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Statistical modeling and CMIP5 simulations of hot spell changes in China

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Abstract

A hot spell is an extreme weather event with one or more consecutive days with daily maximum temperature exceeding a certain threshold of high temperature. Statistical modeling of summer hot spells in China during 1960–2005 and their simulations in the historical experiment of the Coupled Model Intercomparison Project Phase 5 (CMIP5) are investigated in this study. A technique called the hot spell model (HSM), introduced by Furrer et al. (Clim Res 43:191–205, 2010) for modeling hot spells by extending the point process approach to extreme value theory, is applied. Specifically, the frequency of summer hot spells is modeled by a Poisson distribution, their intensity is modeled by a generalized Pareto distribution, and their duration is modeled by a geometric distribution. Results show that the HSM permits realistic modeling of summer hot spells in China. Trends in the frequency, duration, and intensity of hot spells were estimated based on the HSM for the observed period from 1960 to 2005. Furthermore, the performance in simulating hot spell characteristics and trends from the CMIP5 historical run were assessed based on the HSM. Climate models with good performance were selected to conduct an ensemble projection of hot spell intensity, frequency, and duration and their trends in future decades.

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Acknowledgments

This study is supported by the National Nature Science Foundation of China Grant 41175079 and 41376025, the Macao Meteorological and Geophysical Bureau (SMG) Project 9231048, and the Strategic Priority Research Program of the Chinese Academy of Sciences Grant XDA11010403. Y. Li was supported by CSIRO Climate Adaptation Flagship. This work was initiated when the first author visited CSIRO in his PhD study leave during 1 October–30 November 2011, supported by Chow Yei Ching School of Graduate Studies, City University of Hong Kong.

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Authors and Affiliations

  1. Guy Carpenter Asia-Pacific Climate Impact Centre, School of Energy and Environment, City University of Hong Kong, Hong Kong, 00852, China

    Weiwen Wang & Wen Zhou

  2. CSIRO Computational Informatics, Wembley, WA, 6913, Australia

    Yun Li

  3. State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China

    Xin Wang & Dongxiao Wang

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  1. Weiwen Wang
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Correspondence to Wen Zhou.

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Wang, W., Zhou, W., Li, Y. et al. Statistical modeling and CMIP5 simulations of hot spell changes in China. Clim Dyn 44, 2859–2872 (2015). https://doi.org/10.1007/s00382-014-2287-1

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