Tropical cyclones are the most destructive weather systems in the world and are a focus of multimodel ensemble research. TIGGE data have been used for a range of research studies on predictability and dynamical processes. Alternative methods to correct systematic errors, including the use of reforecast data, are also discussed. For a range of forecast parameters, it is shown to be beneficial to combine ensembles from several data providers in a multimodel grand ensemble.
Examples include the forecasting of tropical cyclone tracks, heavy rainfall, strong winds, and flood prediction through coupling hydrological models to ensembles. Although TIGGE is a research project, it has proved invaluable for the development of products for future operational forecasting. We also review how TIGGE has added to our understanding of the dynamics of extratropical cyclones and storm tracks.
We discuss the priorities and key issues in predictability and ensemble forecasting, including the new opportunities of convective-scale ensembles, links with ensemble data assimilation methods, and extension of the range of useful forecast skill.
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