Automated observation of physical snowpack properties in Ny-Alesund
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...
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Online Access: | https://hdl.handle.net/10278/5025141 https://doi.org/10.3389/feart.2023.1123981 |
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ftuniveneziairis:oai:iris.unive.it:10278/5025141 2024-04-21T08:10:21+00:00 Automated observation of physical snowpack properties in Ny-Alesund Scoto, F Pappaccogli, G Mazzola, M Donateo, A Salzano, R Monzali, M de Blasi, F Larose, C Gallet, JC Decesari, S Spolaor, A Scoto, F Pappaccogli, G Mazzola, M Donateo, A Salzano, R Monzali, M de Blasi, F Larose, C Gallet, Jc Decesari, S Spolaor, A 2023 https://hdl.handle.net/10278/5025141 https://doi.org/10.3389/feart.2023.1123981 eng eng info:eu-repo/semantics/altIdentifier/wos/WOS:000970783600001 volume:11 journal:FRONTIERS IN EARTH SCIENCE https://hdl.handle.net/10278/5025141 doi:10.3389/feart.2023.1123981 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85153373580 snow physical propertie arctic svalbard automated nivometric station Settore GEO/04 - Geografia Fisica e Geomorfologia Settore FIS/06 - Fisica per il Sistema Terra e Il Mezzo Circumterrestre info:eu-repo/semantics/article 2023 ftuniveneziairis https://doi.org/10.3389/feart.2023.1123981 2024-03-28T01:22:06Z 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 similar to 1 km Southwest from the settlement of Ny-Alesund (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 differente 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-Alesund measuring key essential climate variables needed to understand the seasonal evolution of the snow cover on land. Article in Journal/Newspaper permafrost Spitzbergen Svalbard Tundra Università Ca’ Foscari Venezia: ARCA (Archivio Istituzionale della Ricerca) Frontiers in Earth Science 11 |
institution |
Open Polar |
collection |
Università Ca’ Foscari Venezia: ARCA (Archivio Istituzionale della Ricerca) |
op_collection_id |
ftuniveneziairis |
language |
English |
topic |
snow physical propertie arctic svalbard automated nivometric station Settore GEO/04 - Geografia Fisica e Geomorfologia Settore FIS/06 - Fisica per il Sistema Terra e Il Mezzo Circumterrestre |
spellingShingle |
snow physical propertie arctic svalbard automated nivometric station Settore GEO/04 - Geografia Fisica e Geomorfologia Settore FIS/06 - Fisica per il Sistema Terra e Il Mezzo Circumterrestre Scoto, F Pappaccogli, G Mazzola, M Donateo, A Salzano, R Monzali, M de Blasi, F Larose, C Gallet, JC Decesari, S Spolaor, A Automated observation of physical snowpack properties in Ny-Alesund |
topic_facet |
snow physical propertie arctic svalbard automated nivometric station Settore GEO/04 - Geografia Fisica e Geomorfologia Settore FIS/06 - Fisica per il Sistema Terra e Il Mezzo Circumterrestre |
description |
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 similar to 1 km Southwest from the settlement of Ny-Alesund (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 differente 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-Alesund measuring key essential climate variables needed to understand the seasonal evolution of the snow cover on land. |
author2 |
Scoto, F Pappaccogli, G Mazzola, M Donateo, A Salzano, R Monzali, M de Blasi, F Larose, C Gallet, Jc Decesari, S Spolaor, A |
format |
Article in Journal/Newspaper |
author |
Scoto, F Pappaccogli, G Mazzola, M Donateo, A Salzano, R Monzali, M de Blasi, F Larose, C Gallet, JC Decesari, S Spolaor, A |
author_facet |
Scoto, F Pappaccogli, G Mazzola, M Donateo, A Salzano, R Monzali, M de Blasi, F Larose, C Gallet, JC Decesari, S Spolaor, A |
author_sort |
Scoto, F |
title |
Automated observation of physical snowpack properties in Ny-Alesund |
title_short |
Automated observation of physical snowpack properties in Ny-Alesund |
title_full |
Automated observation of physical snowpack properties in Ny-Alesund |
title_fullStr |
Automated observation of physical snowpack properties in Ny-Alesund |
title_full_unstemmed |
Automated observation of physical snowpack properties in Ny-Alesund |
title_sort |
automated observation of physical snowpack properties in ny-alesund |
publishDate |
2023 |
url |
https://hdl.handle.net/10278/5025141 https://doi.org/10.3389/feart.2023.1123981 |
genre |
permafrost Spitzbergen Svalbard Tundra |
genre_facet |
permafrost Spitzbergen Svalbard Tundra |
op_relation |
info:eu-repo/semantics/altIdentifier/wos/WOS:000970783600001 volume:11 journal:FRONTIERS IN EARTH SCIENCE https://hdl.handle.net/10278/5025141 doi:10.3389/feart.2023.1123981 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85153373580 |
op_doi |
https://doi.org/10.3389/feart.2023.1123981 |
container_title |
Frontiers in Earth Science |
container_volume |
11 |
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1796951775993921536 |