Open AccessEquiratio cumulative distribution function matching as an improvement to the equidistant approach in bias correction of precipitation
Author(s) -
Wang Lin,
Chen Wen
Publication year - 2013
Publication title -
atmospheric science letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.951
H-Index - 45
ISSN - 1530-261X
DOI - 10.1002/asl2.454
Subject(s) - equidistant , matching (statistics) , cumulative distribution function , precipitation , robustness (evolution) , computer science , function (biology) , statistics , mathematics , probability density function , meteorology , physics , chemistry , geometry , biochemistry , evolutionary biology , biology , gene
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 ( CMIP5 ) confirms the effectiveness and robustness of equiratio CDF 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.