4.4 Article

Comparisons of instantaneous TRMM ground validation and satellite rain-rate estimates at different spatial scales

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JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY
卷 47, 期 8, 页码 2215-2237

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AMER METEOROLOGICAL SOC
DOI: 10.1175/2008JAMC1875.1

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  1. NASA [NNG07EJ50C]

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This study provides a comprehensive intercomparison of instantaneous rain rates observed by the two rain sensors aboard the Tropical Rainfall Measuring Mission (TRMM) satellite with ground data from two regional sites established for long-term ground validation: Kwajalein Atoll and Melbourne, Florida. The satellite rain algorithms utilize remote observations of precipitation collected by the TRMM Microwave Imager (TMI) and the Precipitation Radar ( PR) aboard the TRMM satellite. Three standard level II rain products are generated from operational applications of the TMI, PR, and combined (COM) rain algorithms using rain information collected from the TMI and the PR along the orbital track of the TRMM satellite. In the first part of the study, 0.5 degrees x 0.5 degrees instantaneous rain rates obtained from the TRMM 3G68 product were analyzed and compared to instantaneous Ground Validation (GV) program rain rates gridded at a scale of 0.5 degrees x 0.5 degrees. In the second part of the study, TMI, PR, COM, and GV rain rates were spatiotemporally matched and averaged at the scale of the TMI footprint (similar to 150 km(2)). This study covered a 6-yr period (1999-2004) and consisted of over 50 000 footprints for each GV site. In the first analysis, the results showed that all of the respective rain-rate estimates agree well, with some exceptions. The more salient differences were associated with heavy rain events in which one or more of the algorithms failed to properly retrieve these extreme events. Also, it appears that there is a preferred mode of precipitation for TMI rain rates at or near 2 mm h(-1) over the ocean. This mode was noted over ocean areas of Kwajalein and Melbourne and has been observed in TRMM tropical-global ocean areas as well.

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