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Statistical Bias Correction: Comparison of Methods from Heavy Rainfall Perspective
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- Shibuo Yoshihiro
- Institute of Engineering Innovation, School of Engineering, University of Tokyo
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- Kanae Shinjiro
- Graduate School of Information Science and Engineering, Tokyo Institute of Technology
Bibliographic Information
- Other Title
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- 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
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- Proceeding of Annual Conference
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Proceeding of Annual Conference 23 (0), 40-40, 2010
THE JAPAN SOCIETY OF HYDROLOGY AND WATER RESOURCES
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Details 詳細情報について
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- CRID
- 1390282680690329216
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- NII Article ID
- 130004628123
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- Text Lang
- ja
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed