Skill of Synthetic Superensemble Hurricane Forecasts for the Canadian Maritime Provinces

The impact of tropical cyclones on Canadian Provinces is an important issue. From 1994 to 2003, fifty-five tropical cyclones entered the Canadian Hurricane Centre (CHC) Response Zone, or ~42% of all named Atlantic tropical cyclones in this ten-year period, and 2003 was the fourth consecutive year for a tropical cyclone to make landfall in Canada. The CHC forecasts all tropical cyclones that enter the CHC Response Zone and assumes the lead in forecasting once the cyclone enters the CHC Area of Forecast Responsibility. This study acknowledges the challenges of forecasting such tropical cyclones at extratropical latitudes. If a tropical cyclone has been declared extratropical, global models may no longer carry the cyclone, and even if it is modeled, large model errors often result. The purpose of this study is to develop a new version of the FSU hurricane superensemble with greater skill in tracking tropical cyclones, especially at extratropical latitudes. This has been achieved from the development of the synthetic superensemble. The synthetic superensemble is similar to the multi-model superensemble that is used operationally at FSU. The operational superensemble is a statistical linear regression technique that uses real-time forecasts provided by several hurricane models to construct an optimal consensus forecast. The synthetic superensemble differs from the operational version in that it uses a larger set of member models, including the regular member models, synthetic versions of these models, and the operational superensemble and its synthetic version. Synthetic member model forecast tracks are produced by a simple alteration of the original model track. The alteration consists of producing a linear best-fit line through a hurricane track and applying a Fourier curve to the linear best-fit line to artificially generate a new track shape. This synthetic superensemble is being used here to forecast hurricane tracks from the 2001, 2002, and 2003 hurricane seasons. The synthetic superensemble produced forecasts with generally less track error than its member models, the operational superensemble, and the ensemble mean. It also performed exceptionally well for several major Canadian storms including Hurricane Juan of 2003 where the synthetic superensemble outperformed the Official forecast and the operational superensemble by 425-480 km at the longest forecast hour. Forecasting challenges for each season are discussed and it was found that the synthetic superensemble produced forecasts with greatest skill in the 2003 season when there were few major changes made to member models and when member models performed at their best. Overall, this research shows that the synthetic superensemble performs consistently well and would be an asset to operational hurricane track forecasting.