Climate prediction of summer extreme precipitation frequency in the Yangtze River valley based on sea surface temperature in the southern Indian Ocean and ice concentration in the Beaufort Sea

Abstract Three statistical prediction models for the summer extreme precipitation frequency (EPF) in the middle and lower reaches of the Yangtze River valley (MLYRV) based on the winter sea surface temperature in the southern Indian Ocean (SIO‐SST; Scheme‐SST), the spring sea‐ice concentration in th...

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Published in:International Journal of Climatology
Main Authors: Tian, Baoqiang, Fan, Ke
Other Authors: National Natural Science Foundation of China
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2019
Subjects:
Online Access:http://dx.doi.org/10.1002/joc.6446
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spelling crwiley:10.1002/joc.6446 2024-06-23T07:45:09+00:00 Climate prediction of summer extreme precipitation frequency in the Yangtze River valley based on sea surface temperature in the southern Indian Ocean and ice concentration in the Beaufort Sea Tian, Baoqiang Fan, Ke National Natural Science Foundation of China 2019 http://dx.doi.org/10.1002/joc.6446 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.6446 https://onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6446 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/joc.6446 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6446 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor International Journal of Climatology volume 40, issue 9, page 4117-4130 ISSN 0899-8418 1097-0088 journal-article 2019 crwiley https://doi.org/10.1002/joc.6446 2024-06-04T06:42:48Z Abstract Three statistical prediction models for the summer extreme precipitation frequency (EPF) in the middle and lower reaches of the Yangtze River valley (MLYRV) based on the winter sea surface temperature in the southern Indian Ocean (SIO‐SST; Scheme‐SST), the spring sea‐ice concentration in the Beaufort Sea (Scheme‐SIC), and both predictors (Scheme‐SS), are established by using the year‐to‐year increment method. The winter SIO‐SST may affect the SST anomaly in the east of Australia via a teleconnection pattern. The east of Australia SST signal in winter continues until the following summer and then affects the summer EPF in the MLYRV via modulation of the meridional Hadley circulation in the western North Pacific. The positive Beaufort SIC anomaly may result in a negative summer SST anomaly by the increased surface albedo. In response, the atmospheric circulation presents a dipole anomaly distribution in the Beaufort Sea and the Barents Sea. The Arctic dipole anomaly may bring about frequent extreme precipitation in the MLYRV by adjusting the position of the East Asian westerly jet and Eurasian teleconnection pattern. The prediction skill of the summer EPF for Scheme‐SS is higher than that of Scheme‐SST and Scheme‐SIC in the cross‐validation test during 1962–2017 and the independent hindcast during 1992–2017. Scheme‐SS shows a higher prediction skill of the summer EPF than that of Scheme‐SST and Scheme‐SIC, with a time correlation coefficient of 0.62, accounting for 39% of the total variance, of which 35% is the winter SIO‐SST and 4% the spring Beaufort SIC. Scheme‐SS not only shows a rather high predictive ability for the anomalous summer EPF but can also reproduce the increasing trend of extremely heavy precipitation. Article in Journal/Newspaper albedo Arctic Barents Sea Beaufort Sea Sea ice Wiley Online Library Arctic Barents Sea Indian Pacific International Journal of Climatology 40 9 4117 4130
institution Open Polar
collection Wiley Online Library
op_collection_id crwiley
language English
description Abstract Three statistical prediction models for the summer extreme precipitation frequency (EPF) in the middle and lower reaches of the Yangtze River valley (MLYRV) based on the winter sea surface temperature in the southern Indian Ocean (SIO‐SST; Scheme‐SST), the spring sea‐ice concentration in the Beaufort Sea (Scheme‐SIC), and both predictors (Scheme‐SS), are established by using the year‐to‐year increment method. The winter SIO‐SST may affect the SST anomaly in the east of Australia via a teleconnection pattern. The east of Australia SST signal in winter continues until the following summer and then affects the summer EPF in the MLYRV via modulation of the meridional Hadley circulation in the western North Pacific. The positive Beaufort SIC anomaly may result in a negative summer SST anomaly by the increased surface albedo. In response, the atmospheric circulation presents a dipole anomaly distribution in the Beaufort Sea and the Barents Sea. The Arctic dipole anomaly may bring about frequent extreme precipitation in the MLYRV by adjusting the position of the East Asian westerly jet and Eurasian teleconnection pattern. The prediction skill of the summer EPF for Scheme‐SS is higher than that of Scheme‐SST and Scheme‐SIC in the cross‐validation test during 1962–2017 and the independent hindcast during 1992–2017. Scheme‐SS shows a higher prediction skill of the summer EPF than that of Scheme‐SST and Scheme‐SIC, with a time correlation coefficient of 0.62, accounting for 39% of the total variance, of which 35% is the winter SIO‐SST and 4% the spring Beaufort SIC. Scheme‐SS not only shows a rather high predictive ability for the anomalous summer EPF but can also reproduce the increasing trend of extremely heavy precipitation.
author2 National Natural Science Foundation of China
format Article in Journal/Newspaper
author Tian, Baoqiang
Fan, Ke
spellingShingle Tian, Baoqiang
Fan, Ke
Climate prediction of summer extreme precipitation frequency in the Yangtze River valley based on sea surface temperature in the southern Indian Ocean and ice concentration in the Beaufort Sea
author_facet Tian, Baoqiang
Fan, Ke
author_sort Tian, Baoqiang
title Climate prediction of summer extreme precipitation frequency in the Yangtze River valley based on sea surface temperature in the southern Indian Ocean and ice concentration in the Beaufort Sea
title_short Climate prediction of summer extreme precipitation frequency in the Yangtze River valley based on sea surface temperature in the southern Indian Ocean and ice concentration in the Beaufort Sea
title_full Climate prediction of summer extreme precipitation frequency in the Yangtze River valley based on sea surface temperature in the southern Indian Ocean and ice concentration in the Beaufort Sea
title_fullStr Climate prediction of summer extreme precipitation frequency in the Yangtze River valley based on sea surface temperature in the southern Indian Ocean and ice concentration in the Beaufort Sea
title_full_unstemmed Climate prediction of summer extreme precipitation frequency in the Yangtze River valley based on sea surface temperature in the southern Indian Ocean and ice concentration in the Beaufort Sea
title_sort climate prediction of summer extreme precipitation frequency in the yangtze river valley based on sea surface temperature in the southern indian ocean and ice concentration in the beaufort sea
publisher Wiley
publishDate 2019
url http://dx.doi.org/10.1002/joc.6446
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.6446
https://onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6446
https://onlinelibrary.wiley.com/doi/full-xml/10.1002/joc.6446
https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6446
geographic Arctic
Barents Sea
Indian
Pacific
geographic_facet Arctic
Barents Sea
Indian
Pacific
genre albedo
Arctic
Barents Sea
Beaufort Sea
Sea ice
genre_facet albedo
Arctic
Barents Sea
Beaufort Sea
Sea ice
op_source International Journal of Climatology
volume 40, issue 9, page 4117-4130
ISSN 0899-8418 1097-0088
op_rights http://onlinelibrary.wiley.com/termsAndConditions#vor
op_doi https://doi.org/10.1002/joc.6446
container_title International Journal of Climatology
container_volume 40
container_issue 9
container_start_page 4117
op_container_end_page 4130
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