Ensemble Predictions of Tropical Cyclone Rainfall Totals in Varying Synoptic Environments

The value of using ensemble-based numerical weather prediction (NWP) has been well established within the meteorological forecasting community for some time. Due to the reliance on NWP models for precipitation forecasts, it is increasingly important to determine the systems' performance in multi-threat, high impact events. This research will examine the forecasts of extreme precipitation by several different ensemble prediction systems for landfalling tropical cyclones in varying synoptic environments.

First, the amount and distribution of inland rainfall will be quantified and placed in historical context using multi-sensor precipitation analyses. Then, the probabilistic precipitation forecasts from multiple ensemble prediction systems will be evaluated. These ensemble systems will include the global ensembles in the THORPEX Interactive Grand Global Ensemble (TIGGE) as well as a WRF-based convection-allowing ensemble. The results will be analyzed based upon the prevailing synoptic environment in each tropical cyclone case to identify possible differences in forecast skill, along with the representation of uncertainty by the different ensemble systems. Any statistical difference in skill will be compiled with a goal of determining NWP model tropical cyclone forecasted precipitation tendencies in specific synoptic patterns.