Diagnosing Cloud Microphysical Process Information from Remote Sensing Measurements—A Feasibility Study Using Aircraft Data. Part I: Tropical Anvils Measured during TC4

Abstract

AbstractThe authors investigate whether radar remote sensing of a certain class of ice clouds allows for characterization of the precipitation rates and aggregation processes. The NASA DC-8 collected the measurements in tropical anvils during July and August 2007 as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment. Measured hydrometeor size distributions are used to estimate precipitation rates (P) and to solve the hydrodynamical collection equation. These distributions are also used to estimate radar reflectivity factors (Z) and Doppler velocities (Vd) at W, Ka, and Ku bands. Optimal estimation techniques are then used to estimate the uncertainty in retrieving P and aggregation rates (A) from combinations of Z and Vd. It is found that diagnosing information about A requires significant averaging and that a dual-frequency combination of W and Ka bands seems to provide the most information for the ice clouds sampled during TC4. Furthermore, the addition of Vd with expected uncertainty contributes little to the microphysical retrieval of either P or A. It is also shown that accounting for uncertainty in ice microphysical bulk density dominates the retrieval uncertainty in both P and A causing, for instance, the instantaneous uncertainty in retrieved P to increase from ~30% to ~200%.