Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/9377
Title: Geostatistical downscaling of AMSR2 precipitation with COMS infrared observations
Authors: Park, Nowook 
Hong, Sungwook 
Kyriakidis, Phaedon 
Lee, Woojoo 
Lyu, Sangjin 
metadata.dc.contributor.other: Κυριακίδης, Φαίδων
Major Field of Science: Engineering and Technology
Field Category: Civil Engineering
Keywords: Advanced Microwave Scanning Radiometer 2;AMSR2;COMS;Geostatistical approach
Issue Date: 17-Aug-2016
Source: International Journal of Remote Sensing, 2016, vol. 37, no. 16, pp. 3858-3869
Volume: 37
Issue: 16
Start page: 3858
End page: 3869
Journal: International Journal of Remote Sensing 
Abstract: This article presents a geostatistical approach for downscaling precipitation products from passive microwave satellites with geostationary Meteorological Satellite observations. More precisely, the Advanced Microwave Scanning Radiometer 2 (AMSR2) precipitation (daily level 3 product) with 0.25° spatial resolution and the Communication, Ocean and Meteorological Satellite (COMS) infrared (IR) data with 5 km spatial resolution were used for the downscaling experiment over the Korean peninsula. Brightness temperature data observed at COMS IR 1 and water vapour channels were incorporated for downscaling via area-to-point residual Kriging with non-linear regression. The evaluation results with densely sampled Automatic Weather Station data revealed that incorporating the COMS IR observations with the AMSR2 precipitation showed similar error statistics to those of the AMSR2 precipitation because of the limitations of IR observations themselves and the inherent errors of the AMSR2 precipitation product over land. However, the area-based evaluation using information entropy indicated that incorporating the COMS observations resulted in more detailed spatial variation in the final product than direct downscaling of the AMSR2 precipitation. In addition, local precipitation patterns could be captured when there were regions with missing precipitation values in the AMSR2 product. Consequently, the downscaling result is useful for understanding the local precipitation patterns with an accuracy similar to that provided by microwave satellite observations. It is also suggested that the spatial variability in the downscaling result and errors in input low-resolution data should be considered when downscaling coarse resolution data using fine resolution auxiliary variables.
URI: https://hdl.handle.net/20.500.14279/9377
ISSN: 01431161
DOI: 10.1080/01431161.2016.1204031
Rights: ©Taylor & Francis
Type: Article
Affiliation : Inha University 
Sejong University 
Cyprus University of Technology 
Korea Meteorological Administration 
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