In this study, a dual-polarization spectral analysis for retrieval of microphysical properties of ice hydrometeors is developed. It is shown that, by using simultaneous Doppler polarimetric observations taken at a 45° elevation angle, it is possible to discriminate between different types of ice particles. Particle size distribution parameters for maximally two dominating types of ice particles (aggregates and plates) observed above the melting layer are retrieved. Prior to the retrieval algorithm, a selection of possible types of ice particles based on environmental conditions is carried out. The retrieval procedure is based on a least squares optimization that simultaneously minimizes fit residuals in a Doppler power spectrum and spectral differential reflectivity. The proposed method is illustrated on transportable atmospheric radar (TARA) observations of stratiform rain collected on 19 September 2001 at Cabauw, Netherlands.@en

In most part of the troposphere the temperature is negative. It induces some regions where thropspheric clouds are composed by a mix of ice crystals and supercooled water droplets. Nevertheless those clouds are still poorly represented in climate models (Hogan et al., 2003) even if their influences on cloud evolution, cloud scale dynamics and the surface energy budget are relevant ( Cess & al., 1995, Harrington & Olsson, 2001, Shape & Interieri, 2004). A new technique is under development in the University of Delft for remotely determining IWC inside mixed-phase clouds from measurements taken by the S band Doppler Polarimetric radar TARA and combining it with a microphysical model (appendix D: Spek et al., 2005). This constitutes a first step in the retrieval of IWC and LWC from a radar/ lidar synergy. Since radars and lidars are sensitive to different types of particles the relative differences between both devices backscattered signals contain information on the particles being probed i.e. the WC.@en

Knowledge of water clouds is essential for climate studies. To understand present global climate and predicat climate changes, global observations of cloud microphysical properties are needed and space-based systems must be considered. Retrieval of cloud parameters from space challenges current tedchnological possibilities; not just due to sensor limitations, but also due to complex relationships between cloud parameters and remote sensing observables. Straight-forward retrieval of cloud microphysics with radar only., is hindered bu the presence of drizzle. To overcome this problem, synergetic use of multiple sensors is employed. This paper focusses on the retrieval of the cloud liquid water content by means of spaceborne radar and lidar measurements. The combination of radar reflectivity and lidar optical extinction is used to classify clouds according to their drizzle fraction. Appropriate retrival algorithms can then be applied to each category to obtain the liquid water content. As the method was initially developed for ground-based instruments, differences between sensing clouds from above and below are studied. Airborne data was then used to simulate space-based applications was established. It is shown that accurte liquid water content retrieval from space is possible.@en