Equiratio cumulative distribution function matching as an improvement to the equidistant approach in bias correction of precipitation

Lin Wang, Wen Chen

doi:10.1002/asl2.454

Equiratio cumulative distribution function matching as an improvement to the equidistant approach in bias correction of precipitation

DOI Web Site Web Site 被引用文献6件

Lin Wang

Center for Monsoon System Research, Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China
Wen Chen

Center for Monsoon System Research, Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China

書誌事項

公開日: 2013-07-31

権利情報

http://onlinelibrary.wiley.com/termsAndConditions#vor

DOI

10.1002/asl2.454

公開者: Wiley

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説明

<jats:title>Abstract</jats:title><jats:p><jats:bold>Equidistant cumulative distribution function (CDF) matching has been used frequently in recent studies to bias‐correct raw modeled precipitation. However, this brief discussion shows that negative precipitation will result from applying this method. A feasible alternative to avoid this problem is to use equiratio CDF matching as proposed in this study. A real‐world assessment based on Coupled Model Inter‐comparison Project 5 (<jats:styled-content style="fixed-case">CMIP5</jats:styled-content>) confirms the effectiveness and robustness of equiratio <jats:styled-content style="fixed-case">CDF</jats:styled-content> matching in systematically removing biases in modeled precipitation. Our conclusions here will require a re‐examination of the relevant literature in which equidistant CDF matching is used to bias‐correct precipitation.</jats:bold></jats:p>