A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR: accompanying dataset ...
Dataset containing surface temperature and surface mass balance datasets generated from the MAR regional climate model over Greenland over two test areas using statistical downscaling tools from 6 km to 100m. The abstract of the accompanying submitted paper follows: The Greenland Ice Sheet (GrIS) ha...
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Online Access: | https://dx.doi.org/10.5281/zenodo.7803610 https://zenodo.org/record/7803610 |
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ftdatacite:10.5281/zenodo.7803610 2023-06-11T04:12:04+02:00 A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR: accompanying dataset ... Tedesco, Marco Cervone, Guido Colosio, Paolo Fettweis, Xavier 2023 https://dx.doi.org/10.5281/zenodo.7803610 https://zenodo.org/record/7803610 en eng Zenodo https://dx.doi.org/10.5281/zenodo.7803611 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess Greenland, SMB, statistical downscaling Dataset dataset 2023 ftdatacite https://doi.org/10.5281/zenodo.780361010.5281/zenodo.7803611 2023-05-02T09:43:47Z Dataset containing surface temperature and surface mass balance datasets generated from the MAR regional climate model over Greenland over two test areas using statistical downscaling tools from 6 km to 100m. The abstract of the accompanying submitted paper follows: The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise and this contribution is projected to accelerate over next decades. A crucial tool for studying the evolution 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 ... Dataset Greenland Ice Sheet DataCite Metadata Store (German National Library of Science and Technology) Greenland |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
Greenland, SMB, statistical downscaling |
spellingShingle |
Greenland, SMB, statistical downscaling Tedesco, Marco Cervone, Guido Colosio, Paolo Fettweis, Xavier A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR: accompanying dataset ... |
topic_facet |
Greenland, SMB, statistical downscaling |
description |
Dataset containing surface temperature and surface mass balance datasets generated from the MAR regional climate model over Greenland over two test areas using statistical downscaling tools from 6 km to 100m. The abstract of the accompanying submitted paper follows: The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise and this contribution is projected to accelerate over next decades. A crucial tool for studying the evolution 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 ... |
format |
Dataset |
author |
Tedesco, Marco Cervone, Guido Colosio, Paolo Fettweis, Xavier |
author_facet |
Tedesco, Marco Cervone, Guido Colosio, Paolo Fettweis, Xavier |
author_sort |
Tedesco, Marco |
title |
A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR: accompanying dataset ... |
title_short |
A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR: accompanying dataset ... |
title_full |
A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR: accompanying dataset ... |
title_fullStr |
A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR: accompanying dataset ... |
title_full_unstemmed |
A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR: accompanying dataset ... |
title_sort |
computationally efficient statistically downscaled 100 m resolution greenland product from the regional climate model mar: accompanying dataset ... |
publisher |
Zenodo |
publishDate |
2023 |
url |
https://dx.doi.org/10.5281/zenodo.7803610 https://zenodo.org/record/7803610 |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Greenland Ice Sheet |
genre_facet |
Greenland Ice Sheet |
op_relation |
https://dx.doi.org/10.5281/zenodo.7803611 |
op_rights |
Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5281/zenodo.780361010.5281/zenodo.7803611 |
_version_ |
1768387674028113920 |