Tuleya, R. E., and S. J. Lord, 1997: The impact of dropwindsonde data on GFDL hurricane model forecasts using global analyses. Weather & Forecasting, 12(2), 307-323.

Abstract: The National Centers for Environmental Prediction (NCEP) and the Hurricane Research Division (HRD) of NOAA have collaborated to postprocess Omega dropwindsonde (ODW) data into the NCEP operational global analysis system for a series of 14 cases of Atlantic hurricanes (or tropical storms) from 1982 to 1989. Objective analyses were constructed with and without ingested ODW data by the NCEP operational global system. These analyses were then used as initial conditions by the Geophysical Fluid Dynamics Laboratory (GFDL) high-resolution regional forecast model.

This series of 14 experiments with and without ODWs indicated the positive impacts of ODWs on track forecasts using the GFDL model. The mean forecast track improvement at various forecast periods ranged from 12% to 30% relative to control cases without ODWs: approximately the same magnitude as those of the NCEP global model and higher than those of the VICBAR barotropic model for the same 14 cases. Mean track errors were reduced by 12 km at 12 h, by ~50 km for 24-60 h, and by 127 km at 72 h (nine cases). Track improvements were realized with ODWs at ~75% of the verifying times for the entire 14-case ensemble.

With the improved analysis using ODWs, the GFDL model was able to forecast the interaction of Hurricane Floyd (1987) with an approaching midlatitude trough and the storm's associated movement from the western Caribbean north, then northeastward from the Gulf of Mexico into the Atlantic east of Florida. In addition, the GFDL model with ODWs accurately forecasted the rapid approach and landfall of Hurricane Hugo (1989) onto the U.S. mainland. An assessment of the differences between analyses indicates that the impact of ODWs can be attributable in part to differences of ~1 m s^-1 in steering flow of the initial state.

In addition to track error, the skill of intensity prediction using the ODW dataset was also investigated. Results indicate a positive impact on intensity forecasts with ODW analyses. However, the overall skill relative to the National Hurricane Center statistical model SHIFOR is shown only after 2 or 3 days. It is speculated that with increased data coverage such as ODWs both track and intensity error can be further reduced provided that data sampling can be optimized and objective analysis techniques utilizing asynoptic data can be developed and improved.