Editorial Type:
Article
Article Type:
Research Article

Probability Distribution of Precipitation Extremes for Weather Index–Based Insurance in the Zhujiang River Basin, South China

Thomas Fischer National Climate Center, China Meteorological Administration, Beijing, China, and Department of Geosciences, University of Tübingen, Tübingen, Germany

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Buda Su National Climate Center, China Meteorological Administration, Beijing, China

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Yong Luo National Climate Center, China Meteorological Administration, Beijing, China

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Thomas Scholten Department of Geosciences, University of Tübingen, Tübingen, Germany

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Print Publication:
01 Jun 2012
DOI:
https://doi.org/10.1175/JHM-D-11-041.1
Page(s):
1023–1037
Restricted access

Abstract

In a changing climate, understanding the frequency of weather extremes is crucial to improving the management of the associated risks. The concept of weather index–based insurance is introduced as a new approach in weather risk adaptation. It can decrease the vulnerability to precipitation extremes that cause floods and economic losses in the Zhujiang River basin. The probability of precipitation extremes is a key input and the probability distribution of annual precipitation extremes is analyzed with four distribution functions [gamma 3, generalized extreme value (GEV), generalized Pareto, and Wakeby]. Three goodness-of-fit tests (Kolmogorov–Smirnov, Anderson–Darling, and Chi Squared) are applied to the distribution functions for annual time series (1961–2007) of 192 meteorological stations. The results show that maximum precipitation and 5-day-maximum precipitation are best described by the Wakeby distribution. On a basin scale, the GEV is the most reliable and robust distribution for estimating precipitation indexes for an index-based insurance program in the Zhujiang River basin. However, each station has to be analyzed individually as GEV is not always the best-fitting distribution function. Based on the distribution functions, spatiotemporal characteristics of return periods for maximum precipitation and 5-day-maximum precipitation are determined. The return levels of the 25- and 50-yr return periods show similar spatial pattern: they are higher in the southeast and lower in the southwest of the basin. This spatial distribution is in line with the annual averages. The statistical distribution of precipitation indexes delivers important information for a theoretical weather index–based insurance program.

Corresponding author address: Thomas Fischer, China Meteorological Administration (CMA), National Climate Centre (NCC) 46, Zhongguancun Nandajie, Haidian, Beijing 100 081, China. E-mail: tom.fischer8@gmx.de

Abstract

In a changing climate, understanding the frequency of weather extremes is crucial to improving the management of the associated risks. The concept of weather index–based insurance is introduced as a new approach in weather risk adaptation. It can decrease the vulnerability to precipitation extremes that cause floods and economic losses in the Zhujiang River basin. The probability of precipitation extremes is a key input and the probability distribution of annual precipitation extremes is analyzed with four distribution functions [gamma 3, generalized extreme value (GEV), generalized Pareto, and Wakeby]. Three goodness-of-fit tests (Kolmogorov–Smirnov, Anderson–Darling, and Chi Squared) are applied to the distribution functions for annual time series (1961–2007) of 192 meteorological stations. The results show that maximum precipitation and 5-day-maximum precipitation are best described by the Wakeby distribution. On a basin scale, the GEV is the most reliable and robust distribution for estimating precipitation indexes for an index-based insurance program in the Zhujiang River basin. However, each station has to be analyzed individually as GEV is not always the best-fitting distribution function. Based on the distribution functions, spatiotemporal characteristics of return periods for maximum precipitation and 5-day-maximum precipitation are determined. The return levels of the 25- and 50-yr return periods show similar spatial pattern: they are higher in the southeast and lower in the southwest of the basin. This spatial distribution is in line with the annual averages. The statistical distribution of precipitation indexes delivers important information for a theoretical weather index–based insurance program.

Corresponding author address: Thomas Fischer, China Meteorological Administration (CMA), National Climate Centre (NCC) 46, Zhongguancun Nandajie, Haidian, Beijing 100 081, China. E-mail: tom.fischer8@gmx.de
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