Assessment of Arctic sea ice and surface climate conditions in nine CMIP6 climate models
ABSTRACTThe observed retreat and anticipated further decline in Arctic sea ice holds strong climate, environmental, and societal implications. In predicting climate evolution, ensembles of coupled climate models have demonstrated appreciable accuracy in simulating sea-ice area trends throughout the...
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Format: | Article |
Language: | English |
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Taylor & Francis Group
2023-12-01
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Series: | Arctic, Antarctic, and Alpine Research |
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Online Access: | https://www.tandfonline.com/doi/10.1080/15230430.2023.2271592 |
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author | Martin Henke Felício Cassalho Tyler Miesse Celso M. Ferreira Jinlun Zhang Thomas M. Ravens |
author_facet | Martin Henke Felício Cassalho Tyler Miesse Celso M. Ferreira Jinlun Zhang Thomas M. Ravens |
author_sort | Martin Henke |
collection | DOAJ |
description | ABSTRACTThe observed retreat and anticipated further decline in Arctic sea ice holds strong climate, environmental, and societal implications. In predicting climate evolution, ensembles of coupled climate models have demonstrated appreciable accuracy in simulating sea-ice area trends throughout the historical period, yet individual climate models still show significant differences in accurately representing the sea-ice thickness distribution. To better understand individual model performance in sea-ice simulation, nine climate models were evaluated in comparison with Arctic satellite and reanalysis-derived sea-ice thickness data, sea-ice area records, and atmospheric reanalysis data of surface wind and air temperature. This assessment found that the simulated spatial distribution of historical sea-ice thickness varies greatly between models and that several key limitations persist among models. Primarily, most models do not capture the thickest regimes of multiyear ice present in the Wandel and Lincoln seas; those that do often possess erroneous positive bias in other regions such as the Laptev Sea or along the Eurasian Arctic Shelf. This analysis provides enhanced understanding of individual model historical simulation performance, which is critical in informing the selection of coupled climate model projections for dependent future modeling efforts. |
first_indexed | 2024-03-07T19:48:05Z |
format | Article |
id | doaj.art-20823ce620ef4cbfae285f9717f17f25 |
institution | Directory Open Access Journal |
issn | 1523-0430 1938-4246 |
language | English |
last_indexed | 2024-04-24T13:58:36Z |
publishDate | 2023-12-01 |
publisher | Taylor & Francis Group |
record_format | Article |
series | Arctic, Antarctic, and Alpine Research |
spelling | doaj.art-20823ce620ef4cbfae285f9717f17f252024-04-03T14:36:12ZengTaylor & Francis GroupArctic, Antarctic, and Alpine Research1523-04301938-42462023-12-0155110.1080/15230430.2023.2271592Assessment of Arctic sea ice and surface climate conditions in nine CMIP6 climate modelsMartin Henke0Felício Cassalho1Tyler Miesse2Celso M. Ferreira3Jinlun Zhang4Thomas M. Ravens5Department of Civil, Environmental, and Infrastructure Engineering, George Mason University, Fairfax, Virginia, USADepartment of Civil, Environmental, and Infrastructure Engineering, George Mason University, Fairfax, Virginia, USADepartment of Civil, Environmental, and Infrastructure Engineering, George Mason University, Fairfax, Virginia, USADepartment of Civil, Environmental, and Infrastructure Engineering, George Mason University, Fairfax, Virginia, USAPolar Science Center, Applied Physics Laboratory, University of Washington, Seattle, Washington, USACollege of Engineering, University of Alaska Anchorage, Anchorage, Alaska, USAABSTRACTThe observed retreat and anticipated further decline in Arctic sea ice holds strong climate, environmental, and societal implications. In predicting climate evolution, ensembles of coupled climate models have demonstrated appreciable accuracy in simulating sea-ice area trends throughout the historical period, yet individual climate models still show significant differences in accurately representing the sea-ice thickness distribution. To better understand individual model performance in sea-ice simulation, nine climate models were evaluated in comparison with Arctic satellite and reanalysis-derived sea-ice thickness data, sea-ice area records, and atmospheric reanalysis data of surface wind and air temperature. This assessment found that the simulated spatial distribution of historical sea-ice thickness varies greatly between models and that several key limitations persist among models. Primarily, most models do not capture the thickest regimes of multiyear ice present in the Wandel and Lincoln seas; those that do often possess erroneous positive bias in other regions such as the Laptev Sea or along the Eurasian Arctic Shelf. This analysis provides enhanced understanding of individual model historical simulation performance, which is critical in informing the selection of coupled climate model projections for dependent future modeling efforts.https://www.tandfonline.com/doi/10.1080/15230430.2023.2271592Climate model assessmentsea iceArctic |
spellingShingle | Martin Henke Felício Cassalho Tyler Miesse Celso M. Ferreira Jinlun Zhang Thomas M. Ravens Assessment of Arctic sea ice and surface climate conditions in nine CMIP6 climate models Arctic, Antarctic, and Alpine Research Climate model assessment sea ice Arctic |
title | Assessment of Arctic sea ice and surface climate conditions in nine CMIP6 climate models |
title_full | Assessment of Arctic sea ice and surface climate conditions in nine CMIP6 climate models |
title_fullStr | Assessment of Arctic sea ice and surface climate conditions in nine CMIP6 climate models |
title_full_unstemmed | Assessment of Arctic sea ice and surface climate conditions in nine CMIP6 climate models |
title_short | Assessment of Arctic sea ice and surface climate conditions in nine CMIP6 climate models |
title_sort | assessment of arctic sea ice and surface climate conditions in nine cmip6 climate models |
topic | Climate model assessment sea ice Arctic |
url | https://www.tandfonline.com/doi/10.1080/15230430.2023.2271592 |
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