文献类型： 外文期刊

第一作者： Rui, X. P.

作者： Rui, X. P.;Rui, X. P.;Qu, X. K.;Fan, Y. L.;Yu, X. T.;Lei, Q. L.

作者机构：

关键词： G/R ratio; calibration factors; parameters estimate; state system; adaptive estimation

期刊名称：APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH （ 影响因子：0.711； 五年影响因子：0.796 ）

ISSN： 1589-1623

年卷期： 2019 年 17 卷 1 期

页码：

收录情况： SCI

摘要： To reduce the error of radar rainfall evaluations, an improved Kalman filter (KF) method is used to calibrate the radar quantitative rainfall estimation (QRE). First, the rain gauge rain rate/radar rain rate (G/R) calibration factor model is created in this approach. The prediction and measurement system of the G/R are then established based on the KF. The calibration process of the system parameters and the adaptive estimation process of the system error are introduced to dynamically adjust the KF parameters. Subsequently, the G/R calibration ratio is used to correct the quantitative radar rainfall estimation. The radar and rain gauge hourly rain data of two rain cases in Changchun, China on August 19-20, 2015, and August 6-7, 2016, are used to test the efficiency of the proposed method. The results show that the QRE result based on the KF calibration is better than that without calibration. The average relative errors of the two rain cases decreased from 0.6047 to 0.3557 and 0.2645 and from 0.8052 to 0.3096 and 0.1715 due to the ordinary and improved KFs, respectively. The improved KF is even better than the ordinary KF.

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