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.