Identification of multiple climatic extremes in metropolis: a comparison of Guangzhou and Shenzhen, China

Yanxu Liu (), Shuangshuang Li, Yanglin Wang (), Tian Zhang, Jian Peng and Tianyi Li

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2015, vol. 79, issue 2, 939-953

Abstract: Identifying historical trends in the integrated frequencies of various climate extremes is meaningful in climatic hazard research. However, the variation trends in regional climate extremes still need to be described by more effective indices, correlations among multiple climatic extremes and different regions need to be quantified, and the urban heat island backgrounds and thermal bioclimate conditions in which people live need to be noted. In this study, the threats of heat wave, heavy rain, strong wind, and Universal Thermal Climate Index (UTCI) stress were identified both by units of days using the 90th percentile threshold, and by an unscaled magnitude index derived from kernel density functions for Guangzhou and Shenzhen, China, in 1960–2013. The results show that both metropolises experienced an increase in heat wave threat and a decrease in strong wind threat, and the change amplitudes were higher for Guangzhou than Shenzhen. The correlation of heat wave threat between the two metropolises was significant, while the other correlations depended on the city and index. The heat wave threat was correlated with the UTCI stress in Guangzhou, while both heat wave threat and UTCI stress were correlated with strong wind threat in Shenzhen. The UTCI stress indicated that bioclimate conditions for human habitat have not deteriorated, especially in Shenzhen. In the daily-level results, the heat waves had close relationship between the two adjacent cities, and people suffered from hazard events were usually in high weighted indices of extremes. Copyright Springer Science+Business Media Dordrecht 2015

Keywords: Multiple climatic extremes; Heat wave; Heavy rain; Strong wind; UTCI; Cumulative density function; Urbanization in China (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s11069-015-1885-5

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