Influence of Spatially Varying Bias Adjustment on the accuracy of Radar Rainfall

Abstract

The bias correction factor is an essential value for improving the accuracy of radar rainfall assessment. This factor is acknowledged to be used for reducing the radar rainfall estimation errors contained in the process of the Z-R conversion (the relationship between radar reflectivity (Z) and rain rate (R)). However, various bias adjustment techniques are depending upon the complexity of the analysis. To be useful for selecting the suitable technique, this study aims to study the influence of applying the spatial and temporal varying bias correction techniques on the accuracy of radar rainfall estimates compared with using the mean field bias correction technique (MFB). Two methods of spatial interpolation comprising the Inverse Distance Weighted Interpolation (IDW) and Ordinary Kriging Interpolation (OK) were applied to estimate the gridded bias adjustment factor of radar rainfall. Radar reflectivity data at the Sattahip station and gauge rainfall data from 297 automatic rain gauges in 2013 were used in the study. The results appeared that coupling the spatially varying bias correction technique with the Z-R conversion significantly produce the enhancement of radar rainfall estimates compared with the use of the conventional mean field bias technique. Therefore, it is appropriate to apply the spatial bias correction techniques associated with the rainfall behavior of the study area to further increase the efficiency of water resources development of the country.