THE TRMM DAY-1 RADAR RADIOMETER COMBINED RAIN-PROFILING ALGORITHM/

The Tropical Rainfall Measuring Mission (TRMM)'s 'day-1' combined rada r/radiometer algorithm uses a rain-profiling approach which gives as m uch importance to the measurements of the TRMM satellite's precipitati on radar (PR) and the TRMM microwave imager (TMI) as their respective intrinsic ambiguities warrant, which avoids any ad hoc shortcuts that might introduce large biases in the rain estimates, yet which is simpl e enough to be operational when TRMM is launched in 1997. The algorith m is based on the idea of estimating the rain profile using the radar reflectivities, while constraining this inversion to be consistent wit h the radiometer-derived estimate of the total attenuation. To perform the data fusion, the problem is expressed in terms of drop-size-distr ibution variables. Starting with an a priori probability density funct ion (pdf) for these variables, a Bayesian approach is used to conditio n the pdf successively on the radar and the radiometer measurements. T he resulting algorithm is mathematically consistent and physically rea sonable. The conditional variances which it calculates serve to quanti fy the accuracy of its estimates: small variances indicate that the TR MM observations can indeed be explained by the models used; large vari ances imply that the models are not sufficiently consistent with tile measurements.