Statistical Bias Correction: Comparison of Methods from Heavy Rainfall Perspective

  • Shibuo Yoshihiro
    Institute of Engineering Innovation, School of Engineering, University of Tokyo
  • Kanae Shinjiro
    Graduate School of Information Science and Engineering, Tokyo Institute of Technology

Bibliographic Information

Other Title
  • 統計的バイアス補正:大雨による手法比較

Description

Removing biases from climate models' output so far has been considered to be a part of downscaling processes. However, from application's perspective, it is the biases rather than spatial resolution gap that one has to maneuver when applying climate model's forcings. There has been several bias correction techniques emerged, yet there is very limited studies showing how these techniques are different and how the difference itself would affect the application results. In this study, we apply popular bias correction methods to regional climate model's daily precipitation over Japan, and show their differences by comparing occurrence intervals of a heavy rainfall event.

Journal

Details 詳細情報について

  • CRID
    1390282680690329216
  • NII Article ID
    130004628123
  • DOI
    10.11520/jshwr.23.0.40.0
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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