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http://dx.doi.org/10.5389/KSAE.2021.63.6.049

Application of Bias-Correction and Stochastic Analogue Method (BCSA) to Statistically Downscale Daily Precipitation over South Korea  

Hwang, Syewoon (Department of Agricultural Engineering (Institute of Agriculture and Life Science), Gyeongsang National University)
Jung, Imgook (Dept. of Prediction Research, APEC Climate Center)
Kim, Siho (Department of Agricultural Engineering, Gyeongsang National University)
Cho, Jaepil (Convergence Laboratory for Watershed Management, Integrated Watershed Management Institute)
Publication Information
Journal of The Korean Society of Agricultural Engineers / v.63, no.6, 2021 , pp. 49-60 More about this Journal
Abstract
BCSA (Bias-Correction and Stochastic Analog) is a statistical downscaling technique designed to effectively correct the systematic errors of GCM (General Circulation Model) output and reproduce basic statistics and spatial variability of the observed precipitation filed. In this study, the applicability of BCSA was evaluated using the ASOS observation data over South Korea, which belongs to the monsoon climatic zone with large spatial variability of rainfall and different rainfall characteristics. The results presented the reproducibility of temporal and spatial variability of daily precipitation in various manners. As a result of comparing the spatial correlation with the observation data, it was found that the reproducibility of various climate indices including the average spatial correlation (variability) of rainfall events in South Korea was superior to the raw GCM output. In addition, the needs of future related studies to improve BCSA, such as supplementing algorithms to reduce calculation time, enhancing reproducibility of temporal rainfall patterns, and evaluating applicability to other meteorological factors, were pointed out. The results of this study can be used as the logical background for applying BCSA for reproducing spatial details of the rainfall characteristic over the Korean Peninsula.
Keywords
BCSA; statistical downscaling; GCM output; variability of precipitation;
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Times Cited By KSCI : 2  (Citation Analysis)
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