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.

Persistent Extreme Temperature Events (PETEs) are defined in two steps; first, to define extreme temperature events, the 80th and 20th percentiles of daily maximum and minimum temperature were chosen. Then individual PETE was defined as an event which lasted three or longer consecutive extreme temperature days. In this study, we examined characteristics and changes of PETEs in Republic of Korea (ROK) using 14 weather stations with a relatively long-term period of data, 1954-2016. In ROK, PETEs lasted four-five days on average and occurred two-three times a year. PETEs lasted longer in summer than in winter and in maximum temperature than in minimum temperature. PETEs which lasted greater than seven days account for a greater proportion in summer than in winter. However, intensities of PETEs were greater in winter because of a larger temperature fluctuation. In both summer and winter, durations and intensities of persistent extreme high temperature events increased while those of persistent extreme low temperature events decreased. Changes of PETEs were closely related with both global warming and diverse large-scale climate variabilities such as AO, NAO and Nino 3.4.

In this study, we analyzed the characteristics of summer extreme rainfall over South Korea and their relationships with the synoptic and large-scale circulation anomalies during 1979-2014. Heavy rainfall (R90p) is related with the strong convection surrounded by dry zone over Korean peninsula and the moist air delivered from the convection area over Bay of Bengal-South China Sea-Philippine Sea. The upper-level anticyclonic flow with the low-level dipole of anticyclonic circulation in the Southeast and cyclonic circulation to the northwest of Korean peninsula are the main characteristics when the extreme rainfall occurs. The barotropic Rossby wave developed over the Korean peninsula transfers its energy farther downstream to the western coast of North America. It is also found that the dominant lowfrequency oscillation over the tropics (intraseasonal oscillation) play an important background role for the enhancement of extreme rainfall over South Korea.