Abstract
The problem of four-dimensional data assimilation in the tropics has been studied using a limited-area primitive equation model. Of prime concern is the relative importance of different update variables and their impact on data assimilation. Five new experiments complement a set of ten previously reported experiments that investigate the feasibility of four-dimensional data assimilation in the monsoon region using only the wind observations. In addition to assessing the relative importance of update variables, the present study investigates the role of model physics in data assimilation.
The assimilation experiments are carried out for the onset vortex case of the 1979 Indian summer monsoon for which many special FOGE/MONEX datasets are available. The assimilation-forecast system for all of the experiments comprises a 12-h assimilation phase followed by a 24-h forecast period. In all experiments, updating is done via the Newtonian nudging approach which, in our previous study, was found to be more effective than other methods of updating.
It is found that at least for this dataset, the wind data were wore valuable than the temperatures. Although temperature assimilation alone had some unexpected positive results, it did not offer appreciable improvement over wind-only assimilations when the two variables were inserted together. On the other hand, a combination of wind and moisture data produced the most positive results. This confirms the importance of wind and moisture data in the tropics. Finally, it has been found that the incorporation of physical parameterizations during the assimilation period is important for a proper spinup of the model and its smooth transition into the forecast stage.
