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This paper describes an experimental procedure for assimilating CloudSat Cloud Profiling Radar (CPR) observations in ALADIN 3D-Var through the use of humidity pseudo-observations derived from a one-dimensional Bayesian analysis. Cloud data are considered as binary occurrences (‘cloud’ vs ‘no-cloud’), which makes the approach feasible to be extended to other cloudiness observations, and to any other binary observation in general. A simple large-scale condensation scheme is used for projecting the prior information from a Numerical Weather Prediction model into cloud fraction space. Verification over a 1 month assimilation test period indicates a clear benefit of the pseudo-observation assimilation scheme for the limited CloudSat CPR data set, especially in terms of improved skill scores for dynamical parameters such as geopotential and wind. Copyright © 2008 Royal Meteorological Society |
