Increasing confidence in projecting the Arctic ice-free year with emergent constraints
Abstract An ice-free Arctic summer is a landmark of global change and has the far-reaching climate, environmental, and economic impacts. However, the Coupled Model Intercomparison Project Phase 6 models’ projected occurrence remains notoriously uncertain. Finding emergent constraints to reduce the p...
Published in: | Environmental Research Letters |
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crioppubl:10.1088/1748-9326/ac0b17 2024-06-02T08:00:17+00:00 Increasing confidence in projecting the Arctic ice-free year with emergent constraints Wang, Bin Zhou, Xiao Ding, Qinghua Liu, Jiping National Oceanic and Atmospheric Administration National Natural Science Foundation of China National Science Foundation Climate Program Office 2021 http://dx.doi.org/10.1088/1748-9326/ac0b17 https://iopscience.iop.org/article/10.1088/1748-9326/ac0b17 https://iopscience.iop.org/article/10.1088/1748-9326/ac0b17/pdf unknown IOP Publishing http://creativecommons.org/licenses/by/4.0 https://iopscience.iop.org/info/page/text-and-data-mining Environmental Research Letters volume 16, issue 9, page 094016 ISSN 1748-9326 journal-article 2021 crioppubl https://doi.org/10.1088/1748-9326/ac0b17 2024-05-07T13:56:06Z Abstract An ice-free Arctic summer is a landmark of global change and has the far-reaching climate, environmental, and economic impacts. However, the Coupled Model Intercomparison Project Phase 6 models’ projected occurrence remains notoriously uncertain. Finding emergent constraints to reduce the projection uncertainties has been a foremost challenge. To establish a physical basis for the constraints, we first demonstrate, with numerical experiments, that the observed trend of Arctic ice loss is primarily driven by the Arctic near-surface air temperature. Thus, two constraints are proposed: the Arctic sea ice sensitivity that measures Arctic sea ice response to the local warming, and the Arctic amplification sensitivity that assesses how well the model responds to anthropogenic forcing and allocates heat to the Arctic region. The two constraints are complementary and nearly scenario-independent. The model-projected first Arctic ice-free year significantly depends on the model’s two climate sensitivities. Thus, the first Arctic ice-free year can be predicted by the linear combination of the two Arctic sensitivity measures. Based on model-simulated sensitivity skills, 20 CMIP models are divided into two equal number groups. The ten realistic-sensitivity models project, with a likelihood of 80%, the ice-free Arctic will occur by additional 0.8 °C global warming from 2019 level or before 2040 under the SSP2-4.5 (medium emission) scenario. The ten realistic-sensitivity models’ spread is reduced by about 70% compared to the ten underestimate-sensitivity models’ large spread. The strategy for creating physics-based emergent constraints through numerical experiments may be instrumental for broad application to other fields for advancing robust projection and understanding uncertainty sources. Article in Journal/Newspaper Arctic Global warming Sea ice IOP Publishing Arctic Environmental Research Letters |
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Abstract An ice-free Arctic summer is a landmark of global change and has the far-reaching climate, environmental, and economic impacts. However, the Coupled Model Intercomparison Project Phase 6 models’ projected occurrence remains notoriously uncertain. Finding emergent constraints to reduce the projection uncertainties has been a foremost challenge. To establish a physical basis for the constraints, we first demonstrate, with numerical experiments, that the observed trend of Arctic ice loss is primarily driven by the Arctic near-surface air temperature. Thus, two constraints are proposed: the Arctic sea ice sensitivity that measures Arctic sea ice response to the local warming, and the Arctic amplification sensitivity that assesses how well the model responds to anthropogenic forcing and allocates heat to the Arctic region. The two constraints are complementary and nearly scenario-independent. The model-projected first Arctic ice-free year significantly depends on the model’s two climate sensitivities. Thus, the first Arctic ice-free year can be predicted by the linear combination of the two Arctic sensitivity measures. Based on model-simulated sensitivity skills, 20 CMIP models are divided into two equal number groups. The ten realistic-sensitivity models project, with a likelihood of 80%, the ice-free Arctic will occur by additional 0.8 °C global warming from 2019 level or before 2040 under the SSP2-4.5 (medium emission) scenario. The ten realistic-sensitivity models’ spread is reduced by about 70% compared to the ten underestimate-sensitivity models’ large spread. The strategy for creating physics-based emergent constraints through numerical experiments may be instrumental for broad application to other fields for advancing robust projection and understanding uncertainty sources. |
author2 |
National Oceanic and Atmospheric Administration National Natural Science Foundation of China National Science Foundation Climate Program Office |
format |
Article in Journal/Newspaper |
author |
Wang, Bin Zhou, Xiao Ding, Qinghua Liu, Jiping |
spellingShingle |
Wang, Bin Zhou, Xiao Ding, Qinghua Liu, Jiping Increasing confidence in projecting the Arctic ice-free year with emergent constraints |
author_facet |
Wang, Bin Zhou, Xiao Ding, Qinghua Liu, Jiping |
author_sort |
Wang, Bin |
title |
Increasing confidence in projecting the Arctic ice-free year with emergent constraints |
title_short |
Increasing confidence in projecting the Arctic ice-free year with emergent constraints |
title_full |
Increasing confidence in projecting the Arctic ice-free year with emergent constraints |
title_fullStr |
Increasing confidence in projecting the Arctic ice-free year with emergent constraints |
title_full_unstemmed |
Increasing confidence in projecting the Arctic ice-free year with emergent constraints |
title_sort |
increasing confidence in projecting the arctic ice-free year with emergent constraints |
publisher |
IOP Publishing |
publishDate |
2021 |
url |
http://dx.doi.org/10.1088/1748-9326/ac0b17 https://iopscience.iop.org/article/10.1088/1748-9326/ac0b17 https://iopscience.iop.org/article/10.1088/1748-9326/ac0b17/pdf |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Global warming Sea ice |
genre_facet |
Arctic Global warming Sea ice |
op_source |
Environmental Research Letters volume 16, issue 9, page 094016 ISSN 1748-9326 |
op_rights |
http://creativecommons.org/licenses/by/4.0 https://iopscience.iop.org/info/page/text-and-data-mining |
op_doi |
https://doi.org/10.1088/1748-9326/ac0b17 |
container_title |
Environmental Research Letters |
_version_ |
1800744267812962304 |