Tropical Cyclone Initialization and Prediction Based on Four-Dimensional Variational Data Assimilation

Issues of initialization & simulation of tropical cyclones (TCs) have been addressed in this paper based on a case study using four-dimensional variational data assimilation. In particular, experiments have been carried out to assess: (1) what are the crutial parameters for the so-called bogus data assimilation; & (2) how the current procedures for the bogus data assimilation can be further improved. In this case study, the assimilation of wind fields has shown to be more successful than that of pressure fields in improving the initial structure & the TC prediction. It should be emphasized that the geostrophic adjustment favors the pressure field to adjust to the wind field because the TC vortex is much smaller than the radius of Rossby deformation. Our results suggest that a better initial condition in the wind field would be critical to the simulation of TCs. Our experiments have also shown that inclusion of the initial TC movement in the data assimilation window may help improve the track prediction, particularly during the early integration period. The tentative conclusion has been validated by another typhoon case study. This method works in both cases & would be able to shed light on the improvement of TC simulation based on the bogus data assimilation. In all, our results add a theoretical interpretation of the importance of the wind field to the sea-level pressure field in terms of geostrophic adjustment, as well as a time dimension of the bogus data assimilation by assimilating a movable vortex during the assimilation window. It is worthwhile to apply the proposed findings to more typhoon cases & to examine their generality