Short time precipitation estimation using weather radar and surface observations: With rainfall displacement information integrated in a stochastic manner

Abstract

Rain gauges are the foundation in hydrology to collect rainfall data, however gauge observations alone are limited at representing the complete rainfall distribution. On the other hand, weather radar can provide a nearly complete spatial distribution of rainfall qualitatively at high temporal and spatial resolution, yet concerns about the biases in the precipitation estimates hamper the direct use of radar data in hydrological applications. Thus the focus of this study is to derive a scheme to merge radar precipitation estimates and the contemporaneous point-wise rain gauge observations. It is common practice to construct radar-gauge pairs by assuming the vertical and instant falling of the hydrometeors from aloft onto the ground. On many occasions, the assumption is invalid, as it ignores a significant fact that the hydrometeors are very likely to be laterally advected in the air by the wind while descending, especially from a large height and/or with the existence of snow. The laterally displacement of rainfall will result in a great discrepancy of radar and gauge data. Concerning these issues, a method to quantify the displacement of rainfall is proposed and the results of the quantification are integrated into much improved surface precipitation estimates.