Dynamically weighted hybrid-Mean/LETKF data assimilation

NERSC (Copernicus).
Talk by Helena Barbieri de Azevedo.

Bio

Helena Barbieri de Azevedo is visiting NERSC from UCLouvain.

Abstract

Hybrid systems have become the state of the art among data assimilation methods. These systems combine the benefits of two other systems that are traditionally used in operational weather forecasting: an ensemble-based system and a variational system. One of the most recently proposed hybrid approaches is called hybrid mean/LETKF. It obtains the final analysis as a linear combination of two analyses, assuming that the innovations between the two data assimilation methods are identical. A perfect model experiment was performed using the HG in the SPEEDY model to show a new methodology to assign different weights to the two analyses, LETKF and 3D-Var in the generation of the final analysis. Our new approach uses, in the assignment of the weights, the ensemble spread, considered to be a measure of uncertainty in the LETKF.