Comparison of Regional Climate Model Performances for Different Types of Heat Waves over South Korea

Abstract

South Korea’s heat wave events over 39 years (1980–2018) were defined by spatiotemporal criteria, and their quantitative characteristics were analyzed. The duration and intensity of these events ranked the highest in 2016 and 2018. An examination of synoptic conditions of heat wave events in 2016 and 2018 based on a reanalysis dataset revealed a positive anomaly of 500-hPa geopotential height, which could have induced warm conditions over the Korean Peninsula in both years. However, a difference prevailed in that there was a blocking high over the Kamchatka Peninsula and a continental thermal high over northern China in 2016, while the expansion of the western North Pacific subtropical-high was mainly associated with 2018 heat wave events. Numerical experiments using the Weather Research and Forecasting model (WRF) were conducted to (1) evaluate how distinct meteorological characteristics of heat wave events in 2016 and 2018 were reproduced by the model, and (2) investigate how they affect extreme temperature events. Typical synoptic features of the 2016 heat wave events (i.e., Kamchatka blocking and continental thermal high) were not captured well by the WRF model, while those of 2018 were reasonably reproduced. On the contrary, the heat wave event during late-August 2016 related to the Kamchatka blocking high was realistically simulated when the blocking was artificially persisted by applying the spectral nudging. In conclusion, the existence of a blocking high over the Kamchatka region (i.e., northern Pacific region) is an important feature to accurately predict long-lasted heat waves in East Asia.

Role of Land–Atmosphere Interaction in the 2016 Northeast Asia Heat Wave: Impact of Soil Moisture Initialization

“…Next, atmospheric conditions simulated from the numerical experiments using the WRF model were spatially assessed by comparing to the FNL analysis field and HadISD in‐situ station data (Figure 4). During the simulation period, Northeast Asia experienced severe heat waves with an anomalous mid‐level anticyclone that covered the region from Mongolia to the Korean Peninsula (Li et al., 2022; Yeh et al., 2018; Yoon et al., 2021). The daily mean observed SAT at several stations in southern Mongolia, eastern China, and South Korea exceeded 28°C (Figure 4a).…”

“…Recently, East Asia has experienced record‐breaking heat waves, such as those in 2016 and 2018 (Deng et al., 2019; Min et al., 2020; Ren et al., 2020; Yeh et al., 2018; Yoon et al., 2021). According to the Korean Meteorological Administration and the Korea Centers for Disease Control and Prevention, 2,125 and 4,526 cases of heat‐related diseases were reported in 2016 and 2018 in South Korea due to extreme heat wave for 22 and 31 days, respectively (Yoon et al., 2021). Li et al.…”

“…The recent increase in severe heat waves is a crucial indicator of global warming and has caused considerable socioeconomic damage (Azhar et al., 2014; Coumou et al., 2013; Knowlton et al., 2009; Meehl & Tebaldi, 2004; Poumadere et al., 2005). Recently, East Asia has experienced record‐breaking heat waves, such as those in 2016 and 2018 (Deng et al., 2019; Min et al., 2020; Ren et al., 2020; Yeh et al., 2018; Yoon et al., 2021). According to the Korean Meteorological Administration and the Korea Centers for Disease Control and Prevention, 2,125 and 4,526 cases of heat‐related diseases were reported in 2016 and 2018 in South Korea due to extreme heat wave for 22 and 31 days, respectively (Yoon et al., 2021).…”

Development of model output statistics based on the least absolute shrinkage and selection operator regression for forecasting next‐day maximum temperature in South Korea

“…In terms of the NWP, various studies have found that a high‐resolution regional model mainly produces a more accurate temperature by taking into account the small‐scale features (Prömmel et al ., 2010; Di Luca et al ., 2013; Lee and Hong, 2014; Yoon et al ., 2021). However, the results from this study suggest that random errors of surface air temperature may not be removed in a fine‐resolution model, although the total errors are reduced, and it is challenging to eliminate those random errors using the advanced regression method.…”

The Role of the Pacific‐Japan Pattern in Extreme Heatwaves Over Korea and Japan

“…This process was advanced as a probable cause for the dangerous heatwaves in 2018 (Hsu et al., 2020; Shimpo et al., 2019). In addition, local sea surface temperature anomaly (Hasegawa et al., 2020; Wie et al., 2021) and midlatitude blocking (Yeh et al., 2018; Yoon et al., 2021) are known contributors to the heatwaves, although the latter can be considered as a part of the meridional waves.…”