首页 | 本学科首页   官方微博 | 高级检索  
     


A comparison study of extreme precipitation from six different regional climate models via spatial hierarchical modeling
Authors:Erin M. Schliep  Daniel Cooley  Stephan R. Sain  Jennifer A. Hoeting
Affiliation:1.Department of Statistics,Colorado State University,Fort Collins,USA;2.Geophysical Statistics Project,National Center for Atmospheric Research,Boulder,USA
Abstract:We analyze output from six regional climate models (RCMs) via a spatial Bayesian hierarchical model. The primary advantage of this approach is that the statistical model naturally borrows strength across locations via a spatial model on the parameters of the generalized extreme value distribution. This is especially important in this application as the RCM output we analyze have extensive spatial coverage, but have a relatively short temporal record for characterizing extreme behavior. The hierarchical model we employ is also designed to be computationally efficient as we analyze RCM output for nearly 12000 locations. The aim of this analysis is to compare the extreme precipitation as generated by these RCMs. Our results show that, although the RCMs produce similar spatial patterns for the 100-year return level, their characterizations of extreme precipitation are quite different. Additionally, we examine the spatial behavior of the extreme value index and find differing spatial patterns for the point estimates for the RCMs. However, these differences may not be significant given the uncertainty associated with estimating this parameter.
Keywords:
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号