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Evaluation of the ability of regional climate models and a statistical model to represent the spatial characteristics of extreme precipitation
Author(s) -
Yang Lichao,
Franzke Christian L. E.,
Fu Zuntao
Publication year - 2020
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.6602
Subject(s) - climatology , precipitation , environmental science , climate model , flood myth , spatial ecology , climate extremes , common spatial pattern , climate change , meteorology , geography , geology , statistics , mathematics , ecology , oceanography , archaeology , biology
Extreme precipitation is one of the most severe weather hazards which have a significant influence on society, agriculture and ecosystems. The spatial extension and intensity of extreme precipitation events are two important features which need to be quantified for improved flood risk and water resource management. Here, we evaluate how well regional climate models (RCMs) reproduce precipitation extremes with respect to spatial dependency and intensity. We show by using seasonal extreme intensities in Brandenburg‐Berlin, Germany, that some RCMs underestimate the spatial dependence of extremes in summer and overestimate it in winter, compared with an observational‐based data set. Most RCMs significantly underestimate the magnitudes of extremes in summer and overestimate the magnitudes in autumn and winter. A statistical model, based on a max‐stable process, accounting for both the spatial and temporal variability is developed. We show that this model performs better in representing the spatial dependency and intensity characteristics of extreme precipitation compared to the RCMs.