A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR
peer reviewed Abstract. 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 clima...
Published in: | The Cryosphere |
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Copernicus GmbH
2023
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Online Access: | https://orbi.uliege.be/handle/2268/309353 https://orbi.uliege.be/bitstream/2268/309353/1/tc-17-5061-2023.pdf https://doi.org/10.5194/tc-17-5061-2023 |
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ftorbi:oai:orbi.ulg.ac.be:2268/309353 2024-04-21T08:03:30+00:00 A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR Tedesco, Marco Colosio, Paolo Fettweis, Xavier Cervone, Guido SPHERES - ULiège BE 2023-11-30 https://orbi.uliege.be/handle/2268/309353 https://orbi.uliege.be/bitstream/2268/309353/1/tc-17-5061-2023.pdf https://doi.org/10.5194/tc-17-5061-2023 en eng Copernicus GmbH https://tc.copernicus.org/articles/17/5061/2023/tc-17-5061-2023.pdf urn:issn:1994-0416 urn:issn:1994-0424 https://orbi.uliege.be/handle/2268/309353 info:hdl:2268/309353 https://orbi.uliege.be/bitstream/2268/309353/1/tc-17-5061-2023.pdf doi:10.5194/tc-17-5061-2023 scopus-id:2-s2.0-85179390395 open access http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess The Cryosphere, 17 (12), 5061-5074 (2023-11-30) Earth-Surface Processes Water Science and Technology Physical chemical mathematical & earth Sciences Earth sciences & physical geography Physique chimie mathématiques & sciences de la terre Sciences de la terre & géographie physique journal article http://purl.org/coar/resource_type/c_6501 info:eu-repo/semantics/article peer reviewed 2023 ftorbi https://doi.org/10.5194/tc-17-5061-2023 2024-03-27T14:59:37Z peer reviewed Abstract. 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 University of Liège: ORBi (Open Repository and Bibliography) The Cryosphere 17 12 5061 5074 |
institution |
Open Polar |
collection |
University of Liège: ORBi (Open Repository and Bibliography) |
op_collection_id |
ftorbi |
language |
English |
topic |
Earth-Surface Processes Water Science and Technology Physical chemical mathematical & earth Sciences Earth sciences & physical geography Physique chimie mathématiques & sciences de la terre Sciences de la terre & géographie physique |
spellingShingle |
Earth-Surface Processes Water Science and Technology Physical chemical mathematical & earth Sciences Earth sciences & physical geography Physique chimie mathématiques & sciences de la terre Sciences de la terre & géographie physique 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 |
Earth-Surface Processes Water Science and Technology Physical chemical mathematical & earth Sciences Earth sciences & physical geography Physique chimie mathématiques & sciences de la terre Sciences de la terre & géographie physique |
description |
peer reviewed Abstract. 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. |
author2 |
SPHERES - ULiège BE |
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 GmbH |
publishDate |
2023 |
url |
https://orbi.uliege.be/handle/2268/309353 https://orbi.uliege.be/bitstream/2268/309353/1/tc-17-5061-2023.pdf https://doi.org/10.5194/tc-17-5061-2023 |
genre |
Greenland Ice Sheet The Cryosphere |
genre_facet |
Greenland Ice Sheet The Cryosphere |
op_source |
The Cryosphere, 17 (12), 5061-5074 (2023-11-30) |
op_relation |
https://tc.copernicus.org/articles/17/5061/2023/tc-17-5061-2023.pdf urn:issn:1994-0416 urn:issn:1994-0424 https://orbi.uliege.be/handle/2268/309353 info:hdl:2268/309353 https://orbi.uliege.be/bitstream/2268/309353/1/tc-17-5061-2023.pdf doi:10.5194/tc-17-5061-2023 scopus-id:2-s2.0-85179390395 |
op_rights |
open access http://purl.org/coar/access_right/c_abf2 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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1796943319092166656 |