To appreciate the radiative impact of clouds in the dynamics of the global atmosphere, it is important to deploy from space, from aircraft, or from ground, instruments able to describe the cloud layering and to document the cloud characteristics (namely liquid and/or ice water content, and the effective particle radius). In the framework of EarthCARE (ESA), that plans to associate a cloud radar and a lidar on the same spatial platform, RALI (RAdar-LIdar) airborne system is an interesting demonstrator. RALI combines the 95 GHz radar of the CETP and the 0.5 μm wavelength backscattering lidar of the SA. In order to derive the radiative and microphysical properties of clouds, a synergetic algorithm has been developed. It combines the apparent backscatter coefficient, βa, from the lidar and the apparent reflectivity, Za, from the radar to infer properties of the particle size distribution. The principle of this algorithm is to apply in parallel the Hitschfeld-Bordan algorithm to the radar and the Klett algorithm to the lidar. Taken separately, these two algorithms are unstable, but by considering a mutual constraint, it is shown that a stable solution can be established. This solution formulates the retrieval of the true reflectivity and backscattering coefficient, to access microphysical and radiative parameters of clouds. This algorithm allows also to retrieve the variable N0* parameter, which is a normalization parameter of the particle size distribution.
This synergetic algorithm has been tested with simulated cases, and results of the algorithm applied on real data are validated by microphysical in-situ measurements.