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http://dx.doi.org/10.14191/Atmos.2022.32.4.277

Evaluation of Heat Waves Predictability of Korean Integrated Model  

Jung, Jiyoung (Korea Institute of Atmospheric Prediction Systems)
Lee, Eun-Hee (Korea Institute of Atmospheric Prediction Systems)
Park, Hye-Jin (Korea Institute of Atmospheric Prediction Systems)
Publication Information
Atmosphere / v.32, no.4, 2022 , pp. 277-295 More about this Journal
Abstract
The global weather prediction model, Korean Integrated Model (KIM), has been in operation since April 2020 by the Korea Meteorological Administration. This study assessed the performance of heat waves (HWs) in Korea in 2020. Case experiments during 2018-2020 were conducted to support the reliability of assessment, and the factors which affect predictability of the HWs were analyzed. Simulated expansion and retreat of the Tibetan High and North Pacific High during the 2020 HW had a good agreement with the analysis. However, the model showed significant cold biases in the maximum surface temperature. It was found that the temperature bias was highly related to underestimation of downward shortwave radiation at surface, which was linked to cloudiness. KIM tended to overestimate nighttime clouds that delayed the dissipation of cloud in the morning, which affected the shortage of downward solar radiation. The vertical profiles of temperature and moisture showed that cold bias and trapped moisture in the lower atmosphere produce favorable conditions for cloud formation over the Yellow Sea, which affected overestimation of cloud in downwind land. Sensitivity test was performed to reduce model bias, which was done by modulating moisture mixing parameter in the boundary layer scheme. Results indicated that the daytime temperature errors were reduced by increase in surface solar irradiance with enhanced cloud dissipation. This study suggested that not only the synoptic features but also the accuracy of low-level temperature and moisture condition played an important role in predicting the maximum temperature during the HWs in medium-range forecasts.
Keywords
Heat wave; Korean Integrated Model; Cold bias of surface temperature; Moisture bias in the lower atmosphere; Low level cloud;
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