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Statistical Modelling of Recent Changes in Extreme Rainfall in Taiwan

  • Lan-Fen Chu

    (National Science and Technology Center for Disaster Taiwan)

  • Michael McAleer

    (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam.)

  • Szu-Hua Wang

    (Department of Urban Affairs and Environmental Planning Chinese Cultural University Taiwan.)

This paper has two primary purposes. First, we fit the annual maximum daily rainfall data for 6 rainfall stations, both with stationary and non-stationary generalized extreme value (GEV) distributions for the periods 1911-2010 and 1960-2010 in Taiwan, and detect the changes between the two phases for extreme rainfall. The non-stationary model means that the location parameter in the GEV distribution is a linear function of time to detect temporal trends in maximum rainfall. Second, we compute the future behavior of stationary models for the return levels of 10, 20, 50 and 100-years based on the period 1960-2010. In addition, the 95% confidence intervals of the return levels are provided. This is the first investigation to use generalized extreme value distributions to model extreme rainfall in Taiwan.

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File URL: http://eprints.ucm.es/17573/1/1229.pdf
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Paper provided by Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico in its series Documentos de Trabajo del ICAE with number 2012-29.

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Length: 12 pages
Date of creation: 2012
Date of revision:
Handle: RePEc:ucm:doicae:1229
Note: For financial support, the first and third authors are most grateful to the Taiwan Climate Change Projection and Information Platform Project (NSC 100-2621-M-492-001), and the second author wishes to acknowledge the Australian Research Council, National Science Council, Taiwan, and the Japan Society for the Promotion of Science.
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  1. Demetris Koutsoyiannis & George Baloutsos, 2000. "Analysis of a Long Record of Annual Maximum Rainfall in Athens, Greece, and Design Rainfall Inferences," Natural Hazards, International Society for the Prevention and Mitigation of Natural Hazards, vol. 22(1), pages 29-48, July.
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