Abstract
Precipitation extremes are expected to increase in a warming climate, which may have serious societal impacts. This study uses two initial condition ensembles conducted with the Community Earth System Model (CESM) to investigate potential changes in extreme precipitation under two climate change scenarios over the contiguous United States. We fit non-stationary generalized extreme value (GEV) models to annual maximum daily precipitation simulated from a 30-member ensemble under the RCP8.5 scenario and a 15-member ensemble under the RCP4.5 scenario. We then compare impacts using the 1 % annual exceedance probability (AEP) level, which is the amount of daily rainfall with only a 1 % chance of being exceeded in a given year. Under RCP8.5 between 2005 and 2080, the 1 % AEP level is projected to increase by 17 % on average across the U.S., and up to 36 % for some grid cells. Compared to RCP8.5 in the year 2080, RCP4.5 is projected to reduce the 1 % AEP level by 7 % on average, with reductions as large as 18 % for some grid cells. We also investigate a pattern scaling approach in which we produce predictive GEV distributions of annual precipitation maxima under RCP4.5 given only global mean temperatures for this scenario. We compare results from this less computationally intensive method to those obtained from our GEV model fitted directly to the CESM RCP4.5 output and find that pattern scaling produces reasonable projections.
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