Seasonal Sea Ice Prediction with the CICE Model and Positive Impact of CryoSat-2 Ice Thickness Initialization
The Los Alamos sea ice model (CICE) is being tested in standalone mode for its suitability for seasonal time scale prediction. The prescribed atmospheric forcings to drive the model are from the NCEP Climate Forecast System Reanalysis (CFSR). A built-in mixed layer ocean model in CICE is used. Initi...
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ftcopernicus:oai:publications.copernicus.org:tcd99115 2023-05-15T15:07:49+02:00 Seasonal Sea Ice Prediction with the CICE Model and Positive Impact of CryoSat-2 Ice Thickness Initialization Sun, Shan Solomon, Amy 2021-11-22 application/pdf https://doi.org/10.5194/tc-2021-353 https://tc.copernicus.org/preprints/tc-2021-353/ eng eng doi:10.5194/tc-2021-353 https://tc.copernicus.org/preprints/tc-2021-353/ eISSN: 1994-0424 Text 2021 ftcopernicus https://doi.org/10.5194/tc-2021-353 2021-11-29T17:22:30Z The Los Alamos sea ice model (CICE) is being tested in standalone mode for its suitability for seasonal time scale prediction. The prescribed atmospheric forcings to drive the model are from the NCEP Climate Forecast System Reanalysis (CFSR). A built-in mixed layer ocean model in CICE is used. Initial conditions for the sea ice and the mixed layer ocean in the control experiments are also from CFSR. The simulated sea ice extent in the Arctic in control experiments is generally in good agreement with observations in the warm season at all lead times up to 12 months, suggesting that CICE is able to provide useful ice edge information for seasonal prediction. However, the ice thickness forecast has a positive bias stemming from the initial conditions and often persists for more than a season, limiting the model’s seasonal forecast skill. In addition, thicker ice has a lower melting rate in the warm season, both at the bottom and top, contributing to this positive bias. When this bias is removed by initializing the model using ice thickness data from satellite observations while keeping all other initial fields unchanged, both simulated ice edge and thickness improve. This indicates the important role of ice thickness initialization in sea ice seasonal prediction. Text Arctic Sea ice Copernicus Publications: E-Journals Arctic |
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Copernicus Publications: E-Journals |
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ftcopernicus |
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English |
description |
The Los Alamos sea ice model (CICE) is being tested in standalone mode for its suitability for seasonal time scale prediction. The prescribed atmospheric forcings to drive the model are from the NCEP Climate Forecast System Reanalysis (CFSR). A built-in mixed layer ocean model in CICE is used. Initial conditions for the sea ice and the mixed layer ocean in the control experiments are also from CFSR. The simulated sea ice extent in the Arctic in control experiments is generally in good agreement with observations in the warm season at all lead times up to 12 months, suggesting that CICE is able to provide useful ice edge information for seasonal prediction. However, the ice thickness forecast has a positive bias stemming from the initial conditions and often persists for more than a season, limiting the model’s seasonal forecast skill. In addition, thicker ice has a lower melting rate in the warm season, both at the bottom and top, contributing to this positive bias. When this bias is removed by initializing the model using ice thickness data from satellite observations while keeping all other initial fields unchanged, both simulated ice edge and thickness improve. This indicates the important role of ice thickness initialization in sea ice seasonal prediction. |
format |
Text |
author |
Sun, Shan Solomon, Amy |
spellingShingle |
Sun, Shan Solomon, Amy Seasonal Sea Ice Prediction with the CICE Model and Positive Impact of CryoSat-2 Ice Thickness Initialization |
author_facet |
Sun, Shan Solomon, Amy |
author_sort |
Sun, Shan |
title |
Seasonal Sea Ice Prediction with the CICE Model and Positive Impact of CryoSat-2 Ice Thickness Initialization |
title_short |
Seasonal Sea Ice Prediction with the CICE Model and Positive Impact of CryoSat-2 Ice Thickness Initialization |
title_full |
Seasonal Sea Ice Prediction with the CICE Model and Positive Impact of CryoSat-2 Ice Thickness Initialization |
title_fullStr |
Seasonal Sea Ice Prediction with the CICE Model and Positive Impact of CryoSat-2 Ice Thickness Initialization |
title_full_unstemmed |
Seasonal Sea Ice Prediction with the CICE Model and Positive Impact of CryoSat-2 Ice Thickness Initialization |
title_sort |
seasonal sea ice prediction with the cice model and positive impact of cryosat-2 ice thickness initialization |
publishDate |
2021 |
url |
https://doi.org/10.5194/tc-2021-353 https://tc.copernicus.org/preprints/tc-2021-353/ |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
eISSN: 1994-0424 |
op_relation |
doi:10.5194/tc-2021-353 https://tc.copernicus.org/preprints/tc-2021-353/ |
op_doi |
https://doi.org/10.5194/tc-2021-353 |
_version_ |
1766339237405261824 |