Marginal ice zone fraction benchmarks sea ice and climate model skill

Abstract Global climate models (GCMs) consistently underestimate the response of September Arctic sea-ice area (SIA) to warming. Modeled SIA losses are highly correlated to global mean temperature increases, making it challenging to gauge if improvements in modeled sea ice derive from improved sea-i...

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Published in:Nature Communications
Main Author: Horvat, Christopher
Other Authors: National Aeronautics and Space Administration
Format: Article in Journal/Newspaper
Language:English
Published: Springer Science and Business Media LLC 2021
Subjects:
Online Access:http://dx.doi.org/10.1038/s41467-021-22004-7
http://www.nature.com/articles/s41467-021-22004-7.pdf
http://www.nature.com/articles/s41467-021-22004-7
id crspringernat:10.1038/s41467-021-22004-7
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spelling crspringernat:10.1038/s41467-021-22004-7 2023-05-15T15:04:48+02:00 Marginal ice zone fraction benchmarks sea ice and climate model skill Horvat, Christopher National Aeronautics and Space Administration 2021 http://dx.doi.org/10.1038/s41467-021-22004-7 http://www.nature.com/articles/s41467-021-22004-7.pdf http://www.nature.com/articles/s41467-021-22004-7 en eng Springer Science and Business Media LLC https://creativecommons.org/licenses/by/4.0 https://creativecommons.org/licenses/by/4.0 CC-BY Nature Communications volume 12, issue 1 ISSN 2041-1723 General Physics and Astronomy General Biochemistry, Genetics and Molecular Biology General Chemistry journal-article 2021 crspringernat https://doi.org/10.1038/s41467-021-22004-7 2022-01-04T16:13:17Z Abstract Global climate models (GCMs) consistently underestimate the response of September Arctic sea-ice area (SIA) to warming. Modeled SIA losses are highly correlated to global mean temperature increases, making it challenging to gauge if improvements in modeled sea ice derive from improved sea-ice models or from improvements in forcing driven by other GCM components. I use a set of five large GCM ensembles, and CMIP6 simulations, to quantify GCM internal variability and variability between GCMs from 1979–2014, showing modern GCMs do not plausibly estimate the response of SIA to warming in all months. I identify the marginal ice zone fraction (MIZF) as a metric that is less correlated to warming, has a response plausibly simulated from January–September (but not October–December), and has highly variable future projections across GCMs. These qualities make MIZF useful for evaluating the impact of sea-ice model changes on past, present, and projected sea-ice state. Article in Journal/Newspaper Arctic Sea ice Springer Nature (via Crossref) Arctic Nature Communications 12 1
institution Open Polar
collection Springer Nature (via Crossref)
op_collection_id crspringernat
language English
topic General Physics and Astronomy
General Biochemistry, Genetics and Molecular Biology
General Chemistry
spellingShingle General Physics and Astronomy
General Biochemistry, Genetics and Molecular Biology
General Chemistry
Horvat, Christopher
Marginal ice zone fraction benchmarks sea ice and climate model skill
topic_facet General Physics and Astronomy
General Biochemistry, Genetics and Molecular Biology
General Chemistry
description Abstract Global climate models (GCMs) consistently underestimate the response of September Arctic sea-ice area (SIA) to warming. Modeled SIA losses are highly correlated to global mean temperature increases, making it challenging to gauge if improvements in modeled sea ice derive from improved sea-ice models or from improvements in forcing driven by other GCM components. I use a set of five large GCM ensembles, and CMIP6 simulations, to quantify GCM internal variability and variability between GCMs from 1979–2014, showing modern GCMs do not plausibly estimate the response of SIA to warming in all months. I identify the marginal ice zone fraction (MIZF) as a metric that is less correlated to warming, has a response plausibly simulated from January–September (but not October–December), and has highly variable future projections across GCMs. These qualities make MIZF useful for evaluating the impact of sea-ice model changes on past, present, and projected sea-ice state.
author2 National Aeronautics and Space Administration
format Article in Journal/Newspaper
author Horvat, Christopher
author_facet Horvat, Christopher
author_sort Horvat, Christopher
title Marginal ice zone fraction benchmarks sea ice and climate model skill
title_short Marginal ice zone fraction benchmarks sea ice and climate model skill
title_full Marginal ice zone fraction benchmarks sea ice and climate model skill
title_fullStr Marginal ice zone fraction benchmarks sea ice and climate model skill
title_full_unstemmed Marginal ice zone fraction benchmarks sea ice and climate model skill
title_sort marginal ice zone fraction benchmarks sea ice and climate model skill
publisher Springer Science and Business Media LLC
publishDate 2021
url http://dx.doi.org/10.1038/s41467-021-22004-7
http://www.nature.com/articles/s41467-021-22004-7.pdf
http://www.nature.com/articles/s41467-021-22004-7
geographic Arctic
geographic_facet Arctic
genre Arctic
Sea ice
genre_facet Arctic
Sea ice
op_source Nature Communications
volume 12, issue 1
ISSN 2041-1723
op_rights https://creativecommons.org/licenses/by/4.0
https://creativecommons.org/licenses/by/4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.1038/s41467-021-22004-7
container_title Nature Communications
container_volume 12
container_issue 1
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