Using the Superensemble Method to Improve Eastern Pacific Tropical Cyclone Forecasting

For many years tropical cyclone superensemble has shown remarkable skill in forecasting Atlantic tropical cyclone track and intensity. In this project tropical cyclone superensemble is applied to Eastern Pacific tropical cyclone forecasting for the 2004 Eastern Pacific tropical cyclone season. This task is completed by conducting a collection of model combination tests to discover which models perform best within the superensemble method. Then, the two main questions of this thesis are addressed: will a combined Eastern Pacific and Atlantic training set provide superior forecasts over just using an Eastern Pacific training set, and do intensity-specific training sets provide superior forecasts over just using all storms of varying intensities? In the context of the 2004 Eastern Pacific tropical cyclone season, the answer to both questions is yes. However, the ultimate findings are quite perplexing, as an Atlantic training set provides superior forecasts when compared to forecasts using an Eastern Pacific training set or a combined-basin training set. Furthermore, forecasts made using only hurricane training usually outperform forecasts made using combined-intensity training and tropical storm training. The rest of the project uses model bias comparisons and intensity-specific error calculations to try and determine why the results are as they are.