In:
Hydrology and Earth System Sciences, Copernicus GmbH, Vol. 22, No. 6 ( 2018-06-27), p. 3435-3452
Abstract:
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 35 km, depending on the spatial
distribution, rather than intensity, of precipitation, whereas the
e-folding time ranges from 1 to 2 h. 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 (∼ 100 km), 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.
Type of Medium:
Online Resource
ISSN:
1607-7938
DOI:
10.5194/hess-22-3435-2018
Language:
English
Publisher:
Copernicus GmbH
Publication Date:
2018
detail.hit.zdb_id:
2100610-6
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