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. Among the meteorological disasters, heavy rainfalls cause the second largestdamage in Korea, following typhoons. To manage the potential disastersdue to heavy rainfalls, understanding the observational characteristics ofprecipitation is of utmost importance. In this study, we investigate thespatial and temporal characteristics of warm-season precipitation in Korea,according to the precipitation types, by conducting the geostatisticalanalyses such as an autocorrelogram, Moran's  I and general  G on thecomposite (radar  +  station) precipitation data. The e -folding distanceof precipitation ranges from 15 to 35 km, depending on the spatialdistribution, rather than intensity, of precipitation, whereas the e -folding time ranges from 1 to 2 h. The directional analyses revealedthat the warm-season precipitation systems in Korea, especially those witha high precipitation amount, have high spatial autocorrelations in thesouthwest–northeast and west–east directions, in association with thefrontal rainfalls, convection bands, etc. Furthermore, the cluster versusdispersion patterns and the hot versus cold spots are analyzed throughMoran's  I and general  G , respectively. Water vapor, represented by thebrightness temperature, from three Himawari-8 water vapor bands also showssimilar characteristics with precipitation but with strong spatialcorrelation over a much longer distance ( ∼  100 km), possibly due to thecontinuity of water vapor. We found that, under the e -folding-basedstandard, the current observation network of Korea is sufficient to capturethe characteristics of most precipitation systems; however, under a strictstandard (e.g., autocorrelation of 0.6), a higher-resolution observationnetwork is essentially required – especially in local areas with frequentheavy rainfalls – depending on the directional features of precipitationsystems. Establishing such an observation network based on thecharacteristics of precipitation enables us to improvemonitoring, tracking, and prediction skills of high-impact weather phenomena aswell as to enhance the utilization of numerical weather prediction.

Geostatistical assessment of warm-season precipitation observations in Korea based on the composite precipitation and satellite water vapor data