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In this study, 10 min and 2 km high-resolution blended fog data (HRBFD) were generated using grid visibility data (GVD) and data from a GK2A (GEO-KOMPSAT-2A) fog product (GKFP) in Korea. As the blending method, the decision tree method (DTM) was used to consider the different characteristics of the two-input data (categorical data and continuity data). The blending of the two datasets was performed according to the presence or absence of the input data and considered the spatial representation of the GVD and the accuracy of the GKFP. The quality of the HRBFD was evaluated through visual comparison using GVD, GKFP, and visible images of the GK2A. The HRBFD seems to have partly solved the problem of fog detection in areas where visibility meters are rare or absent through the detection of fog occurring in the sea or mountain areas. In addition, the critical problem of the GKFP, which has limitations in detecting fog occurring under clouds, has been mostly overcome. Using the DTM, we generated 23 fog cases of 10 min and 2 km HRBFD. The results confirmed that detailed spatiotemporal characteristics of fog in Korea can be analyzed if such HRBFD is generated for a long time. [ABSTRACT FROM AUTHOR]

Rice production in the Korean Peninsula (KP) in the near future (2021–2050) is analysed in terms of the climatic yield potential (CYP) index for Japonica‐type rice. Data obtained from the dynamically downscaled daily temperature and sunshine duration for the Historical period (1981–2010) and near future under two Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios are utilized. To reduce uncertainties that might be induced by using a Coupled General Circulation Model (CGCM)—a Regional Climate Model (RCM) chain in dynamical downscaling, two CGCM—three RCM chains are used to estimate the CYP index. The results show that the mean rice production decreases, mainly due to the increase of the temperature during the grain‐filling period (40 days after the heading date). According to multi model ensemble, the optimum heading date in the near future will be approximately 12 days later and the maximum CYP will be even higher than in the Historical. This implies that the rice production is projected to decrease if the heading date is selected based on the optimum heading date of Historical, but to increase if based on that of near future. The mean rice production during the period of ripening is projected to decrease (to about 95% (RCP4.5) and 93% (RCP8.5) of the Historical) in the western and southern regions of the KP, but to increase (to about 104% (RCP4.5) and 106% (RCP8.5) of the Historical) in the northeastern coastal regions of the KP. However, if the optimum heading date is selected in the near future climate, the peak rice production is projected to increase (to about 105% (RCP4.5) and 104% (RCP8.5) of the Historical) in the western, southern and northeastern coastal regions of the KP, but to decrease (to about 98% (RCP4.5) and 96% (RCP8.5) of the Historical) in the southeastern coastal regions of the KP. [ABSTRACT FROM AUTHOR]

The evaluation of climate model performance is necessary to enhance the reliability of available models. Recently, the interest in the added value has been increasing due to the continued enhancement of the horizontal model resolution for dynamical downscaling. We have examined the simulation performance of regional climate models (RCMs) forced by two global climate models (GCMs) for summer precipitation over Far East Asia and South Korea on the basis of spatial resolution improvement. In terms of model resolution, coarse‐resolution RCMs present limitations, whilst high‐resolution RCMs offer the added value as revealed by several performance evaluations. RCMs forced by HadGEM2‐AO estimated smaller summer precipitation over South Korea than those observed, whereas RCMs forced by MPI‐ESM‐LR presented a wet bias. Here, moderate‐heavy rain in RCMs forced by HadGEM2‐AO and light‐moderate rain in RCMs forced by MPI‐ESM‐LR were found to lead to dry and wet biases, respectively. [ABSTRACT FROM AUTHOR]