Abstract
Spatial analysis method is one of the most common methods. This research selects an appropriate interpolation method to generate the precipitation data for the grid of mostly urban area missing South Korean detailed precipitation data according to RCP 8.5 scenario provided by Korea Meteorological Administration (KMA) and considers the applicability of 1km*1km grid precipitation date to the administrative district of Korea. To generate the precipitation data of missing area, ESRI ArcGIS was used, and an optimum interpolation method will be selected to generate the precipitation data for the missing areas according to the future climate change scenario, the used interpolation method includes Inverse Distance Weighting (IDW) method, Ordinary Kriging, Universal Kriging, and Spline methods. The most accurate value was found with the Ordinary Kriging in the calculation of suitable interpolation methods using the precipitation data of August, where the precipitation was the highest in the period of 2015 through 2019 with the RCP 8.5 scenario.
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