Lidar-radar synergistic method to retrieve ice, supercooled and mixed-phase clouds properties

Abstract. Mixed-phase clouds are not well represented in climate and weather forecasting models, due to a lack of the key processescontrolling their life cycle. Developing methods to study these clouds is therefore essential, despite the complexity of mixed-phase cloud processes and the difficulty of observing two cloud phases simultaneously. We propose in this paper a new methodto retrieve the microphysical properties of mixed-phase clouds, ice clouds and supercooled water clouds using airborne orsatellite radar and lidar measurements. This method extends an existing variational method developed for ice clouds retrievalusing lidar, radar and passive radiometers. We assume that the attenuated lidar backscatter β at 532 nm is more sensitive toparticle concentration and is consequently mainly sensitive to the presence of supercooled water. In addition, radar reflectivityZ at 95 GHz is sensitive to the size of hydrometeors and hence more sensitive to the presence of ice crystals. Consequently,in the mixed-phase the supercooled liquid droplets are retrieved with the lidar signal and the ice crystals with the radar signal,meaning that the retrieval rely strongly on a priori and errors values. This method retrieves then simultaneously the visibleextinction for ice αice and liquid αliq particles, the ice and liquid water contents IWC and LWC, the effective radius of icere,ice and liquid re,liq particles and the ice and liquid number concentrations Nice and Nliq. Moreover, total extinction αtot, totalwater content TWC and total number concentration Ntot can also be estimated. As the retrieval of ice and liquid is different, it isnecessary to correctly identify each phase of the cloud. To this end, a cloud phase classification is used as input to the algorithmand has been adapted for mixed-phase retrieval. The data used in this study are from DARDAR-MASK v2.23 products, basedon the CALIOP lidar and CPR radar observations, respectively from the CALIPSO and CloudSat satellites belonging to theA-Train constellation launched in 2006. Airborne in situ measurements performed on the 7th April 2007 during the ASTARcampaign and collected under the track of CloudSat-CALIPSO are compared to the retrievals of the new algorithm to validateits performance. Visible extinctions and water contents properties derived from in situ measurements and the retrievals showedsimilar trends and are globally in good agreement. The mean percent error between the retrievals and in situ is 39 % for αliq,398 % for αice, 49 % for LWC and 75 % for IWC. It is also important to note that the temporal and spatial collocations are notalways optimal, that the sensibility of remote sensing and in situ are not the same and that in situ measurements uncertaintiesare between 25 % and 60 %.