Sensitivity of the MAR regional climate model snowpack to the parameterization of the assimilation of satellite-derived wet-snow masks on the Antarctic Peninsula

Both regional climate models (RCMs) and remote sensing (RS) data are essential tools in understanding the response of polar regions to climate change. RCMs can simulate how certain climate variables, such as surface melt, runoff and snowfall, are likely to change in response to different climate sce...

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Published in:The Cryosphere
Main Authors: Dethinne, Thomas, Glaude, Quentin, Picard, Ghislain, Kittel, Christoph, Alexander, Patrick, Orban, Anne, Fettweis, Xavier
Format: Text
Language:English
Published: 2023
Subjects:
Online Access:https://doi.org/10.5194/tc-17-4267-2023
https://tc.copernicus.org/articles/17/4267/2023/
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spelling ftcopernicus:oai:publications.copernicus.org:tc108100 2023-11-05T03:36:56+01:00 Sensitivity of the MAR regional climate model snowpack to the parameterization of the assimilation of satellite-derived wet-snow masks on the Antarctic Peninsula Dethinne, Thomas Glaude, Quentin Picard, Ghislain Kittel, Christoph Alexander, Patrick Orban, Anne Fettweis, Xavier 2023-10-06 application/pdf https://doi.org/10.5194/tc-17-4267-2023 https://tc.copernicus.org/articles/17/4267/2023/ eng eng doi:10.5194/tc-17-4267-2023 https://tc.copernicus.org/articles/17/4267/2023/ eISSN: 1994-0424 Text 2023 ftcopernicus https://doi.org/10.5194/tc-17-4267-2023 2023-10-09T16:24:15Z Both regional climate models (RCMs) and remote sensing (RS) data are essential tools in understanding the response of polar regions to climate change. RCMs can simulate how certain climate variables, such as surface melt, runoff and snowfall, are likely to change in response to different climate scenarios but are subject to biases and errors. RS data can assist in reducing and quantifying model uncertainties by providing indirect observations of the modeled variables on the present climate. In this work, we improve on an existing scheme to assimilate RS wet snow occurrence data with the “Modèle Atmosphérique Régional” (MAR) RCM and investigate the sensitivity of the RCM to the parameters of the scheme. The assimilation is performed by nudging the MAR snowpack temperature to match the presence of liquid water observed by satellites. The sensitivity of the assimilation method is tested by modifying parameters such as the depth to which the MAR snowpack is warmed or cooled, the quantity of water required to qualify a MAR pixel as “wet” (0.1 % or 0.2 % of the snowpack mass being water), and assimilating different RS datasets. Data assimilation is carried out on the Antarctic Peninsula for the 2019–2021 period. The results show an increase in meltwater production ( +66.7 % on average, or +95 Gt ), along with a small decrease in surface mass balance (SMB) ( −4.5 % on average, or −20 Gt ) for the 2019–2020 melt season after assimilation. The model is sensitive to the tested parameters, albeit with varying orders of magnitude. The prescribed warming depth has a larger impact on the resulting surface melt production than the liquid water content (LWC) threshold due to strong refreezing occurring within the top layers of the snowpack. The values tested for the LWC threshold are lower than the LWC for typical melt days (approximately 1.2 %) and impact results mainly at the beginning and end of the melting period. The assimilation method will allow for the estimation of uncertainty in MAR meltwater production and will ... Text Antarc* Antarctic Antarctic Peninsula Copernicus Publications: E-Journals The Cryosphere 17 10 4267 4288
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description Both regional climate models (RCMs) and remote sensing (RS) data are essential tools in understanding the response of polar regions to climate change. RCMs can simulate how certain climate variables, such as surface melt, runoff and snowfall, are likely to change in response to different climate scenarios but are subject to biases and errors. RS data can assist in reducing and quantifying model uncertainties by providing indirect observations of the modeled variables on the present climate. In this work, we improve on an existing scheme to assimilate RS wet snow occurrence data with the “Modèle Atmosphérique Régional” (MAR) RCM and investigate the sensitivity of the RCM to the parameters of the scheme. The assimilation is performed by nudging the MAR snowpack temperature to match the presence of liquid water observed by satellites. The sensitivity of the assimilation method is tested by modifying parameters such as the depth to which the MAR snowpack is warmed or cooled, the quantity of water required to qualify a MAR pixel as “wet” (0.1 % or 0.2 % of the snowpack mass being water), and assimilating different RS datasets. Data assimilation is carried out on the Antarctic Peninsula for the 2019–2021 period. The results show an increase in meltwater production ( +66.7 % on average, or +95 Gt ), along with a small decrease in surface mass balance (SMB) ( −4.5 % on average, or −20 Gt ) for the 2019–2020 melt season after assimilation. The model is sensitive to the tested parameters, albeit with varying orders of magnitude. The prescribed warming depth has a larger impact on the resulting surface melt production than the liquid water content (LWC) threshold due to strong refreezing occurring within the top layers of the snowpack. The values tested for the LWC threshold are lower than the LWC for typical melt days (approximately 1.2 %) and impact results mainly at the beginning and end of the melting period. The assimilation method will allow for the estimation of uncertainty in MAR meltwater production and will ...
format Text
author Dethinne, Thomas
Glaude, Quentin
Picard, Ghislain
Kittel, Christoph
Alexander, Patrick
Orban, Anne
Fettweis, Xavier
spellingShingle Dethinne, Thomas
Glaude, Quentin
Picard, Ghislain
Kittel, Christoph
Alexander, Patrick
Orban, Anne
Fettweis, Xavier
Sensitivity of the MAR regional climate model snowpack to the parameterization of the assimilation of satellite-derived wet-snow masks on the Antarctic Peninsula
author_facet Dethinne, Thomas
Glaude, Quentin
Picard, Ghislain
Kittel, Christoph
Alexander, Patrick
Orban, Anne
Fettweis, Xavier
author_sort Dethinne, Thomas
title Sensitivity of the MAR regional climate model snowpack to the parameterization of the assimilation of satellite-derived wet-snow masks on the Antarctic Peninsula
title_short Sensitivity of the MAR regional climate model snowpack to the parameterization of the assimilation of satellite-derived wet-snow masks on the Antarctic Peninsula
title_full Sensitivity of the MAR regional climate model snowpack to the parameterization of the assimilation of satellite-derived wet-snow masks on the Antarctic Peninsula
title_fullStr Sensitivity of the MAR regional climate model snowpack to the parameterization of the assimilation of satellite-derived wet-snow masks on the Antarctic Peninsula
title_full_unstemmed Sensitivity of the MAR regional climate model snowpack to the parameterization of the assimilation of satellite-derived wet-snow masks on the Antarctic Peninsula
title_sort sensitivity of the mar regional climate model snowpack to the parameterization of the assimilation of satellite-derived wet-snow masks on the antarctic peninsula
publishDate 2023
url https://doi.org/10.5194/tc-17-4267-2023
https://tc.copernicus.org/articles/17/4267/2023/
genre Antarc*
Antarctic
Antarctic Peninsula
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Antarctic
Antarctic Peninsula
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op_relation doi:10.5194/tc-17-4267-2023
https://tc.copernicus.org/articles/17/4267/2023/
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container_title The Cryosphere
container_volume 17
container_issue 10
container_start_page 4267
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