Nowadays, it is still not really clear how the large panel of different cloud microphysical characteristics influences the radiative balance at a global scale. This leads to great uncertainties in assessing the cloud radiative forcing effect. Observations strategies are therefore developed to better determine and understand the worldwide relative proportion of clouds, in term of phase, particle habits, particle size distribution and orientation. The focus of this work lies on the observation, at high resolution, of ice crystals within mixed-phase clouds using the S-Band atmospheric radar TARA. Combining the Doppler and polarimetric capabilities of such radar, spectral parameters as the spectral differential reflectivity sZDR can be measured. First, from this parameter only, ice particle orientation and the degree of sphericity of the crystals are derived for each time and range bins. In a second step, the measured Doppler spectrum is compared and fitted with a simulated one obtained from a microphysical model based on spheroidal particle shapes. The ice particle size distribution, and consequently the ice water content, for different crystal habits can then be retrieved assuming that sZDR gives the axial ratio (from dual polarization) versus the size (from Doppler velocities) of the ice crystals. A great care is taken to obtain reliable spectral parameters. It will be discussed in this paper. Then results of the retrieval technique will be illustrated using collocated ground-based and aircraft measurements taken during the COPS campaign (Convective and Orographically-Induced Precipitation Study) in the black forest, Germany, in 2007.@en

Spectral polarimetry is based on combined simultaneous Doppler and polarization measurements, with a close look on the polarization dependence of the radar signal per velocity bin of the Doppler spectrum. The principle of radar spectral polarimetry and the main steps of the related processing are given in the paper. The processing results in clutter- and noise-free atmospheric spectrographs (Doppler spectra for every height). When the processed spectrographs are integrated to calculate the classical Doppler moments, the resulting estimates of reflectivity, mean Doppler velocity, Doppler width and polarimetric parameters are improved. Improved profiles have the potentiality to lead to better estimates of rain rates, liquid water and ice water content, and wind. In the paper, illustration is provided in the context of wind profiling, which employs as input mean Doppler velocity profiles. Another application consists of linking the processed Doppler spectrum with the Particle Size Distribution (PSD) of the medium being probed. Thus, in addition to the more traditional method of expressing the Doppler spectrum in its statistical moments, spectral polarimetry can also provide detailed microphysical information of precipitation and clouds in the case of slant profiling. One illustration is shown in the case of mixed-phase clouds. Both illustrations are part of the extended data set collected by the S-band radar TARA (Transportable Atmospheric RAdar) within the COPS campaign (Convective Orographycally-induced Precipitation Study) in the black forest in Germany during the summer of 2007.@en

Accuracy of Lidar remote sensors for wind energy has been previously reported. Coherent Doppler lidars have shown very high correlation with calibrated cup anemometers in flat terrain, both onshore and offshore. However, in more complex terrain, not only more turbulent air flow but also loss of flow homogeneity happen, and remote sensors measurement process need to be closely examined. We compare and simulate cup¿s point and lidar¿s volume measurements to understand and explain for the two sensor¿s response. We put in evidence the main error term in the horizontal and vertical wind speed retrieval. Geometrical optimizations of the WINDCUBETM measurement process are also investigated to get more reliable wind speed estimate. We show our conclusions and the results of the CFD simulation performed on a Spanish complex terrain case.@en

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

Snow crystals consist of many different types of ice particles. Typical radar measurements observe only bulk properties of all types of ice particles present in a radar volume. Due to their difference in radar cross-section, larger particles will reflect more power of the transmitted radar signal, than small particles. If small and large particles are present in the same radar volume with comparable volume concentration, the radar measurements will be dominated by larger particles. Because of this, it is difficult to obtain microphysical properties of both large and small particle types, based on reflectivity alone. In this work, application of dual polarization spectral analysis for retrieval of microphysical properties of ice particles in stratiform precipitation is presented. Based on literature research, a selection on the particle types that are predominantly present in radar measurements is done. The selection is based on both radar cross sections of the different particles and meteorological conditions. The radar cross-sections are calculated with a model derived from literature, on the microstructure of ice crystals. With the obtained knowledge, it is shown that only aggregates and plates dominate spectral radar retrievals above the melting layer of stratiform precipitation. A model for the spectral horizontal reflectivity and spectral differential reflectivity of plates and aggregates, is created. This model is dependent on the parameters of the drop size distribution of plates and aggregates, the ambient wind velocity and spectral broadening. Using a sensitivity study of the spectral radar observables on the drop size distribution parameters, an algorithm is developed that is able to retrieve drop size distribution parameters of plates and aggregates from spectral radar measurements collected above the melting layer in stratiform precipitation. The drop size distribution parameters are retrieved by fitting the modelled spectral radar observables to the radar measurements using a non-linear least squares optimization technique. This kind of optimization algorithms, change the dependent variables of the model to obtain the best fit of the model to the measurement. The retrieval of drop size distribution parameters of plates and aggregates, is illustrated on data of stratiform precipitation collected by TARA. TARA is an S-band FM-CW dual polarization Doppler radar, situated at the measurement site Cabauw, The Netherlands. Using the outputs of the algorithm, it is shown that the obtained drop size distribution parameters are consistent. Verification of the outputs of the algorithm is performed by comparison of the estimated ice water content with the liquid water content, obtained below the melting layer. The estimated ice water content is also compared to the measured reflectivity. It is shown that the obtained results for plates are in good agreement with relations between ice water content and reflectivity obtained from literature. A new relation between the ice water content and the reflectivity is derived for aggregates.@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