Impact of dropwindsonde data on the track forecasts of a tropical cyclone: An observing-systems simulation experiment study

Abstract

In this study, the model initial uncertainties associated with the track forecast of Hurricane Bonnie (1998) is examined through a series of observing-systems simulation experiments (OSSEs) with the Penn State University-National Center for Atmospheric Research inesoscale model (i.e., MM5). Analysis soundings with varying densities and configurations are used to mimic the inclusion of dropwindsonde data in the model initial conditions. Results show that increasing the soundings around the storm center improves the track forecasts. Enhanced observations in any quadrant of the storm would result in better track forecasts, but the forecast improvement is more pronounced when more Soundings are added to a region of stronger winds. The results indicate that proper design of the dropwindsonde distribution and density is crucial to the improvement of the track forecasts of tropical cyclones.