Explaining discrepancies in passive microwave cloud-radiation databases in microphysical context from two different cloud-resolving models

Abstract

Mesoscale Cloud Resolving Models (CRMs) are often used to generate descriptions of the microphysical properties of precipitating clouds for the purpose of guiding precipitation retrieval algorithms designed for satellite-borne passive microwave radiometers. However, CRMs were not originally designed for that purpose. Notably, individual CRMs have adopted different bulk microphysical schemes to optimize the dynamical evolution of storms and accumulated rainfall, rather than optimizing for simulations of radiative properties – which are greatly affected by the microphysical details and vertical distributions of liquid and frozen hydrometeors. Thus, in principle, the simulated upwelling passive microwave (PMW) brightness temperatures (TBs) and associated precipitation retrievals generated by means of different CRMs with different microphysical parameterizations may be significantly different – even when the different CRMs prognostically adhere to the main dynamical and precipitation characteristics of a given storm.