Optimal RCM and spatial interpolation methods for estimating future precipitation in the Republic of Korea

Abstract

Recent droughts and floods caused by climate change have caused considerable damage to the use of water resources. According to several climate forecasts in various Intergovernmental Panel on Climate Change (IPCC) reports, the use of stable water resources remains vulnerable and can be heavily influenced by climate change. An adequate response to the climate change threat is thus growing more important for water resources management. This study aimed to select the optimal regional climate model (RCM) and spatial interpolation method for the practical application of future estimation of precipitation data produced by climate change scenarios. The results indicate that HadGEM3-RA (Hadley Centre Global Environment Model version 3 – Regional Atmospheric) is the most suitable of the five RCMs when comparing its predicted values to the monthly precipitation forecasts of the Korea Meteorological Administration (KMA), from 2006 to 2015, in Korea. Universal kriging was chosen as the optimal interpolation method for generating accurate precipitation data, among several spatial interpolation methods. In Korea, the accuracy of precipitation prediction by the RCM is low on the coasts and islands. In comparison, the accuracy is found to be higher in the northern inland area.

Keywords

• Precipitation
• regional climate model
• climate change
• spatial interpolation method
• Précipitation
• modèle climatique régional