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상세화 기법을 통한 한반도 공간 강우장 분석 KCI 등재

Analysis of Spatial Precipitation Field Using Downscaling on the Korean Peninsula

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한국수자원학회 논문집 (Journal of Korea Water Resources Association)
한국수자원학회 (Korea Water Resources Association)
초록

강우는수문순환에서중요한요소중에하나로시·공간적변동성이크므로정확한공간강우장의파악이요구된다. 열대강우 관측 위성(Tropical Rainfall Monitoring Mission, TRMM)에서 제공하는 3B43 월 누적 강우량 자료는 25 km의 공간해상도를 갖고 있어 공간 강우장의 정확성을 높이기 위해 상세화 기법을 적용하여 1km의 공간 해상도로 생성하였다.Terra 위성에 탑재된 MODIS (Moderate Resolution Imaging Spectroradiometers) 센서가 제공하는 정규식생지수(Normalized Difference Vegetation Index, NDVI) (공간해상도1km)와강우자료의관계성을회귀식으로나타냈고상세화기법에 적용하였다. 이에 따른 결과를 지점과 위성 강우 자료와의 차이를 통해 보정하는 방법인 GDA (Geographical Difference Analysis)와 지점과 위성 강우 자료와의 비율로 편차를 보정하는 GRA (Geographical Ratio Analysis) 상세화기법을사용하여공간강우장을나타내었다. 우리나라의공간강우장결과를지점자료를기준으로비교검증을실시하였다.그결과GDA 상세화기법의경우가2009년(Bias=4.26mm, RMSE=172.16 mm, MAE=141.95 mm, IOA=0.64), 2011년(Bias=17.21 mm, RMSE=253.43 mm, MAE=310.56 mm, IOA=0.62)으로가장잘맞는것으로나타났다. 이를바탕으로우리나라의공간 강우장을 1 km의 공간 해상도로 파악할 수 있었으며, 더 나아가 지점의 수를 늘려 보정을 정밀하게 하거나, 강우레이더 자료를 가지고 상세화 기법을 적용한다면 더욱 정확한 공간 강우장을 파악할 수 있을 것이다.

Precipitation is one of the important factors in the hydrological cycle. It needs to understand accurate of spatial precipitation field because it has large spatio-temporal variability. Precipitation data obtained through the Tropical Rainfall Monitoring Mission (TRMM) 3B43 product is inaccurate because it has 25 km space scale. Downscaling of TRMM 3B43 product can increase the accuracy of spatial precipitation field from 25 km to 1km scale. The relationship between precipitation and the normalized difference vegetation index(NDVI) (1 km space scale) which is obtained from the Moderate Resolution Imaging Spectroradio- meters (MODIS) sensor loaded in Terra satellite is variable at different scales. Therefore regression equations were established and these equations apply to downscaling. Two renormalization strategies, Geographical Difference Analysis (GDA) and Geographical Ratio Analysis (GRA) are implemented for correcting the dif- ferences between remote sensing-derived and rain gauge data. As for considering the GDA method results, biases, the root mean-squared error (RMSE), MAE and Index of agreement (IOA) is equal to 4.26 mm, 172.16 mm, 141.95 mm, 0.64 in 2009 and 17.21 mm, 253.43 mm, 310.56 mm, 0.62 in 2011. In this study, we can see the 1km spatial precipitation field map over Korea. It will be possible to get more accurate spatial analysis of the precipitation field through using the additional rain gauges or radar data.

저자
  • 조혜린(Graduate Student Department of Civil and Environmental Engineering, Hanyang University) | Cho, Herin
  • 황석환(Water Resources Research Division, Korea Institute of Construction Technology) | Hwang, Seokhwan
  • 조용식(Professor, Department of Civil and Environmental Engineering, Hanyang University) | Cho, Yongsik
  • 최민하(Assistant Professor, Department of Civil and Environmental Engineering, Hanyang University) | Choi, Minha Corresponding Author