赣江流域TRMM降水数据的误差特征与成因

阐明TRMM 3B42V6（Tropical rainfall measuring mission 3B42 version 6）的误差特征及成因，对于合理使用该卫星降水数据，并完善其降水反演算法具有重要意义。在赣江流域0.25°×0.25°空间尺度上，对比了TRMM 3B42V6、TRMM 3B42RTV6和CMORPH的精度特征。结果表明，3B42V6的系统偏差远低于3B42RTV6、CMORPH，但平均绝对值偏差、效率系数和探测率均明显劣于CMORPH。TRMM 3B42V6的系统偏差较低的原因主要在于该数据采用地面月降水量进行了校准，而其绝对值偏差、效率系数和探测率明显劣于CMORPH的主要原因在于所采用的热红外/被动微波降水联合反演算法不及后者有效。今后有必要对TRMM 3B42的精度进行全面评估，并改进该数据的热红外/微波降水反演算法及与地面降水信息的融合算法。

Characteristics and sources of errors in daily TRMM precipitation product over Ganjiang River basin in China

In order to ensure rational utilization and to improve rainfall retrieval algorithms, it is of great significance to illustrate the characteristics and the sources of errors in the daily Tropical Rainfall Measuring Mission (TRMM) 3B42V6 precipitation product. In this study, we analyze the accuracy of three high resolution precipitation datasets at a spatial resolution of 0.25°×0.25° degrees using daily rain gauge data observed over the Ganjiang River basin. The three datasets are daily TRMM and other satellites precipitation product (3B42V6 derived), TRMM (3B42RTV6), and NOAA Climate Prediction Center Morphing Technique (CMORPH). Results show that the bias (B) of 3B42V6 is substantially less than that of 3B42RTV6 and CMORPH. However, CMORPH is more accurate than 3B42V6 as measured by other accuracy indices including the absolute bias (A_B), the Nash-Sutcliffe efficiency coefficient (C) and the probability of detection (P_D). The lower B values obtained from the TRMM 3B42V6 precipitation product are due to the fact that the rainfall monthly ground station data are used to correct the original TRMM data. However, the scheme for merging microwave and infrared (IR) precipitation information in TRMM 3B42V6 may not be as effective as the ones in 3B42RTV6 and CMORPH. As a result, the TRMM 3B42V6 precipitation product has higher A_B but lower C and P_D values compared to CMORPH. A further comprehensive assessment on the quality of daily TRMM 3B42V6 precipitation product is thus warranted to improve the performance of the scheme for merging microwave and IR precipitation information as well as the method of merging the satellite-gauge data.