A Bayesian approach to microwave precipitation profile retrieval

Theoretical studies using Bayes theorem help develop a multichannel passive microwave precipitation remote sensing algorithm that retrieves hydrometeor profiles. Maximization of the posterior probability density for each vector of observations helps retrieve hydrometeor profiles. Application of this algorithm reveals that hydrometeor profiles retrieved for land have higher error than those of water. This method retrieves integrated hydrometeor contents more efficiently than profiles. Errors associated with the method and future improvements are discussed.