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ATOVS data assimilation in two different heavy rainfalls

机译:在两个不同的强降雨中的ATOVS数据同化

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Based on T213-SSI assimilation system, using ATOVS data from NOAA16, 17, an assimilation experiment was done. Three schemes was used to simulate two cases — the Sichuan and Chongqing heavy rainfall and the Huaihe Basin heavy rainfall. Comparing the different assimilation results draw a conclusion below: Assimilated ATOVS data by T213-SSI system is very useful in heavy rainfall forecasting. By continued assimilation, satellite data can improve Large-scale synoptic situation and the precipitation forecast, especially precipitation intensity. T213-SSI assimilation and forecast system showed more accurate in Huaihe basin than in Sichuan and Chongqing area on heavy rainfall forecast. After assimilation, all weather elements showed a greater improvement in Sichuan and Chongqing area than another. Different area, different rainfall systems need different data assimilation schemes to get a better result. In Huaihe basin, close to the sea, the heavy rainfall caused by frontogenesis with the high-level trough should be removed surface and low level channels data of the AMSU-A in assimilation. Sichuan and Chongqing has a complex terrain, and Qinghai-Tibet Plateau is lack of conventional observation data. So AMSU-A data which include surface and low level channels should be assimilated.
机译:基于T213-SSI同化系统,利用来自NOAA16、17的ATOVS数据,进行了同化实验。三种方案被用来模拟两种情况-四川和重庆的强降雨和淮河流域的强降雨。比较不同的同化结果得出以下结论:T213-SSI系统的同化ATOVS数据在强降雨预报中非常有用。通过持续同化,卫星数据可以改善大尺度天气状况和降水预报,特别是降水强度。 T213-SSI同化和预报系统在强降雨预报方面比在四川和重庆地区更准确。经过同化后,四川和重庆地区的所有天气要素均显示出较大的改善。不同的地区,不同的降雨系统需要不同的数据同化方案,以获得更好的结果。在靠近海的淮河流域,应将同化中AMSU-A的地面和低层通道数据清除掉,因为前生是由高位槽造成的。四川和重庆地势复杂,青藏高原缺乏常规观测资料。因此,应该吸收包括表面和低水平通道的AMSU-A数据。

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