Validation of Level 2 TRMM Rain Profile Algorithms by Intercomparison and Hypothesis Testing
AIR FORCE INST OF TECH WRIGHT-PATTERSONAFB OH SCHOOL OF ENGINEERING
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Satellite algorithms are currently the methodology showing most promise for obtaining more accurate global precipitation estimates. However, a general problem with satellite methods is that they do not measure precipitation directly, but through inversion of radiation-rain relationships. Because of this, procedures are needed to verify algorithm-generated results. The most common method of verifying satellite rain estimates is by comparison with ground truth derived from measurements obtained by raingage networks, ground weather radar, or a combination of the two. However, these types of measurements often have uncertainty magnitudes on the order or greater than the satellite algorithms, motivating the search for alternate approaches. The purpose of this research is to explore a new type of approach for validating the level 2 TRMM facility rain profile algorithms. This is done by an algorithm-to-algorithm intercomparison analysis in the context of physical hypothesis testing. Beginning with the four algorithms strengths and weaknesses garnered from the physics used to develop the algorithms, seven hypotheses were formed detailing expected performance characteristics of the algorithms. Procedures were developed to test these hypotheses and applied to 48 storms from all ocean basins within the tropical and subtropical zones over which TRMM coverage is available approx. 35N - 35S. The testing resulted in five hypotheses verified, one partially verified, and one inconclusive. These findings suggest that the four level 2 TRMM facility profile algorithms are performing in a manner consistent with the underlying physical limitations in the measurements or, alternatively, the strengths of the physical assumptions, providing an independent measure of the level 2 algorithms validity.