Assimilation of cloud information from space‐borne radar and lidar: experimental study using a 1D+4D‐Var technique

Space-borne active instruments, providing a vertically resolved characterization of clouds, promise a new dimension of information to be used in numerical weather prediction systems. Research activities are ongoing at the European Centre for Medium-Range Weather Forecasts to exploit these data for monitoring and assimilation purposes. Using currently available observations from CloudSat and CALIPSO, a technique combining one-dimensional variational (1D-Var) assimilation with four-dimensional variational (4D-Var) data assimilation has been used to study the impact of cloud-related observations on analyses and subsequent forecasts. Temperature and specific humidity vertical profiles retrieved from 1D-Var using observations of cloud radar reflectivity and lidar backscatter, either separately or in combination, were used as pseudo-observations in the 4D-Var system. Results indicate that 1D-Var analyses get closer to assimilated and also independent observations when appropriate quality control, bias correction and error estimate are applied. The performed 1D+4D-Var assimilation experiments also suggest a slight positive impact of the new observations on the subsequent forecast. Generally, the impact of lidar backscatter from clouds is smaller than that of cloud radar reflectivity.