Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals
Greenland ice sheet mass loss continues to accelerate as global temperatures increase. The surface albedo of the ice sheet determines the amount of absorbed solar energy, which is a key factor in driving surface snow and ice melting. Satellite-retrieved snow albedo allows us to compare and optimise...
Published in: | The Cryosphere |
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Format: | Article in Journal/Newspaper |
Language: | English |
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2023
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Online Access: | https://hal.science/hal-04172792 https://hal.science/hal-04172792/document https://hal.science/hal-04172792/file/tc-17-2705-2023.pdf https://doi.org/10.5194/tc-17-2705-2023 |
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ftccsdartic:oai:HAL:hal-04172792v1 2023-08-27T04:09:43+02:00 Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals Raoult, Nina Charbit, Sylvie Dumas, Christophe Maignan, Fabienne Ottlé, Catherine Bastrikov, Vladislav Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) Modélisation du climat (CLIM) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) Modélisation des Surfaces et Interfaces Continentales (MOSAIC) Science Partners, Paris 2023-07-12 https://hal.science/hal-04172792 https://hal.science/hal-04172792/document https://hal.science/hal-04172792/file/tc-17-2705-2023.pdf https://doi.org/10.5194/tc-17-2705-2023 en eng HAL CCSD Copernicus info:eu-repo/semantics/altIdentifier/doi/10.5194/tc-17-2705-2023 hal-04172792 https://hal.science/hal-04172792 https://hal.science/hal-04172792/document https://hal.science/hal-04172792/file/tc-17-2705-2023.pdf doi:10.5194/tc-17-2705-2023 info:eu-repo/semantics/OpenAccess ISSN: 1994-0424 EISSN: 1994-0416 The Cryosphere https://hal.science/hal-04172792 The Cryosphere, 2023, 17 (7), pp.2705 - 2724. ⟨10.5194/tc-17-2705-2023⟩ [SDU]Sciences of the Universe [physics] info:eu-repo/semantics/article Journal articles 2023 ftccsdartic https://doi.org/10.5194/tc-17-2705-2023 2023-08-05T22:35:21Z Greenland ice sheet mass loss continues to accelerate as global temperatures increase. The surface albedo of the ice sheet determines the amount of absorbed solar energy, which is a key factor in driving surface snow and ice melting. Satellite-retrieved snow albedo allows us to compare and optimise modelled albedo over the entirety of the ice sheet. We optimise the parameters of the albedo scheme in the ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) land surface model for 3 random years taken over the 2000-2017 period and validate over the remaining years. In particular, we want to improve the albedo at the edges of the ice sheet, since they correspond to ablation areas and show the greatest variations in runoff and surface mass balance. By giving a larger weight to points at the ice sheet's edge, we improve the model-data fit by reducing the root-mean-square deviation by over 25 % for the whole ice sheet for the summer months. This improvement is consistent for all years, even those not used in the calibration step. We also show the optimisation successfully improves the model-data fit at 87.5 % of in situ sites from the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) network. We conclude by showing which additional model outputs are impacted by changes to the albedo parameters, encouraging future work using multiple data streams when optimising these parameters. Article in Journal/Newspaper Greenland Ice Sheet The Cryosphere Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) Greenland The Cryosphere 17 7 2705 2724 |
institution |
Open Polar |
collection |
Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) |
op_collection_id |
ftccsdartic |
language |
English |
topic |
[SDU]Sciences of the Universe [physics] |
spellingShingle |
[SDU]Sciences of the Universe [physics] Raoult, Nina Charbit, Sylvie Dumas, Christophe Maignan, Fabienne Ottlé, Catherine Bastrikov, Vladislav Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals |
topic_facet |
[SDU]Sciences of the Universe [physics] |
description |
Greenland ice sheet mass loss continues to accelerate as global temperatures increase. The surface albedo of the ice sheet determines the amount of absorbed solar energy, which is a key factor in driving surface snow and ice melting. Satellite-retrieved snow albedo allows us to compare and optimise modelled albedo over the entirety of the ice sheet. We optimise the parameters of the albedo scheme in the ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) land surface model for 3 random years taken over the 2000-2017 period and validate over the remaining years. In particular, we want to improve the albedo at the edges of the ice sheet, since they correspond to ablation areas and show the greatest variations in runoff and surface mass balance. By giving a larger weight to points at the ice sheet's edge, we improve the model-data fit by reducing the root-mean-square deviation by over 25 % for the whole ice sheet for the summer months. This improvement is consistent for all years, even those not used in the calibration step. We also show the optimisation successfully improves the model-data fit at 87.5 % of in situ sites from the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) network. We conclude by showing which additional model outputs are impacted by changes to the albedo parameters, encouraging future work using multiple data streams when optimising these parameters. |
author2 |
Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) Modélisation du climat (CLIM) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) Modélisation des Surfaces et Interfaces Continentales (MOSAIC) Science Partners, Paris |
format |
Article in Journal/Newspaper |
author |
Raoult, Nina Charbit, Sylvie Dumas, Christophe Maignan, Fabienne Ottlé, Catherine Bastrikov, Vladislav |
author_facet |
Raoult, Nina Charbit, Sylvie Dumas, Christophe Maignan, Fabienne Ottlé, Catherine Bastrikov, Vladislav |
author_sort |
Raoult, Nina |
title |
Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals |
title_short |
Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals |
title_full |
Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals |
title_fullStr |
Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals |
title_full_unstemmed |
Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals |
title_sort |
improving modelled albedo over the greenland ice sheet through parameter optimisation and modis snow albedo retrievals |
publisher |
HAL CCSD |
publishDate |
2023 |
url |
https://hal.science/hal-04172792 https://hal.science/hal-04172792/document https://hal.science/hal-04172792/file/tc-17-2705-2023.pdf https://doi.org/10.5194/tc-17-2705-2023 |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Greenland Ice Sheet The Cryosphere |
genre_facet |
Greenland Ice Sheet The Cryosphere |
op_source |
ISSN: 1994-0424 EISSN: 1994-0416 The Cryosphere https://hal.science/hal-04172792 The Cryosphere, 2023, 17 (7), pp.2705 - 2724. ⟨10.5194/tc-17-2705-2023⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.5194/tc-17-2705-2023 hal-04172792 https://hal.science/hal-04172792 https://hal.science/hal-04172792/document https://hal.science/hal-04172792/file/tc-17-2705-2023.pdf doi:10.5194/tc-17-2705-2023 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.5194/tc-17-2705-2023 |
container_title |
The Cryosphere |
container_volume |
17 |
container_issue |
7 |
container_start_page |
2705 |
op_container_end_page |
2724 |
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1775351281882234880 |