DESIGN OF AN INVERSION-BASED PRECIPITATION PROFILE RETRIEVAL ALGORITHM USING AN EXPLICIT CLOUD MODEL FOR INITIAL GUESS MICROPHYSICS

This paper describes the design and validation of the FSU precipitatio n profile retrieval algorithm for applications with SSM/I passive micr owave measurements. The algorithm employs the principles of multifrequ ency inversion based on forward radiative transfer modeling. A Sobolev 2-stream solution to the radiative transfer equation (RTE) is used as the forward RTE model and is described herein. The method is shown to be very accurate, retaining the same degree of computational efficien cy inherent to simpler 2-stream flux models. Tests of the model agains t more detailed multistream, adding-doubling models demonstrate that t he Sobolev solution produces radiance accuracies of approximately 1%. An advantage of the Sobolev approach is that the intensity field can b e expanded in a mathematically consistent fashion, an essential featur e in applications with the off-nadir SSM/I microwave measurements. A 4 -dimensional non-hydrostatic cloud model provides the microphysical un derpinnings of the algorithm, and is used to generate the initial gues s profiles for the inversion procedure. The various stages of the algo rithm are described, as well as two different methods of computational implementation for storm-scale and global-scale applications. The pap er also summarizes a number of different rainrate validation analyses that have been carried out at the two scales, as well as examining the capabilities of the algorithm in diagnosing the vertical latent heati ng structure. The validation results represent a mixture of quantitati ve comparisons to radar and raingage datasets, and more qualitative co mparisons to the numerical modeling results of other investigators. Be cause of known uncertainties in the validation data in terms of their accuracy and representativeness, and the underlying problems with time -space matching of the comparisons, it is not yet possible to place ab solute confidence limits on the retrievals. However, taken as a whole, the rainrate validation analyses and the estimated latent heating pro files present solid evidence that the profile approach is returning cr edible rainfall estimates whose uncertainties are commensurate with th ose of current validation data.