Ardao-Berdejo, Jose (Instituto Nacional de Meteorologia, Madrid, Spain)
Garcia-Moya, J. A. (same affiliation)
The four-dimensional data assimilation nudging technique is applied in order to extract as much information as possible from the observations.
In this technique artificial terms are added to the model's prognostic equations to correct the model's values and produce improved datasets to be used as initial conditions for the forecast model. Such corrections are proportional to the difference between the observed values and the model's values.
The main goal of this presentation is to show the usefulness of the this new assimilation technique in the framework of the Hirlam forecast system.
As nudging is well suited to assimilate asynoptic data a case study from the PYREX experiment was chosen to assess the performance of the new technique comparing with the standard assimilation by intermitent steps.