Snowfall and snow accumulation during the MOSAiC winter and spring seasons
Data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition allowed us to investigate the temporal dynamics of snowfall, snow accumulation and erosion in great detail for almost the whole accumulation season (November 2019 to May 2020). We computed cumula...
Published in: | The Cryosphere |
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Gottingen, COPERNICUS GESELLSCHAFT MBH
2022
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Online Access: | https://doi.org/10.5194/tc-16-2373-2022 https://infoscience.epfl.ch/record/295377/files/tc-16-2373-2022.pdf http://infoscience.epfl.ch/record/295377 |
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ftinfoscience:oai:infoscience.epfl.ch:295377 2023-05-15T15:17:33+02:00 Snowfall and snow accumulation during the MOSAiC winter and spring seasons Wagner, David N. Shupe, Matthew D. Cox, Christopher Persson, Ola G. Uttal, Taneil Frey, Markus M. Kirchgaessner, Amelie Schneebeli, Martin Jaggi, Matthias Macfarlane, Amy R. Itkin, Polona Arndt, Stefanie Hendricks, Stefan Krampe, Daniela Nicolaus, Marcel Ricker, Robert Regnery, Julia Kolabutin, Nikolai Shimanshuck, Egor Oggier, Marc Raphael, Ian Stroeve, Julienne Lehning, Michael 2022-07-18T00:34:46Z https://doi.org/10.5194/tc-16-2373-2022 https://infoscience.epfl.ch/record/295377/files/tc-16-2373-2022.pdf http://infoscience.epfl.ch/record/295377 unknown Gottingen, COPERNICUS GESELLSCHAFT MBH isi:000812322400001 doi:10.5194/tc-16-2373-2022 https://infoscience.epfl.ch/record/295377/files/tc-16-2373-2022.pdf http://infoscience.epfl.ch/record/295377 http://infoscience.epfl.ch/record/295377 Text 2022 ftinfoscience https://doi.org/10.5194/tc-16-2373-2022 2023-02-13T23:10:54Z Data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition allowed us to investigate the temporal dynamics of snowfall, snow accumulation and erosion in great detail for almost the whole accumulation season (November 2019 to May 2020). We computed cumulative snow water equivalent (SWE) over the sea ice based on snow depth and density retrievals from a SnowMicroPen and approximately weekly measured snow depths along fixed transect paths. We used the derived SWE from the snow cover to compare with precipitation sensors installed during MOSAiC. The data were also compared with ERAS reanalysis snowfall rates for the drift track. We found an accumulated snow mass of 38 mm SWE between the end of October 2019 and end of April 2020. The initial SWE over first-year ice relative to second-year ice increased from 50 % to 90 % by end of the investigation period. Further, we found that the Vaisala Present Weather Detector 22, an optical precipitation sensor, and installed on a railing on the top deck of research vessel Polarstern, was least affected by blowing snow and showed good agreements with SWE retrievals along the transect. On the contrary, the OTT Pluvio 2 pluviometer and the OTT Parsivel 2 laser disdrometer were largely affected by wind and blowing snow, leading to too high measured precipitation rates. These are largely reduced when eliminating drifting snow periods in the comparison. ERAS reveals good timing of the snowfall events and good agreement with ground measurements with an overestimation tendency. Retrieved snowfall from the ship-based K-a-band ARM zenith radar shows good agreements with SWE of the snow cover and differences comparable to those of ERAS. Based on the results, we suggest the K-a-band radar-derived snowfall as an upper limit and the present weather detector on RV Polarstern as a lower limit of a cumulative snowfall range. Based on these findings, we suggest a cumulative snowfall of 72 to 107 mm and a precipitation mass loss of the snow cover due ... Text Arctic Sea ice EPFL Infoscience (Ecole Polytechnique Fédérale Lausanne) Arctic The Cryosphere 16 6 2373 2402 |
institution |
Open Polar |
collection |
EPFL Infoscience (Ecole Polytechnique Fédérale Lausanne) |
op_collection_id |
ftinfoscience |
language |
unknown |
description |
