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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Online Access: | https://doi.org/10.5194/tc-16-2373-2022 https://tc.copernicus.org/articles/16/2373/2022/ |
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ftcopernicus:oai:publications.copernicus.org:tc94258 2023-05-15T15:18:30+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, Amélie 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 2022-06-17 application/pdf https://doi.org/10.5194/tc-16-2373-2022 https://tc.copernicus.org/articles/16/2373/2022/ eng eng doi:10.5194/tc-16-2373-2022 https://tc.copernicus.org/articles/16/2373/2022/ eISSN: 1994-0424 Text 2022 ftcopernicus https://doi.org/10.5194/tc-16-2373-2022 2022-06-20T16:22:42Z 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 ERA5 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. ERA5 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 ERA5. 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 ... Text Arctic Sea ice Copernicus Publications: E-Journals Arctic The Cryosphere 16 6 2373 2402 |
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Open Polar |
collection |
Copernicus Publications: E-Journals |
op_collection_id |
ftcopernicus |
language |
English |
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 ERA5 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. ERA5 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 ERA5. 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 ... |
format |
Text |
author |
Wagner, David N. Shupe, Matthew D. Cox, Christopher Persson, Ola G. Uttal, Taneil Frey, Markus M. Kirchgaessner, Amélie 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, Amélie 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, Amélie 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 |
publishDate |
2022 |
url |
https://doi.org/10.5194/tc-16-2373-2022 https://tc.copernicus.org/articles/16/2373/2022/ |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
eISSN: 1994-0424 |
op_relation |
doi:10.5194/tc-16-2373-2022 https://tc.copernicus.org/articles/16/2373/2022/ |
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 |
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1766348699166834688 |