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Veljko Petković, Marko Orescanin, Pierre Kirstetter, Christian Kummerow, and Ralph Ferraro

supplement to PMW observations. It is therefore important to assess if convective/stratiform information can be inferred from the passive microwave information itself. Yet, despite sustained, decades-long effort to identify a robust link between PMW observations and convective fraction, only a few regression methods with modest skill are available. These methods largely utilize the spatial variability of the brightness temperature (Tb) of the high-frequency channels (e.g., 30 GHz and above). Thus, the

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F. Joseph Turk, Z. S. Haddad, and Y. You

simulations should cover the full range of the variability in the underlying atmospheric and surface conditions, with sufficient skill to represent the multichannel TB that would have been measured by actual MW radiometer observations. Once created for each sensor in the GPM constellation, the observational “database” with its associated TB is available offline as the a priori knowledge for probabilistic, Bayesian-based precipitation retrievals, for subsequent precipitation retrievals separately from each

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