Abstract
Although there have been significant technological advances in radar technology in terms of electronics and computation, the impacts of overall radar-rainfall uncertainty, its factors, and the methods of its evaluation have not been presented clearly. Hence, this study estimated the radar rainfall for each radar-rainfall estimation algorithm (R(ZH), R(ZH, ZDR), R(JPL) using data from the Biseulsan Rainfall Radar System (dual-polarization radar), which was first introduced in Korea. Then, this study compared the result with ground observation rainfall using radar performance statistical indicators and analyzed them. According to the result, the R(ZH, ZDR) algorithm sensitively reacted to the bias of differential refletivity (ZDR), an observation variable, which caused large variation in instrumental observation errors. When the composite algorithm (R(JPL) was applied, most of the radar performance statistical indicators were improved, which demonstrated the effectiveness of the estimation variable from the dual-polarization radar. However, it was also found that it is necessary to develop algorithms and variable test methods suitable for the observation characteristics of Korean rainfall radars. In addition, the results of study were compared with those of previous studies in the United States and then reviewed to assess the level of Korean technology for uncertainty of rainfall data from the radar. The results showed a large spatial variability in data from the Korean radar in comparison to the results from the previous U.S. studies; there was also an improvement in the uncertainty of the radar-rainfall estimation. Therefore, the results of this study can be important for establishing the evaluation criteria regarding the uncertainty of radar-rainfall estimation and for contributing to the improvement in the uncertainty of radar-rainfall estimation. Keywords: Quantitative Radar-rainfall Estimation, Radar-rainfall Uncertainties, Radar Technical Level
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More From: Journal of the Korean Society of Hazard Mitigation
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