Analysis of precipitation extremes with the assessment of regional climate models over the Willamette River Basin, USA

摘要

An appropriate, rapid and effective response to extreme precipitation and any potential flood disaster is essential. Providing annaccurate estimate of future changes to such extreme events due to climate change are crucial for responsible decision making innflood risk management given the predictive uncertainties. The objective of this article is to provide a comparison of dynamicallyndownscaled climate models simulations from multiple model including 12 different combinations of General Circulation Modeln(GCM)–regional climate model (RCM), which offers an abundance of additional data sets. The three major aspects of this studyninclude the bias correction of RCM scenarios, the application of a newly developed performance metric and the extreme valuenanalysis of future precipitation. The dynamically downscaled data sets reveal a positive overall bias that is removed throughnquantile mapping bias correction method. The added value index was calculated to evaluate the models’ simulations. Resultsnfrom this metric reveal that not all of the RCMs outperform their host GCMs in terms of correlation skill. Extreme value theorynwas applied to both historic, 1980–1998, and future, 2038–2069, daily data sets to provide estimates of changes to 2- and 25-yearnreturn level precipitation events. The generalized Pareto distribution was used for this purpose. The Willamette River basin wasnselected as the study region for analysis because of its topographical variability and tendency for significant precipitation. Thenextreme value analysis results showed significant differences between model runs for both historical and future periods withnconsiderable spatial variability in precipitation extremes. Copyright © 2012 John Wiley & Sons, Ltd.