Data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition allowed us to investigate the temporal dynamics of snowfall, snow accumulation and erosion in great detail for almost the whole accumulation season (November 2019 to May 2020). We computed cumulative snow water equivalent (SWE) over the sea ice based on snow depth and density retrievals from a SnowMicroPen and approximately weekly measured snow depths along fixed transect paths. We used the derived SWE from the snow cover to compare with precipitation sensors installed during MOSAiC. The data were also compared with ERAS reanalysis snowfall rates for the drift track. We found an accumulated snow mass of 38 mm SWE between the end of October 2019 and end of April 2020. The initial SWE over first-year ice relative to second-year ice increased from 50 % to 90 % by end of the investigation period. Further, we found that the Vaisala Present Weather Detector 22, an optical precipitation sensor, and installed on a railing on the top deck of research vessel Polarstern, was least affected by blowing snow and showed good agreements with SWE retrievals along the transect. On the contrary, the OTT Pluvio 2 pluviometer and the OTT Parsivel 2 laser disdrometer were largely affected by wind and blowing snow, leading to too high measured precipitation rates. These are largely reduced when eliminating drifting snow periods in the comparison. ERAS reveals good timing of the snowfall events and good agreement with ground measurements with an overestimation tendency. Retrieved snowfall from the ship-based K-a-band ARM zenith radar shows good agreements with SWE of the snow cover and differences comparable to those of ERAS. Based on the results, we suggest the K-a-band radar-derived snowfall as an upper limit and the present weather detector on RV Polarstern as a lower limit of a cumulative snowfall range. Based on these findings, we suggest a cumulative snowfall of 72 to 107 mm and a precipitation mass loss of the snow cover due ... |
format |
Text |
author |
Wagner, David N. Shupe, Matthew D. Cox, Christopher Persson, Ola G. Uttal, Taneil Frey, Markus M. Kirchgaessner, Amelie Schneebeli, Martin Jaggi, Matthias Macfarlane, Amy R. Itkin, Polona Arndt, Stefanie Hendricks, Stefan Krampe, Daniela Nicolaus, Marcel Ricker, Robert Regnery, Julia Kolabutin, Nikolai Shimanshuck, Egor Oggier, Marc Raphael, Ian Stroeve, Julienne Lehning, Michael |
spellingShingle |
Wagner, David N. Shupe, Matthew D. Cox, Christopher Persson, Ola G. Uttal, Taneil Frey, Markus M. Kirchgaessner, Amelie Schneebeli, Martin Jaggi, Matthias Macfarlane, Amy R. Itkin, Polona Arndt, Stefanie Hendricks, Stefan Krampe, Daniela Nicolaus, Marcel Ricker, Robert Regnery, Julia Kolabutin, Nikolai Shimanshuck, Egor Oggier, Marc Raphael, Ian Stroeve, Julienne Lehning, Michael Snowfall and snow accumulation during the MOSAiC winter and spring seasons |
author_facet |
Wagner, David N. Shupe, Matthew D. Cox, Christopher Persson, Ola G. Uttal, Taneil Frey, Markus M. Kirchgaessner, Amelie Schneebeli, Martin Jaggi, Matthias Macfarlane, Amy R. Itkin, Polona Arndt, Stefanie Hendricks, Stefan Krampe, Daniela Nicolaus, Marcel Ricker, Robert Regnery, Julia Kolabutin, Nikolai Shimanshuck, Egor Oggier, Marc Raphael, Ian Stroeve, Julienne Lehning, Michael |
author_sort |
Wagner, David N. |
title |
Snowfall and snow accumulation during the MOSAiC winter and spring seasons |
title_short |
Snowfall and snow accumulation during the MOSAiC winter and spring seasons |
title_full |
Snowfall and snow accumulation during the MOSAiC winter and spring seasons |
title_fullStr |
Snowfall and snow accumulation during the MOSAiC winter and spring seasons |
title_full_unstemmed |
Snowfall and snow accumulation during the MOSAiC winter and spring seasons |
title_sort |
snowfall and snow accumulation during the mosaic winter and spring seasons |
publisher |
Gottingen, COPERNICUS GESELLSCHAFT MBH |
publishDate |
2022 |
url |
https://doi.org/10.5194/tc-16-2373-2022 https://infoscience.epfl.ch/record/295377/files/tc-16-2373-2022.pdf http://infoscience.epfl.ch/record/295377 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
http://infoscience.epfl.ch/record/295377 |
op_relation |
isi:000812322400001 doi:10.5194/tc-16-2373-2022 https://infoscience.epfl.ch/record/295377/files/tc-16-2373-2022.pdf http://infoscience.epfl.ch/record/295377 |
op_doi |
https://doi.org/10.5194/tc-16-2373-2022 |
container_title |
The Cryosphere |
container_volume |
16 |
container_issue |
6 |
container_start_page |
2373 |
op_container_end_page |
2402 |
_version_ |
1766347787441537024 |