Spatiotemporal analysis of consecutive extreme wet days in China from 1980 to 2020

Author:

Zong Xuezheng12ORCID,Yin Yunhe1,Cui Tong3,Hou Wenjuan1,Deng Haoyu1

Affiliation:

1. Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences Beijing China

2. University of Chinese Academy of Sciences Beijing China

3. National Climate Center China Meteorological Administration Beijing China

Abstract

AbstractConsecutive extreme wet days (CEWDs) typically affect the likelihood of flooding and landslides and have negative effects on both natural and artificial ecosystems; however, the spatiotemporal changes in their features are still unclear at the national scale. Investigating changes in the frequency and intensity of such events is essential for climate risk management. Here, this study thoroughly analysed CEWD features in China from 1980 to 2020 using the daily observation dataset. We also evaluated and compared the ability of two widely used precipitation products, the European Centre for Medium‐Range Weather Forecasts Reanalysis 5th Generation (ERA5) and the Multi‐Source Weighted‐Ensemble Precipitation version 2 (MSWEP), to detect CEWD features. According to the observation data, the frequency and intensity of CEWD events are related to local climate and present “high eastern and low western” spatial patterns across China. Since 1980, more than half of China's mainland has experienced increases in both the frequency and intensity of CEWDs. Some stations detected decreasing trends in CEWD frequency and amounts, which are primarily located in the eastern coastal regions and southwest of warm temperate humid/subhumid regions. The ERA5 precipitation product generally outperforms MSWEP data in detecting CEWD events, and the latter significantly underestimates the annual frequency and amounts of CEWDs. These findings provide basic and valuable information regarding CEWD features across China and where such studies can be conducted based on precipitation datasets. Furthermore, these findings will also aid policymakers in managing extreme precipitation‐related natural hazards.

Publisher

Wiley

Subject

Atmospheric Science

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