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Volume 22, issue 6 | Copyright
Hydrol. Earth Syst. Sci., 22, 3435-3452, 2018
https://doi.org/10.5194/hess-22-3435-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 27 Jun 2018

Research article | 27 Jun 2018

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

Sojung Park1,3,4, Seon Ki Park1,2,3,4, Jeung Whan Lee5, and Yunho Park5 Sojung Park et al.
  • 1Department of Climate and Energy Systems Engineering, Ewha Womans University, Seoul, Republic of Korea
  • 2Department of Environmental Science and Engineering, Ewha Womans University, Seoul, Republic of Korea
  • 3Severe Storm Research Center, Ewha Womans University, Seoul, Republic of Korea
  • 4Center for Climate/Environment Change Prediction Research, Ewha Womans University, Seoul, Republic of Korea
  • 5Korea Meteorological Administration, Seoul, Republic of Korea

Abstract. Among the meteorological disasters, heavy rainfalls cause the second largest damage in Korea, following typhoons. To manage the potential disasters due to heavy rainfalls, understanding the observational characteristics of precipitation is of utmost importance. In this study, we investigate the spatial and temporal characteristics of warm-season precipitation in Korea, according to the precipitation types, by conducting the geostatistical analyses such as an autocorrelogram, Moran's I and general G on the composite (radar+station) precipitation data. The e-folding distance of precipitation ranges from 15 to 35km, depending on the spatial distribution, rather than intensity, of precipitation, whereas the e-folding time ranges from 1 to 2h. The directional analyses revealed that the warm-season precipitation systems in Korea, especially those with a high precipitation amount, have high spatial autocorrelations in the southwest–northeast and west–east directions, in association with the frontal rainfalls, convection bands, etc. Furthermore, the cluster versus dispersion patterns and the hot versus cold spots are analyzed through Moran's I and general G, respectively. Water vapor, represented by the brightness temperature, from three Himawari-8 water vapor bands also shows similar characteristics with precipitation but with strong spatial correlation over a much longer distance (∼100km), possibly due to the continuity of water vapor. We found that, under the e-folding-based standard, the current observation network of Korea is sufficient to capture the characteristics of most precipitation systems; however, under a strict standard (e.g., autocorrelation of 0.6), a higher-resolution observation network is essentially required – especially in local areas with frequent heavy rainfalls – depending on the directional features of precipitation systems. Establishing such an observation network based on the characteristics of precipitation enables us to improve monitoring, tracking, and prediction skills of high-impact weather phenomena as well as to enhance the utilization of numerical weather prediction.

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Understanding the precipitation characteristics is essential to design an optimal observation network. We studied the spatial and temporal characteristics of summertime precipitation systems in Korea via geostatistical analyses on the ground-based precipitation and satellite water vapor data. We found that, under a strict standard, an observation network with higher resolution is required in local areas with frequent heavy rainfalls, depending on directional features of precipitation systems.
Understanding the precipitation characteristics is essential to design an optimal observation...
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