Global data assimilation techniques developed in the world leading numerical weather prediction centers in the years to come are more clearly seen in the direction of combining variational data assimilation with ensemble information in model background error covariance, or hybrid data assimilation. The remote sense observations are used more efficiently. The effort will focus on the satellite radiance data assimilation in the area of cloud and rain covered regions. As the first leading numerical weather prediction center on data assimilation technique development, European Center for Medium-Range Weather Forecasts (ECMWF) technique development has representativeness. The progress on data assimilation technique in ECMWF is reviewed in this paper, specially focusing on the fields of variational data assimilation system development and satellite observation application. The key technical advances are introduced, including long-time window and weak-constraint four-dimensional variational data assimilation, ensemble data assimilation, moisture and cloud condensation analysis, linearizing moisture physics processes, assimilation of satellite infrared hyper-spectral observation in clear-sky, satellite infrared hyper-spectral and microwave observations under cloud and precipitation conditions. The technical review can be seen as a guidance for the development of Global and Regional Analysis and Prediction System (GRAPES) numerical weather model: priority should be given to the key technique selection of GRAPES 3/4DVAR operational application, and hybrid data assimilation technique should be considered and prepared in advance when the 4DVAR technique is being developed.
Author: Gong Jiandong
Source: Advances in Meteorological Science and Technology
Editor: Hao Jing