A spatiotemporal model for extreme precipitation simulated by a climate model, with an application to assessing changes in return levels over North America

作者：Jalbert Jonathan^*; Favre Anne Catherine; Belisle Claude; Angers Jean Francois

来源：Journal of the Royal Statistical Society - Series C: Applied Statistics , 2017, 66(5): 941-962.

DOI：10.1111/rssc.12212

• Bayesian hierarchical model
• Climate changes
• Generalized extreme value
• Markov random field
• Precipitation
• Regional climate model

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.

• 出版日期2017-11
• 单位McGill