Sensitivity of Spaceborne Radar and Microwave Radiometer Observations to Cloud Microphysical Properties in Deep Convection

Cloud microphysical processes are key to the development of convective systems, and exert an important influence on the precipitation, dynamics, and radiative properties of storms. Because in-situ and ground based observations of microphysics are limited to a few locations and times, satellite observations provide most of the global information on cloud microphysical processes. While cloud-top information can be obtained from passive measurements in visible and infrared wavelengths, the majority of the in-cloud information is derived from passive and active (e.g., radar) microwave measurements. The well-known sensitivity of radar and passive microwave measurements of clouds present both an opportunity and a challenge for the interpretation of spaceborne measurements, and have significant implifications for the design of future observing systems. New observations have promise for providing new information about cloud processes and properties; however, the complexity of cloud microphysics introduces significant uncertainty into the estimation of cloud properties. Ice microphysical properties are particularly complicated, involving a vast diversity of crystal habits and degrees of accumulated frozen liquid drops (rime). Ice crystal shape complexity introduces additional ambiguity into the relationship between radar measurements and cloud properties (mass and number distribution).

In this presentation, we focus on the challenge of quantifying and mitigating the uncertainty in estimates of cloud characteristics that arises from poorly constrained microphysical properties. In particular, we seek to determine whether the degree and characteristics of the uncertainty may vary as a function of the cloud type observed. We show results from a study of simulated microwave radiometer and radar reflectivity sensitivity to changes in cloud microphysical property assumptions for a large database of convective systems simulated with a high resolution numerical model. The model used is the Regional Atmospheric Modeling System (RAMS), which includes a highly realistic bin-emulating two-moment bulk microphysical scheme. RAMS has been used to simulate convective systems over land and ocean that range from shallow to deep and isolated to organized, forming in environments with a large range of shear and instability. Radar reflectivity and microwave brightness temperature observations are simulated from the RAMS output using a model that includes detailed ice crystal scattering properties. An uncertainty quantification infrastructure that is coupled with a flexible parallel computing toolkit allows for quantification of radar sensitivity to changes in microphysical assumptions, and for the uncertainties to be characterized as a function of convective storm type, development phase, and environment.