A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR

The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise, and this contribution is projected to accelerate over the next decades. A crucial tool for studying the evolution of surface mass loss (e.g., surface mass balance, SMB) consists of regional climate models (RCMs), which...

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Published in:The Cryosphere
Main Authors: Tedesco, Marco, Colosio, Paolo, Fettweis, Xavier, Cervone, Guido
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2023
Subjects:
Online Access:https://doi.org/10.5194/tc-17-5061-2023
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spelling ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00070178 2023-12-31T10:07:24+01:00 A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR Tedesco, Marco Colosio, Paolo Fettweis, Xavier Cervone, Guido 2023-11 electronic https://doi.org/10.5194/tc-17-5061-2023 https://noa.gwlb.de/receive/cop_mods_00070178 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00068534/tc-17-5061-2023.pdf https://tc.copernicus.org/articles/17/5061/2023/tc-17-5061-2023.pdf eng eng Copernicus Publications The Cryosphere -- ˜Theœ Cryosphere -- http://www.bibliothek.uni-regensburg.de/ezeit/?2393169 -- http://www.the-cryosphere.net/ -- 1994-0424 https://doi.org/10.5194/tc-17-5061-2023 https://noa.gwlb.de/receive/cop_mods_00070178 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00068534/tc-17-5061-2023.pdf https://tc.copernicus.org/articles/17/5061/2023/tc-17-5061-2023.pdf https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess article Verlagsveröffentlichung article Text doc-type:article 2023 ftnonlinearchiv https://doi.org/10.5194/tc-17-5061-2023 2023-12-04T00:22:44Z The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise, and this contribution is projected to accelerate over the next decades. A crucial tool for studying the evolution of surface mass loss (e.g., surface mass balance, SMB) consists of regional climate models (RCMs), which can provide current estimates and future projections of sea level rise associated with such losses. However, one of the main limitations of RCMs is the relatively coarse horizontal spatial resolution at which outputs are currently generated. Here, we report results concerning the statistical downscaling of the SMB modeled by the Modèle Atmosphérique Régional (MAR) RCM from the original spatial resolution of 6 km to 100 m building on the relationship between elevation and mass losses in Greenland. To this goal, we developed a geospatial framework that allows the parallelization of the downscaling process, a crucial aspect to increase the computational efficiency of the algorithm. Using the results obtained in the case of the SMB, surface and air temperature are assessed through the comparison of the modeled outputs with in situ and satellite measurement. The downscaled products show a considerable improvement in the case of the downscaled product with respect to the original coarse output, with the coefficient of determination (R2) increasing from 0.868 for the original MAR output to 0.935 for the SMB downscaled product. Moreover, the value of the slope and intercept of the linear regression fitting modeled and measured SMB values shifts from 0.865 for the original MAR to 1.015 for the downscaled product in the case of the slope and from the value −235 mm w.e. yr−1 (original) to −57 mm w.e. yr−1 (downscaled) in the case of the intercept, considerably improving upon results previously published in the literature. Article in Journal/Newspaper Greenland Ice Sheet The Cryosphere Niedersächsisches Online-Archiv NOA The Cryosphere 17 12 5061 5074
institution Open Polar
collection Niedersächsisches Online-Archiv NOA
op_collection_id ftnonlinearchiv
language English
topic article
Verlagsveröffentlichung
spellingShingle article
Verlagsveröffentlichung
Tedesco, Marco
Colosio, Paolo
Fettweis, Xavier
Cervone, Guido
A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR
topic_facet article
Verlagsveröffentlichung
description The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise, and this contribution is projected to accelerate over the next decades. A crucial tool for studying the evolution of surface mass loss (e.g., surface mass balance, SMB) consists of regional climate models (RCMs), which can provide current estimates and future projections of sea level rise associated with such losses. However, one of the main limitations of RCMs is the relatively coarse horizontal spatial resolution at which outputs are currently generated. Here, we report results concerning the statistical downscaling of the SMB modeled by the Modèle Atmosphérique Régional (MAR) RCM from the original spatial resolution of 6 km to 100 m building on the relationship between elevation and mass losses in Greenland. To this goal, we developed a geospatial framework that allows the parallelization of the downscaling process, a crucial aspect to increase the computational efficiency of the algorithm. Using the results obtained in the case of the SMB, surface and air temperature are assessed through the comparison of the modeled outputs with in situ and satellite measurement. The downscaled products show a considerable improvement in the case of the downscaled product with respect to the original coarse output, with the coefficient of determination (R2) increasing from 0.868 for the original MAR output to 0.935 for the SMB downscaled product. Moreover, the value of the slope and intercept of the linear regression fitting modeled and measured SMB values shifts from 0.865 for the original MAR to 1.015 for the downscaled product in the case of the slope and from the value −235 mm w.e. yr−1 (original) to −57 mm w.e. yr−1 (downscaled) in the case of the intercept, considerably improving upon results previously published in the literature.
format Article in Journal/Newspaper
author Tedesco, Marco
Colosio, Paolo
Fettweis, Xavier
Cervone, Guido
author_facet Tedesco, Marco
Colosio, Paolo
Fettweis, Xavier
Cervone, Guido
author_sort Tedesco, Marco
title A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR
title_short A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR
title_full A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR
title_fullStr A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR
title_full_unstemmed A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR
title_sort computationally efficient statistically downscaled 100 m resolution greenland product from the regional climate model mar
publisher Copernicus Publications
publishDate 2023
url https://doi.org/10.5194/tc-17-5061-2023
https://noa.gwlb.de/receive/cop_mods_00070178
https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00068534/tc-17-5061-2023.pdf
https://tc.copernicus.org/articles/17/5061/2023/tc-17-5061-2023.pdf
genre Greenland
Ice Sheet
The Cryosphere
genre_facet Greenland
Ice Sheet
The Cryosphere
op_relation The Cryosphere -- ˜Theœ Cryosphere -- http://www.bibliothek.uni-regensburg.de/ezeit/?2393169 -- http://www.the-cryosphere.net/ -- 1994-0424
https://doi.org/10.5194/tc-17-5061-2023
https://noa.gwlb.de/receive/cop_mods_00070178
https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00068534/tc-17-5061-2023.pdf
https://tc.copernicus.org/articles/17/5061/2023/tc-17-5061-2023.pdf
op_rights https://creativecommons.org/licenses/by/4.0/
uneingeschränkt
info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.5194/tc-17-5061-2023
container_title The Cryosphere
container_volume 17
container_issue 12
container_start_page 5061
op_container_end_page 5074
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