The purposes of this study were to classify detailed climate types over the Republic of Korea (ROK) and to delineate their climate characteristics using the new normals of 1991-2020 for 219 weather stations. Total five climate types, Cfa, Cfb, Cwa, Dwa, and Dwb were identified in ROK based on the Köppen’s climate classification criteria. Subtropical climate types, Cfa or Cwa types were broadly covered with 79.9% of 219 stations and the most of remaining stations were included in Dwa types which had a very cold winter and hot summer with wet conditions. In the Trewartha classification, four climate types were identified, one subtropical Cfa, and three temperate Doa, Dca, and Dcb types. Dcb types were found at four stations (Daegwallyeong, Taebaek, Jinburyeong, and Sabuk) in Taebak mountains indicating the extent of cool summer climate types with more stations in mountain areas. The climate characteristics by climate types only were presented the results from the Trewartha classification with the new normals and 66 ASOS stations because Köppen’s climate classification was not appropriate for ROK. The annual mean precipitation of Cfa was the greatest while Dcb the lowest among four types. The annual range was the greatest at Dca types while the smallest at Cfa due to the geographical varieties. More detailed climate types were located in ROK with 219 weather stations and the new normals (1991-2020). However, there were some limitation applying the criteria of Köppen’s and Trewartha’s climate classification to a very complex topographical region.

This paper has presented not only the spatial coverage change of climate extreme events in summer and winter seasons during the period of 2000-2017, but also their future projections in 2021-2100, South Korea through analysis of a Combined Climate Extreme Index (CCEI). The CCEI quantifies the spatial coverage of climate extreme events based on a set of five indicators. MK (Modified Korean)-PRISM (Parameter-elevation Regression on Independent Slopes Model)v1.2 (1×1km) and RCP scenario data (1×1km) were applied to CCEI. Results indicated that in average, 21.7% of the areas in the summer and 23.6% in the winter experienced climate extremes from 2000 to 2017 regardless of types of climate extreme events in South Korea. The summer of 2003 and 2009 was relatively cool and humid, while the summer of 2014 and 2015 was cool and dry and the summer of 2016 was warm and dry. The extreme events with much above normal maximum and minimum temperature during the study period were detected but not much below normal maximum and minimum temperature after 2015. For RCP2.6 and RCP8.5 scenarios, there were statistically significant trends with spatial coverage expansion of climate extreme events in the future. It might be concluded that climate extreme events in the summer and winter seasons were affected simultaneously by two or more indicators than a single indicator in South Korea.

In this study, we analyzed the characteristics of climate variability in summer rainfall during Changma over three sub-sector regions (Middle, Southern, Jeju) in South Korea for the new climatological period of 1991- 2020 using observation data from 60 ASOS stations. There was a significant interannual variability in rainfall, wet days, and rainfall intensity but the long-term trend of rainfall was not significant over the three sectors in South Korea. Comparing the new climatology (P2: 1991-2020) with the old one (P1: 1981-2010), it was found that the precipitation during Changma in new climatology (P2) was enhanced in Middle sector but reduced in Southern and Jeju sectors. In P2, wet days increased only a few stations in the Middle sector but the rainfall intensity was strengthened over the 50% stations including Middle sector, south and west coast of the Southern sector. Wet days above 25, 50, 75, 95%ile rainfall during Changma in Southern and Jeju sectors all decreased in P2. Climatological change from P1 to P2 showed a large variability not only in temporal frame but also in the spatial distribution in South Korea.

Cell based grid data of future temperature and precipitation produced with four RCP scenarios were converted into polygon based data for administrative districts using three simple vectorizing methods; (1) KMA Dong-Nae forecast point based, (2) areal ratio based and (3) central point based methods. The results were compared the existed KMA areal weight based methods to identify which methods were more efficient than others. Simple statistical methods such descriptive statistics, correlation coefficient, and Bland & Altman plots (B&A) were used to compare agreements between them. When central point and areal ratio based methods were applied to administrative districts of Eup-Myeon-Dong or some Gus, NULLs were found because their sizes are smaller than the cell of 1x1 km. Therefore, KMA Dong-Nae forecast point based methods were better when sizes of administrative districts are smaller than the cell size. For Do and Metropolitan cities, there were no greater differences among methods except for the KMA Dong- Nae forecast points. The greater the areas of administrative districts the more distortions from the KMA Dong-Nae forecast points because only KMA Dong-Nae forecast one point were used for the calculation. In conclusion, the KMA Dong-Nae forecast point based method was appropriate when sizes of administrative districts are smaller than the grid cell. For the greater areal sizes such as Do and Metropolitan cities, areal ratio and central point based methods were better.

This paper has identified detailed climate types and their geographical extents in the Republic of Korea using MK (Modified Korean)-PRISM (Parameter-elevation Regression on Independent Slopes Model) 1×1km high-resolution grid climate data and Trewartha climate classification. When considering 60 ASOS (The Automated Synoptic Observing Systems) stations, only four climate types were identified over South Korea. Three climate types, Dca (52%), Doa (28%) and Cfa (18%), were prevalent while Dcb type was only located at Daegwallyeong. When based on a high-resolution grid climate data, six climate types were identified including Dob and E types which were not detected with ASOS stations. High-resolution grid climate data reflected better and detailed geographical characteristics. Areas occupied by Cfa climate types were located along the narrow southern and Jeju coastal areas, dedicating only 6.9% of South Korea. Trewartha climate classification was also applied to 1km×1km RCP scenarios. The most distinct feature of future climate changes based on RCPs was a larger expansion of Cfa and Doa types with a drastic reduction of Dca and Dcb, indicating that a warmer and wetter climate would be prevalent over South Korea in the latter period of this century. Even for RCP2.6, all the coastal areas, some of Seoul metropolitan area, a large part of Daegu and Gwangju metropolitan areas would be classified as Cfa. For RCP8.5, 51.5% of South Korea would be occupied by the Cfas and 25.1% by the Doas, leaving only 23.2% of Dcas.