Simulation and sensitivity analysis for cloud and precipitation measurements via spaceborne millimeter-wave radar

Abstract

Abstract. This study presents a simulation framework for cloud and precipitation measurements via spaceborne millimeter-wave radar composed of eight submodules. To demonstrate the influence of the assumed physical parameters and to improve the microphysical modeling of the hydrometeors, we first conducted a sensitivity analysis. The results indicated that the radar reflectivity was highly sensitive to the particle size distribution (PSD) parameter of the median volume diameter and particle density parameter, which can cause reflectivity variations of several to more than 10 dB. The variation in the prefactor of the mass–power relations that related to the riming degree may result in an uncertainty of approximately 30 %–45 %. The particle shape and orientation also had a significant impact on the radar reflectivity. The spherical assumption may result in an average overestimation of the reflectivity by approximately 4 %–14 %, dependent on the particle type, shape, and orientation. Typical weather cases were simulated using improved physical modeling, accounting for the particle shapes, typical PSD parameters corresponding to the cloud precipitation types, mass–power relations for snow and graupel, and melting modeling. We present and validate the simulation results for a cold-front stratiform cloud and a deep convective process with observations from a W-band cloud profiling radar (CPR) on the CloudSat satellite. The simulated bright band features, echo structure, and intensity showed a good agreement with the CloudSat observations; the average relative error of radar reflectivity in the vertical profile was within 20 %. Our results quantify the uncertainty in the millimeter-wave radar echo simulation that may be caused by the physical model parameters and provide a scientific basis for optimal forward modeling. They also provide suggestions for prior physical parameter constraints for the retrieval of the microphysical properties of clouds and precipitation.