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Munehiko Yamaguchi, Junichi Ishida, Hitoshi Sato, and Masayuki Nakagawa


Tropical cyclone (TC) track forecasts of operational numerical weather prediction (NWP) models have been compared and verified by the Japan Meteorological Agency (JMA) under an intercomparison project of the Working Group on Numerical Experimentation (WGNE) since 1991. This intercomparison has promoted validation of the global models in the tropics and subtropics. The results have demonstrated a steady increase in the global models’ ability to predict TC positions over the past quarter century.

The intercomparison study started from verification for TCs in the western North Pacific basin with three global models. Up to the present date, the verification has been extended to all ocean basins where TCs regularly occur, and 12 global models participated in the project. In recent years, the project has been extended to include verification of intensity forecasts and forecasts by regional models.

This intercomparison project has seen a significant improvement in TC track forecasts, both globally and in each TC basin. In the western North Pacific, for example, we have succeeded in obtaining an approximately 2.5-day lead-time improvement. The project has also demonstrated the benefits of multicenter track forecasts (i.e., consensus forecasts). Finally, the paper considers future challenges to TC track forecasting by NWP models that have been identified at the World Meteorological Organization’s (WMO’s) Eighth International Workshop on Tropical Cyclones (IWTC-8). We discuss the priorities and key issues in further improving the accuracy of TC track forecasts, reducing cases of large position errors, and enhancing the use of ensemble information.

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Richard Swinbank, Masayuki Kyouda, Piers Buchanan, Lizzie Froude, Thomas M. Hamill, Tim D. Hewson, Julia H. Keller, Mio Matsueda, John Methven, Florian Pappenberger, Michael Scheuerer, Helen A. Titley, Laurence Wilson, and Munehiko Yamaguchi


The International Grand Global Ensemble (TIGGE) was a major component of The Observing System Research and Predictability Experiment (THORPEX) research program, whose aim is to accelerate improvements in forecasting high-impact weather. By providing ensemble prediction data from leading operational forecast centers, TIGGE has enhanced collaboration between the research and operational meteorological communities and enabled research studies on a wide range of topics.

The paper covers the objective evaluation of the TIGGE data. For a range of forecast parameters, it is shown to be beneficial to combine ensembles from several data providers in a multimodel grand ensemble. Alternative methods to correct systematic errors, including the use of reforecast data, are also discussed.

TIGGE data have been used for a range of research studies on predictability and dynamical processes. Tropical cyclones are the most destructive weather systems in the world and are a focus of multimodel ensemble research. Their extratropical transition also has a major impact on the skill of midlatitude forecasts. We also review how TIGGE has added to our understanding of the dynamics of extratropical cyclones and storm tracks.

Although TIGGE is a research project, it has proved invaluable for the development of products for future operational forecasting. Examples include the forecasting of tropical cyclone tracks, heavy rainfall, strong winds, and flood prediction through coupling hydrological models to ensembles.

Finally, the paper considers the legacy of TIGGE. 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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