Characterising Daily Precipitation Concentration and Interannual Variability in China

ABSTRACT Heavy precipitation events can have catastrophic socioeconomic impacts. Daily distribution of annual precipitation amount is strongly linked to potentially disastrous events—both floods and droughts. Hence, investigating the spatial and temporal characteristics of daily precipitation concentration is of great importance. Here we analysed the concentration index (CI), an indicator that measures the concentration of daily precipitation in a year, and the corresponding percentages of annual precipitation in the 25% rainiest days (hereafter called P‐25%) each year from 1960 to 2016 at 602 weather stations across China. Based on the scatter plots of CI and P‐25%, we delineated three contiguous zones across the country. The consistency between CI and P‐25% is improved within each zone, compared to being evaluated across different zones. We further identified high CI areas in each zone and found the areas of high CI values were shrinking in all zones during 1960–2016. The Mann–Kendall time tendency tests of CI and annual max 1‐day precipitation (Rx1day) reveal that extreme precipitation occurs in more concentrated areas in the southeast part of China. Additionally, the coefficient of variation (CV) in CI and P‐25% shows their inter‐annual variation is less strong in the southern humid regions than in the northwest arid regions. The spatial extent and temporal variation of such areas with high precipitation concentration provide a new perspective for improving preparedness for heavy rain‐caused natural disasters such as floods and debris flows.

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Publication Details

Journal
International Journal of Climatology
Published
2025-03-16
DOI
https://doi.org/10.1002/joc.8826
Citations
1
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.11

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article

Characterising Daily Precipitation Concentration and Interannual Variability in China

Hongbo Zhang, Sadia Bibi, Tingju Zhu, A. Sankarasubramanian et al.
1 citations
International Journal of Climatology
Climate variability and models
1.11
article

Characterising Daily Precipitation Concentration and Interannual Variability in China

Hongbo Zhang, Sadia Bibi, Tingju Zhu, A. Sankarasubramanian, Ci Li
article en
1 citations

Abstract

ABSTRACT Heavy precipitation events can have catastrophic socioeconomic impacts. Daily distribution of annual precipitation amount is strongly linked to potentially disastrous events—both floods and droughts. Hence, investigating the spatial and temporal characteristics of daily precipitation concentration is of great importance. Here we analysed the concentration index (CI), an indicator that measures the concentration of daily precipitation in a year, and the corresponding percentages of annual precipitation in the 25% rainiest days (hereafter called P‐25%) each year from 1960 to 2016 at 602 weather stations across China. Based on the scatter plots of CI and P‐25%, we delineated three contiguous zones across the country. The consistency between CI and P‐25% is improved within each zone, compared to being evaluated across different zones. We further identified high CI areas in each zone and found the areas of high CI values were shrinking in all zones during 1960–2016. The Mann–Kendall time tendency tests of CI and annual max 1‐day precipitation (Rx1day) reveal that extreme precipitation occurs in more concentrated areas in the southeast part of China. Additionally, the coefficient of variation (CV) in CI and P‐25% shows their inter‐annual variation is less strong in the southern humid regions than in the northwest arid regions. The spatial extent and temporal variation of such areas with high precipitation concentration provide a new perspective for improving preparedness for heavy rain‐caused natural disasters such as floods and debris flows.

International Journal of ClimatologyVol. 45(7)
Zhejiang International Studies University (CN), North Carolina State University (US), University of Illinois Urbana-Champaign (US), Chang'an University (CN), Zhejiang University-University of Edinburgh Institute (CN), Zhejiang University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 26%
Climate variability and models
1.11
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