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http://dx.doi.org/10.14191/Atmos.2018.28.4.479

Predictability of Temperature over South Korea in PNU CGCM and WRF Hindcast  

Ahn, Joong-Bae (Division of Earth Environmental System, Pusan National University)
Shim, Kyo-Moon (National Academy of Agricultural Science, RDA)
Jung, Myung-Pyo (National Academy of Agricultural Science, RDA)
Jeong, Ha-Gyu (Division of Earth Environmental System, Pusan National University)
Kim, Young-Hyun (Division of Earth Environmental System, Pusan National University)
Kim, Eung-Sup (Division of Earth Environmental System, Pusan National University)
Publication Information
Atmosphere / v.28, no.4, 2018 , pp. 479-490 More about this Journal
Abstract
This study assesses the prediction skill of regional scale model for the mean temperature anomaly over South Korea produced by Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF) chain. The initial and boundary conditions of WRF are derived from PNU CGCM. The hindcast period is 11 years from 2007 to 2017. The model's prediction skill of mean temperature anomaly is evaluated in terms of the temporal correlation coefficient (TCC), root mean square error (RMSE) and skill scores which are Heidke skill score (HSS), hit rate (HR), false alarm rate (FAR). The predictions of WRF and PNU CGCM are overall similar to observation (OBS). However, TCC of WRF with OBS is higher than that of PNU CGCM and the variation of mean temperature is more comparable to OBS than that of PNU CGCM. The prediction skill of WRF is higher in March and April but lower in October to December. HSS is as high as above 0.25 and HR (FAR) is as high (low) as above (below) 0.35 in 2-month lead time. According to the spatial distribution of HSS, predictability is not concentrated in a specific region but homogeneously spread throughout the whole region of South Korea.
Keywords
PNU CGCM; WRF; dynamical downscaling; hindcast; prediction skill;
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