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A spatiotemporal model for extreme precipitation simulated by a climate model, with an application to assessing changes in return levels over North America
Author(s) -
Jalbert Jonathan,
Favre AnneCatherine,
Bélisle Claude,
Angers JeanFrançois
Publication year - 2017
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/rssc.12212
Subject(s) - precipitation , flooding (psychology) , flood myth , climatology , environmental science , climate model , climate change , return period , statistical model , grid , meteorology , computer science , geography , geology , artificial intelligence , psychology , oceanography , archaeology , psychotherapist , geodesy
Summary Extreme precipitation plays a major role in flooding events and their occurrence and intensity are expected to increase. Because climate models are the only tools for providing quantitative projections of precipitation, flood risk management for the future climate may be based on the simulation of such events. The goal of the paper is to develop a spatiotemporal statistical model for extremes that is particularly suited to climate model outputs, which are transient and lie on a regular grid. Using the statistical model proposed, projected precipitation return levels for the coming climate over North America are estimated.