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http://dx.doi.org/10.7780/kjrs.2020.36.5.1.8

Downscaling GPM Precipitation Using Finer-scale MODIS Based Optical Image in Korean Peninsula  

Oh, Seungcheol (School of Civil, Architectural and Environmental System Engineering, Sungkyunkwan University)
Jeong, Jaehwan (Department of Water Resources, Sungkyunkwan University)
Lee, Seulchan (Department of Water Resources, Sungkyunkwan University)
Choi, Minha (Department of Civil Engineering, Sungkyunkwan University)
Publication Information
Korean Journal of Remote Sensing / v.36, no.5_1, 2020 , pp. 749-762 More about this Journal
Abstract
Precipitation is closely related to various hydrometeorological phenomena, such as runoff and evapotranspiration. In Korean Peninsula, observing rainfall intensity using weather radar and rain gauge network is dominating due to their accurate, intuitive and precise detecting power. However,since these methods are not suitable at ungauged regions, rainfall detection using satellite is required. Satellite-based rainfall data has coarse spatial resolution (10 km, 25 km), and has a limited range of usage due to its reliability of data. The aim of this study is to obtain finer scale precipitation. Especially, to make the applicability of satellite higher at ungauged regions, 10 km satellite-based rainfall data was downscaled to 1 km data using MODerate Resolution Imaging Spectroradiometer (MODIS) based cloud property. Downscaled precipitation was verified in urban region, which has complex topographical and environmental characteristics. Correlation coefficient was similar in summer (+0), decreased in spring (-0.08) and autumn (-0.01), and increased in winter (+0.04) season compared to Global Precipitation Measurement (GPM) based precipitation. Downscaling without calibration using in situ data could be useful in areas where rain gauge system is not sufficient or ground observations are rarely available.
Keywords
Downscaling; Precipitation; GPM; AWS; MODIS; Cloud;
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