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Statistics of extremes in climatology

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  • T.A. Buishand

Abstract

Climatology is an area with many applications of extreme–value theory. In applications to climatic data it is necessary to consider the distribution ol extremes for dependent random variables and to make allowance for non–stationarity (seasonal variation). It is shown that also for such data the classical limiting distributions for normalized maxima of independent and identically distributed random variables remain useful candidates to describe the distribution of the largest value in a year. Parameter estimation of extreme–value distributions is briefly reviewed. Attention is paid to variance–reduction of quantile estimates by making use of more observations than just the annual maxima. Three examples of applications deal with topics like the estimation of large quantiles by combining information from several records in a region, shifts in the distribution of maxima due to changes in measurement practices, and the use of covariates.

Suggested Citation

  • T.A. Buishand, 1989. "Statistics of extremes in climatology," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 43(1), pages 1-30, March.
    • Handle: RePEc:bla:stanee:v:43:y:1989:i:1:p:1-30
    DOI: 10.1111/j.1467-9574.1989.tb01244.x
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    Cited by:

    1. Myeong-Ho Yeo & Van-Thanh-Van Nguyen & Yong Sang Kim & Theodore A. Kpodonu, 2022. "An Integrated Extreme Rainfall Modeling Tool (SDExtreme) for Climate Change Impacts and Adaptation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3153-3179, July.
    2. Muhammad Uzair Qamar & Muhammad Azmat & Muhammad Adnan Shahid & Daniele Ganora & Shakil Ahmad & Muhammad Jehanzeb Masud Cheema & Muhammad Abrar Faiz & Abid Sarwar & Muhammad Shafeeque & Muhammad Imran, 2017. "Rainfall Extremes: a Novel Modeling Approach for Regionalization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(6), pages 1975-1994, April.
    3. Dutfoy Anne & Parey Sylvie & Roche Nicolas, 2014. "Multivariate Extreme Value Theory - A Tutorial with Applications to Hydrology and Meteorology," Dependence Modeling, De Gruyter, vol. 2(1), pages 1-19, June.
    4. van Noortwijk, J.M. & van der Weide, J.A.M. & Kallen, M.J. & Pandey, M.D., 2007. "Gamma processes and peaks-over-threshold distributions for time-dependent reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(12), pages 1651-1658.

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