中文摘要：

本文比较了三种卫星遥感资料和三层嵌套WRF模式预报降水在舟曲泥石流事件前后相对观测降水的准确度、误差等。结果表明,卫星遥感资料能从降水分布型、降水量值等方面反映出实际的降水特征,尤其是CMORPH和TRMM,更是基本接近实际降水的情况。PERSIANN资料虽然有相对大一些的误差,但区域降水总量、降水区分布型以及最大降水的时空再现已经比较精确。数值预报降水对区域总降水以及降水的分布形态能比较好的预报,高分辨率的模式甚至能较好地预报降水极值的时间和位置,因此在灾害预警方面有较高的应用价值。

英文摘要：

The data of several rainfall products, including those estimated from satellite measurements and those forecasted via numerical weather modeling, for a severe debris-flow event in Zhouqu, Northwest China, are compared and analyzed in this paper. The satellite products, including CPC MORPHing technique（CMORPH）, TMPA-RT, and PERSIANN are all near-real-time retrieved with high temporal and spatial resolutions. The numerical weather model used in this paper for precipitation forecasting is WRF. The results show that all three satellite products can basically reproduce the rainfall pattern, distribution, timing, scale, and extreme values of the event, compared with gauge data. Their temporal and spatial correlation coefficients with gauge data are as high as about 0.6, which is statistically significant at 0.01 level. The performance of the forecasted results modeled with different spatial resolutions are not as good as the satellite-estimated results, although their correlation coefficients are still statistically significant at 0.05 level. From the total rainfall and extreme value time series for the domain, it is clear that, from the grid-to-grid perspective, the passive microwave-based CMORPH and TRMM products are more accurate than the infrared-based PERSIANN, while PERSIANN performs very well from the general point of view, especially when considering the whole domain or the whole convective precipitation system. The forecasted data — especially the highest resolution model domain data — are able to represent the total or mean precipitation very well in the research domain, while for extreme values the errors are large. This study suggests that satellite-retrieved and model-forecasted rainfall data are a useful complement to gauge data, especially for areas without gauge stations and areas not covered by weather radars.