The TRMM multisatellite precipitation analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales
The TRMM multisatellite precipitation analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales
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DOI：
10.1175/jhm560.1
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发表时间：
2007-02-01
影响因子：
3.8
通讯作者：
Wolff, David B.
中科院分区：
文献类型：
--
作者：
Huffman, George J.;Adler, Robert F.;Wolff, David B.
热带降雨测量使命任务多卫星降水分析提供了一种基于校准的顺序方案，用于在精细尺度（0.25度x0.25度和每3小时）上将多颗卫星的降水估计值以及在可行的情况下的测量分析结合起来。根据TRMM组合仪器和TRMM微波成像仪降水产品分别进行的校准，TMPA可在之后和真实的时间内使用。目前只有实时后产品包含仪表数据。该数据集涵盖了从1998年至今的北纬50度的纬度带。早期验证结果如下：TMPA在月尺度上提供了合理的性能，尽管由于对海洋上空的低降水率缺乏敏感性，它被证明具有依赖于降水率的低偏差[基于高级微波探测单元-B（AMSU-B）]。在更精细的尺度上，TMPA成功地近似再现了基于地面观测的降水直方图，并合理地检测到大型日活动。然而，与其他细标度估计器一样，TMPA在短时间间隔内正确指定中度和轻度事件数量方面的技能较低。提供了洪水事件和日周期确定的示例。
The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) provides a calibration-based sequential scheme for combining precipitation estimates from multiple satellites, as well as gauge analyses where feasible, at fine scales (0.25 degrees x 0.25 degrees and 3 hourly). TMPA is available both after and in real time, based on calibration by the TRMM Combined Instrument and TRMM Microwave Imager precipitation products, respectively. Only the after-real-time product incorporates gauge data at the present. The dataset covers the latitude band 50 degrees N-S for the period from 1998 to the delayed present. Early validation results are as follows: the TMPA provides reasonable performance at monthly scales, although it is shown to have precipitation rate-dependent low bias due to lack of sensitivity to low precipitation rates over ocean in one of the input products [ based on Advanced Microwave Sounding Unit-B (AMSU-B)]. At finer scales the TMPA is successful at approximately reproducing the surface observation-based histogram of precipitation, as well as reasonably detecting large daily events. The TMPA, however, has lower skill in correctly specifying moderate and light event amounts on short time intervals, in common with other finescale estimators. Examples are provided of a flood event and diurnal cycle determination.