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.</p
