Feasibility of Direct Assimilation of Cloud Radar and Lidar Observations in the ECMWF 4D-Var System using Cloudsat and CALIPSO

Active observations from profiling instruments such as cloud radar or lidar contain a wealth of information on the vertical structure of clouds and precipitation. However, the only cloud affected observations that are routinely assimilated in global NWP models are radiance observations, which contain limited information on cloud structure. Inspired by the success of 1D+4D-Var experiments where Cloudsat radar reflectivity and Calipso attenuated backscatter profiles were indirectly assimilated via pseudo observations of temperature and humidity, the ECMWF 4D-Var system has been adapted to allow their direct assimilation. Direct 4D-Var assimilation allows a more accurate treatment of observation errors compared to the 1D+4D-Var approach.

In this presentation, we will first outline the challenges to assimilation of profiling observations of clouds, including the specification of the forward models and a flow-dependent characterisation of the observation error. In particular, errors due to representativity will be discussed, which can be large considering the instruments’ narrow field-of-views. We will then assess the impact of assimilating Cloudsat and Calipso observations directly into the ECMWF 4D-Var assimilation system by comparing the analysis to independent observations. This is the first time cloud radar and lidar observations have been directly assimilated in a global NWP model and paves the way for operational assimilation of EarthCARE measurements upon its launch.