of water equivalent). The LWC in the snowpack was generally low (<4%) during wintertime, nevertheless, we observed three snow-melting events between November and February 2021 and one in June 2021, connected with positive temperature and rain on snow events (ROS). In view of the foreseen future developments, the ANS is the first automated, comprehensive snowpack monitoring system in Ny-Ålesund measuring key essential climate variables needed to understand the seasonal evolution of the snow cover on land.