Lagged Linkage between the Kara–Barents Sea Ice and Early Summer Rainfall in Eastern China in Chinese CMIP6 Models
The lagged relationship between Kara–Barents sea ice and summer precipitation in eastern China is evaluated for Chinese models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). A previous study revealed a dipole rainfall structure in eastern China related to winter Arcti...
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ftmdpi:oai:mdpi.com:/2072-4292/15/8/2111/ 2023-08-20T04:04:26+02:00 Lagged Linkage between the Kara–Barents Sea Ice and Early Summer Rainfall in Eastern China in Chinese CMIP6 Models Huidi Yang Jian Rao Haohan Chen Qian Lu Jingjia Luo agris 2023-04-17 application/pdf https://doi.org/10.3390/rs15082111 EN eng Multidisciplinary Digital Publishing Institute Atmospheric Remote Sensing https://dx.doi.org/10.3390/rs15082111 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 15; Issue 8; Pages: 2111 rainfall in China CMIP Kara–Barents sea ice Text 2023 ftmdpi https://doi.org/10.3390/rs15082111 2023-08-01T09:43:09Z The lagged relationship between Kara–Barents sea ice and summer precipitation in eastern China is evaluated for Chinese models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). A previous study revealed a dipole rainfall structure in eastern China related to winter Arctic sea ice variability. Almost all Chinese CMIP6 models reproduce the variability and climatology of the sea ice in most of the Arctic well except the transition regions with evident biases. Further, all Chinese CMIP6 models successfully simulate the decreasing trend for the Kara–Barents sea ice. The dipole centers located in the Yangtze–Huai River Valley (YHRV) and South China (SC) related to Kara–Barents sea ice variability are simulated with different degrees of success. The anomalous dipole rainfall structure related to the winter Kara–Barents sea ice variability can roughly be reproduced by two models, while other models reproduce a shifted rainfall anomaly pattern or with the sign reversed. The possible delayed influence of sea ice forcing on early summer precipitation in China is established via three possible processes: the long memory of ice, the long-lasting stratospheric anomalies triggered by winter sea ice forcing, and the downward impact of the stratosphere as the mediator. Most Chinese models can simulate the negative Northern Hemisphere Annular Mode (NAM) phase in early winter but fail to reproduce the reversal of the stratospheric anomalies to a positive NAM pattern in spring and early summer. Most models underestimate the downward impact from the stratosphere to the troposphere. This implies that the stratospheric pathway is essential to mediate the winter sea ice forcing and rainfall in early summer over China for CMIP6 models. Text Arctic Barents Sea Sea ice MDPI Open Access Publishing Arctic Barents Sea Remote Sensing 15 8 2111 |
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Open Polar |
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MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
rainfall in China CMIP Kara–Barents sea ice |
spellingShingle |
rainfall in China CMIP Kara–Barents sea ice Huidi Yang Jian Rao Haohan Chen Qian Lu Jingjia Luo Lagged Linkage between the Kara–Barents Sea Ice and Early Summer Rainfall in Eastern China in Chinese CMIP6 Models |
topic_facet |
rainfall in China CMIP Kara–Barents sea ice |
description |
The lagged relationship between Kara–Barents sea ice and summer precipitation in eastern China is evaluated for Chinese models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). A previous study revealed a dipole rainfall structure in eastern China related to winter Arctic sea ice variability. Almost all Chinese CMIP6 models reproduce the variability and climatology of the sea ice in most of the Arctic well except the transition regions with evident biases. Further, all Chinese CMIP6 models successfully simulate the decreasing trend for the Kara–Barents sea ice. The dipole centers located in the Yangtze–Huai River Valley (YHRV) and South China (SC) related to Kara–Barents sea ice variability are simulated with different degrees of success. The anomalous dipole rainfall structure related to the winter Kara–Barents sea ice variability can roughly be reproduced by two models, while other models reproduce a shifted rainfall anomaly pattern or with the sign reversed. The possible delayed influence of sea ice forcing on early summer precipitation in China is established via three possible processes: the long memory of ice, the long-lasting stratospheric anomalies triggered by winter sea ice forcing, and the downward impact of the stratosphere as the mediator. Most Chinese models can simulate the negative Northern Hemisphere Annular Mode (NAM) phase in early winter but fail to reproduce the reversal of the stratospheric anomalies to a positive NAM pattern in spring and early summer. Most models underestimate the downward impact from the stratosphere to the troposphere. This implies that the stratospheric pathway is essential to mediate the winter sea ice forcing and rainfall in early summer over China for CMIP6 models. |
format |
Text |
author |
Huidi Yang Jian Rao Haohan Chen Qian Lu Jingjia Luo |
author_facet |
Huidi Yang Jian Rao Haohan Chen Qian Lu Jingjia Luo |
author_sort |
Huidi Yang |
title |
Lagged Linkage between the Kara–Barents Sea Ice and Early Summer Rainfall in Eastern China in Chinese CMIP6 Models |
title_short |
Lagged Linkage between the Kara–Barents Sea Ice and Early Summer Rainfall in Eastern China in Chinese CMIP6 Models |
title_full |
Lagged Linkage between the Kara–Barents Sea Ice and Early Summer Rainfall in Eastern China in Chinese CMIP6 Models |
title_fullStr |
Lagged Linkage between the Kara–Barents Sea Ice and Early Summer Rainfall in Eastern China in Chinese CMIP6 Models |
title_full_unstemmed |
Lagged Linkage between the Kara–Barents Sea Ice and Early Summer Rainfall in Eastern China in Chinese CMIP6 Models |
title_sort |
lagged linkage between the kara–barents sea ice and early summer rainfall in eastern china in chinese cmip6 models |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2023 |
url |
https://doi.org/10.3390/rs15082111 |
op_coverage |
agris |
geographic |
Arctic Barents Sea |
geographic_facet |
Arctic Barents Sea |
genre |
Arctic Barents Sea Sea ice |
genre_facet |
Arctic Barents Sea Sea ice |
op_source |
Remote Sensing; Volume 15; Issue 8; Pages: 2111 |
op_relation |
Atmospheric Remote Sensing https://dx.doi.org/10.3390/rs15082111 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs15082111 |
container_title |
Remote Sensing |
container_volume |
15 |
container_issue |
8 |
container_start_page |
2111 |
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1774714811910717440 |