两种基于雷达的临近预报算法在赣江流域的应用

将多尺度雷达回波跟踪(MTREC:Muti-scale Tracking radar echoes by correlation)算法和基于降水栅格数据的网格追踪临近预报外推(PBN:Pixel-Based Nowcasting)算法应用在赣江流域,对这两种临近预报算法在1~3 h预见期的临近预报降水数据进行评估,总结两种临近预报算法在赣江流域的预报性能和预报特点。结果表明:(1)随着预见期的增加,MTREC方法的预报性能变化较为平缓。PBN方法的预报性能明显变差。(2)MTREC方法预报降水偏弱,且对于低值降水预报较为准确,而PBN方法预报降水偏强,且预报高值降水较为准确。(3)MTREC方法预报的降水高值区的范围偏小而低值降水区范围偏大,PBN方法预报的高值降水区的范围偏大而低值降水区范围偏小。(4)随着预见期的增加,MTREC方法的降水概率预报变化较为平稳,而PBN方法预报高值降水(0.4 mm·h~(-1))的概率偏高,预报低值降水(0.4 mm·h~(-1))的概率偏低。

Application of two radar-based nowcasting methods over Ganjiang River basin

The Muti-scale Tracking Radar Echoes by Cross-correlation scheme (MTREC) and Pixel-Based Nowcasting algorithm (PBN) are selected and applied over Ganjiang River basin in this study. The nowcasting precipitation for 1-3 h leading time by the two methods were evaluated to summarize the nowcasting abilities and characteristics of the two nowcasting methods. Results indicate that:(1) with the leading time increasing, the variation of the forecasting abilities of the MTREC method is gentle, while the PBN method is getting worse. (2)The precipitation magnitude forecasted by the MTREC method is smaller than RQPE, and the low precipitation forecasted by the MTREC method is closer to RQPE; the PBN method is on the contrary. (3) The precipitation area forecasted by the MTREC method is smaller than RQPE, and the low precipitation area forecasted by the MTREC method is closer to RQPE; the PBN is on the contrary. (4) As the leading time increasing, the changing for Probability Distribution Function (PDF) of precipitation forecasted by the MTREC method is stable and matches well with the PDF of RQPE, while the PDF of the precipitation (>0.4 mm/h) forecasted by the PBN method is larger than that of RQPE and the PDF of the precipitation (<0.4 mm/h) forecasted by the PBN method is smaller than that of RQPE.