Forward Modeling of Spaceborne Active Radar Observations

Abstract. Accurate forward models, particularly radiative transfer models, are essential for the assimilation of both passive and active satellite observations in modern data assimilation frameworks. The Community Radiative Transfer Model (CRTM), widely used in the assimilation of satellite data within numerical weather prediction systems, especially in the United States, has recently been expanded to include an active radar module. This study assesses the new module across multiple radar frequencies using observations from the Earth Clouds, Aerosols and Radiation Explorer Cloud Profiling Radar (EarthCARE CPR), the CloudSat CPR, and the Global Precipitation Measurement Dual-Frequency Precipitation Radar (GPM DPR). Simulated radar reflectivities were compared with the spaceborne measurements to assess the impacts of hydrometeor profiles, particle size distributions (PSDs), and frozen hydrometeor habits. The results indicate that both PSD selection and particle shape significantly influence the simulated reflectivities, with snow particle habits introducing differences of up to 4 dBZ in W-band comparisons. For the GPM DPR, reflectivities simulated using the Thompson PSD showed better agreement with observations compared to those using the Abel PSD. The findings highlight the strong sensitivity of forward radar simulations to microphysical assumptions, underscoring their potential to improve the assimilation of spaceborne radar data in NWP models.