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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Published in:Frontiers in Earth Science
Main Authors: Scoto, F, Pappaccogli, G, Mazzola, M, Donateo, A, Salzano, R, Monzali, M, de Blasi, F, Larose, C, Gallet, JC, Decesari, S, Spolaor, A
Other Authors: Gallet, Jc
Format: Article in Journal/Newspaper
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/10278/5025141
https://doi.org/10.3389/feart.2023.1123981
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record_format openpolar
spelling 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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