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Physical processes of summer extreme rainfall interannual variability in eastern China. part I, observational analysis

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Tian, F., Li, S., Dong, B. orcid id iconORCID: https://orcid.org/0000-0003-0809-7911, Klingaman, N. P. orcid id iconORCID: https://orcid.org/0000-0002-2927-9303, Freychet, N. and Sparrow, S. (2022) Physical processes of summer extreme rainfall interannual variability in eastern China. part I, observational analysis. Climate Dynamics, 59. pp. 201-217. ISSN 0930-7575 doi: 10.1007/s00382-021-06123-x

Abstract/Summary

Extreme precipitation can have catastrophic effects in China by triggering floods, landslides, and other natural disasters. We measure extreme precipitation over eastern China by the maximum of five-day precipitation amount (Rx5day) in June, July, and August (JJA), which contributes more than 20% of the climate mean of JJA regional total precipitation. Based on the empirical orthogonal teleconnection (EOT) method, this work identifies four dominant regions of observed Rx5day interannual variability in eastern China: north-eastern China (EOT1), the southern lower reaches of the Yangtze valley (EOT2), southern China (EOT3) and the northern lower reaches of the Yangtze valley (EOT4). EOT1 extreme precipitation is related to a strong East Asian Summer Monsoon (EASM), a weak monsoon front and a northward displaced upper-tropospheric westerly jet. EOT2 and EOT4 extreme precipitation are related to an enhanced and stable monsoon front and a strong western North Pacific subtropical high (WNPSH). The WNPSH associated with EOT4 is stronger than that associated with EOT2, which pushes the monsoon front further north. EOT3 represents extreme precipitation that is related to anomalous southerlies around the western ridge of the WNPSH. The southerlies transport warm and moist air to southern China and increase precipitation there. The four key regions and the related mechanisms are not sensitive to the EOT technique, as the EOT-based extreme precipitation patterns and circulation anomalies are confirmed using Self-Organising Maps (SOMs).

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Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/102468
Item Type Article
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher Springer
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