Comparison of spatial interpolation techniques for predicting climate factors in Korea

Abstract

A variety of statistical interpolation techniques have been used with climate factors. This study compared three statistical interpolation techniques such as PRISM, Kriging, and IDW with temperature and precipitation. Mean monthly cumulative values on temperature and precipitation from 1977 to 2006, which were provided by Korea Meteorological Administration, were used for this study. The aim of this study is to find better appropriate process which can consider to the topographical characteristics of Korea and to produce high‐resolution climate‐maps using statistical models. As a result, Kriging showed gradual and smooth pattern, while IDW showed rather irregularly distributed with discontinuous borders. And PRISM generated the most detailed pattern. This paper will contribute to coping with climate‐change such as urban heat island, flood, disaster, and to make alterative suggestion for the meteorological factors on forest and vegetation models in the future.