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 |
---|---|
Main Authors: | , , , , , |
Format: | Text |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | https://doi.org/10.5194/tc-17-2705-2023 https://tc.copernicus.org/articles/17/2705/2023/ |
id |
ftcopernicus:oai:publications.copernicus.org:tc105571 |
---|---|
record_format |
openpolar |
spelling |
ftcopernicus:oai:publications.copernicus.org:tc105571 2023-07-30T04:03:48+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 2023-07-12 application/pdf https://doi.org/10.5194/tc-17-2705-2023 https://tc.copernicus.org/articles/17/2705/2023/ eng eng doi:10.5194/tc-17-2705-2023 https://tc.copernicus.org/articles/17/2705/2023/ eISSN: 1994-0424 Text 2023 ftcopernicus https://doi.org/10.5194/tc-17-2705-2023 2023-07-17T16:24:17Z 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. Text Greenland Ice Sheet Copernicus Publications: E-Journals Greenland The Cryosphere 17 7 2705 2724 |
institution |
Open Polar |
collection |
Copernicus Publications: E-Journals |
op_collection_id |
ftcopernicus |
language |
English |
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. |
format |
Text |
author |
Raoult, Nina Charbit, Sylvie Dumas, Christophe Maignan, Fabienne Ottlé, Catherine Bastrikov, Vladislav |
spellingShingle |
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 |
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 |
publishDate |
2023 |
url |
https://doi.org/10.5194/tc-17-2705-2023 https://tc.copernicus.org/articles/17/2705/2023/ |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Greenland Ice Sheet |
genre_facet |
Greenland Ice Sheet |
op_source |
eISSN: 1994-0424 |
op_relation |
doi:10.5194/tc-17-2705-2023 https://tc.copernicus.org/articles/17/2705/2023/ |
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 |
_version_ |
1772814901202386944 |