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http://dx.doi.org/10.14191/Atmos.2022.32.4.353

Evaluation of Predictability of Global/Regional Integrated Model System (GRIMs) for the Winter Precipitation Systems over Korea  

Yeon, Sang-Hoon (Korea Institute of Atmospheric Prediction Systems)
Suh, Myoung-Suk (Kongju National University)
Lee, Juwon (TOP PLUS Academy)
Lee, Eun-Hee (Korea Institute of Atmospheric Prediction Systems)
Publication Information
Atmosphere / v.32, no.4, 2022 , pp. 353-365 More about this Journal
Abstract
This paper evaluates precipitation forecast skill of Global/Regional Integrated Model system (GRIMs) over South Korea in a boreal winter from December 2013 to February 2014. Three types of precipitation are classified based on development mechanism: 1) convection type (C type), 2) low pressure type (L type), and 3) orographic type (O type), in which their frequencies are 44.4%, 25.0%, and 30.6%, respectively. It appears that the model significantly overestimates precipitation occurrence (0.1 mm d-1) for all types of winter precipitation. Objective measured skill scores of GRIMs are comparably high for L type and O type. Except for precipitation occurrence, the model shows high predictability for L type precipitation with the most unbiased prediction. It is noted that Equitable Threat Score (ETS) is inappropriate for measuring rare events due to its high dependency on the sample size, as in the case of Critical Success Index as well. The Symmetric Extreme Dependency Score (SEDS) demonstrates less sensitivity on the number of samples. Thus, SEDS is used for the evaluation of prediction skill to supplement the limit of ETS. The evaluation via SEDS shows that the prediction skill score for L type is the highest in the range of 5.0, 10.0 mm d-1 and the score for O type is the highest in the range of 1.0, 20.0 mm d-1. C type has the lowest scores in overall range. The difference in precipitation forecast skill by precipitation type can be explained by the spatial distribution and intensity of precipitation in each representative case.
Keywords
Classification of precipitation; Verification; the Korean Peninsula; Numerical weather prediction; Winter precipitation;
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