| Autor: |
Federico Scoto, Gianluca Pappaccogli, Mauro Mazzola, Antonio Donateo, Roberto Salzano, Matteo Monzali, Fabrizio de Blasi, Catherine Larose, Jean-Charles Gallet, Stefano Decesari, Andrea Spolaor |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Frontiers in Earth Science, Vol 11 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2296-6463 |
| DOI: |
10.3389/feart.2023.1123981 |
| Popis: |
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 ( |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
