Abstract
The successful deployment of many different observing systems during the summer Monsoon Experiment of 1979 provides a unique opportunity to perform extensive observing system experiments. These numerical studies, accomplished here with a ten-level, limited-area primitive equation model, allow the assessment of the value of individual or combined observing systems to the model's four-dimensional data assimilation system as well as to its subsequent forecasts. The specific objectives of this work include the investigation of (i) the relative merit of ten different data platforms, (ii) the relative role of wind and mass field data, (iii) the effect of different vertical distributions of single-level wind data, and (iv) the dynamical response of the model to different modes of data insertion.
Eight experiments are summarized, all of which involved a 12-h data assimilation period based on the Newtonian relaxation procedure followed by a 36-h forecast. Predictions using all of the data produced very good forecasts of the June 1979 onset vortex over the Arabian Sea. The dropwindsonde data were found to be most responsible for this success, primarily because they resolve the rotational modes of the system and cover a significant depth of the troposphere. While the winds were more important, the dropsonde thermodynamic data were beneficial. All datasets, when tested individually, had a positive impact on the forecasts. When used in combination, however, some datasets became less important or even redundant. The influence of satellite winds was enhanced greatly by spreading the wind increments over a larger vertical depth. It is shown that the dynamical response of the model to the various distributions and amounts of new data is consistent with geostrophic adjustment theory and provides guidance for future observing system.
