Synergistic radar and radiometer retrievals of ice hydrometeors

Abstract. The upcoming Ice Cloud Imager (ICI) radiometer, to be launched on board the second generation of European operational meteorological satellites (Metop-SG), will be the first microwave imager to provide sub-millimeter observations of the atmosphere. The Microwave Imager (MWI) radiometer will be flown on the same satellites and complement the ICI sensor with observations at traditional millimeter wavelengths. The addition of these two new passive microwave sensors to the global system of earth observation satellites opens up opportunities for synergistic satellite missions aiming to maximize the scientific return of the Metop-SG program. This study analyzes the potential benefits of combining observations of the MWI and ICI radiometers with a 94-GHz cloud radar for the retrieval of frozen hydrometeors. Starting from a simplified numerical experiment, it is shown that the complementary information content in the radar and radiometer observations can help to better constrain the particle size distribution of ice particles in the atmosphere. The feasibility of the combined retrieval is demonstrated by applying a one-dimensional, variational cloud-retrieval algorithm to simulated observations from a high-resolution atmospheric model. Comparison of the results with passive- and radar-only versions of the retrieval algorithm confirms that synergies between the active and passive observations allow an improved retrieval of microphysical properties of frozen hydrometeors. The effect of the assumed ice particle shape on the results is analyzed and found to be critical for obtaining good retrieval performance. In addition to this, the synergistic retrieval shows improved sensitivity to liquid water in both warm and supercooled clouds. The results of this study clearly demonstrate the potential of the combined observations to constrain the microphysical properties of ice hydrometeors which can help to reduce errors in retrieved profiles of mass- and number densities.