An extreme rainfall event in summer 2018 of Hami city in eastern Xinjiang, China

Zou Shan, Duan Wei-Li, Nikolaos Christidis, Daniel Nover, Abuduwaili Jilili, Philippe De Maeyer, Tim Van De Voorde

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Extreme rainfall events are rare in inland arid regions, but have exhibited an increasing trend in recent years, causing many casualties and substantial socioeconomic losses. A series of heavy rains that began on July 31st, 2018, battered the Hami prefecture of eastern Xinjiang, China for four days. These rains sparked devastating floods, caused 20 deaths, eight missing, and the evacuation of about 5500 people. This study examines the extreme rainfall event in a historical context and explores the anthropogenic causes based on analysis of multiple datasets (i.e., the observed daily data, the global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5), the NCEP/NCAR Reanalysis 1, and the satellite cloud data) and several statistical techniques. Results show that this extraordinarily heavy rainfall was due mainly to the abnormal weather system (e.g., the abnormal subtropical high) that transported abundant water vapor from the Indian Ocean and the East China Sea crossed the high mountains and formed extreme rainfall in Hami prefecture, causing the reservoir to break and form a flood event with treat loss, which is a typical example of a comprehensive analysis of the extreme rainfall event in summer in Northwest China. Also, the fraction of attributable risk (FAR) value was 1.00 when the 2018 July–August RX1day (11.52 mm) was marked as the threshold, supporting the claim of a significant anthropogenic influence on the risk of this extreme rainfall. The results offer insights into the variability of precipitation extremes in arid areas contributing to better manage water-related disasters.
Originele taal-2English
Pagina's (van-tot)795-803
Aantal pagina's9
TijdschriftAdvances in Climate Change Research
Volume12
Nummer van het tijdschrift6
DOI's
StatusPublished - dec 2021

Bibliografische nota

Funding Information:
Extreme rainfall events are rare in inland arid regions, but have exhibited an increasing trend in recent years, causing many casualties and substantial socioeconomic losses. A series of heavy rains that began on July 31st, 2018, battered the Hami prefecture of eastern Xinjiang, China for four days. These rains sparked devastating floods, caused 20 deaths, eight missing, and the evacuation of about 5500 people. This study examines the extreme rainfall event in a historical context and explores the anthropogenic causes based on analysis of multiple datasets (i.e., the observed daily data, the global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5), the NCEP/NCAR Reanalysis 1, and the satellite cloud data) and several statistical techniques. Results show that this extraordinarily heavy rainfall was due mainly to the abnormal weather system (e.g., the abnormal subtropical high) that transported abundant water vapor from the Indian Ocean and the East China Sea crossed the high mountains and formed extreme rainfall in Hami prefecture, causing the reservoir to break and form a flood event with treat loss, which is a typical example of a comprehensive analysis of the extreme rainfall event in summer in Northwest China. Also, the fraction of attributable risk (FAR) value was 1.00 when the 2018 July–August RX1day (11.52 mm) was marked as the threshold, supporting the claim of a significant anthropogenic influence on the risk of this extreme rainfall. The results offer insights into the variability of precipitation extremes in arid areas contributing to better manage water-related disasters.This study was sponsored by the Project of Tianshan Innovation Team in Xinjiang (202113050) and the Chinese Academy of Sciences President's International Fellowship Initiative (2017VCA0002). Nikolaos CHRISTIDIS was supported by the Met Office Hadley Centre Climate Programme funded by Department for Business, Energy and Industrial Strategy and Department for Environment, Food and Rural Affairs. We acknowledged the World Climate Research Programme's Working Group on Coupled Modeling for providing CMIP5 data, and the NOAA/OAR/ESRL PSD, for offering NCEP Reanalysis data. We also acknowledge Prof. Jianli Ding for offering useful suggestions to improve the manuscript.

Funding Information:
This study was sponsored by the Project of Tianshan Innovation Team in Xinjiang ( 202113050 ) and the Chinese Academy of Sciences President's International Fellowship Initiative ( 2017VCA0002 ). Nikolaos CHRISTIDIS was supported by the Met Office Hadley Centre Climate Programme funded by Department for Business, Energy and Industrial Strategy and Department for Environment, Food and Rural Affairs . We acknowledged the World Climate Research Programme's Working Group on Coupled Modeling for providing CMIP5 data, and the NOAA/OAR/ESRL PSD, for offering NCEP Reanalysis data. We also acknowledge Prof. Jianli Ding for offering useful suggestions to improve the manuscript.

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© 2021 The Authors

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Copyright 2021 Elsevier B.V., All rights reserved.

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