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Abstract:
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Quantitative precipitation estimation (QPE) plays an important role in a wide array of fields. Although meteorological radar is widely used to measure precipitation at high temporal and spatial resolution, it is well-known that radar-based rainfall estimation suffers from several types of errors. To cope with these errors, spatial interpolation methods have been commonly used to calibrate radar data in radar rainfall estimation. These methods typically focus on mean prediction, which has inherent limitations. In this study, we propose a flexible spatial quantile interpolation method to enhance radar rainfall estimation. This method allows us to incorporate the predicted quantile information into radar rainfall estimation. A real-world data set is used to illustrate the proposed method, and the result shows improvement in QPE.
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