Promising results in hybrid data assimilation tests
Hamrud, Mats ; Bonavita, Massimo ; Isaksen, Lars
ECMWF has been a pioneer in the development and operational implementation of a data assimilation method called 4DVAR. '4D' stands for the three spatial dimensions plus time, as this method uses observations as they come in over a period of time, while 'VAR' refers to variational methods. An alternative algorithm, called the Ensemble Kalman Filter (EnKF), is also suitable for operational use. In recent tests, an EnKF-based data assimilation system developed at the Centre has shown good forecast performance, and a hybrid 4DVAR/EnKF approach has been found to perform significantly better than the two systems in standard configuration individually. The EnKF algorithm is also highly scalable, making it particularly well-suited to future, massively parallel computer architectures. The performance of the hybrid 4DVAR/EnKF system has been found to be comparable to that of a low-resolution version of the data assimilation system in operational use at ECMWF, which is a 4DVAR system combined with an ensemble of data assimilations.
Accès à la notice sur le site du portail documentaire de Météo-France