An intercomparison experiment involving 15 commonly used detection and tracking algorithms for extratropical cyclones reveals those cyclone characteristics that are robust between different schemes and those that differ markedly.

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A B S T R A C T By way of introduction to the TELLUS thematic cluster on outcomes of the IMILAST project (Intercomparison of MId-LAtitude STorm diagnostics), this paper presents the results of new research that is fundamental for the correct interpretation of IMILAST results. Specifically we investigated the mesoscale structure of cyclonic windstorms, and the representation of those windstorms in re-analysis data. The paper concludes with an overview of the project itself. Twenty-nine historic windstorms are studied in detail, using wide-ranging observational data, and on this basis a conceptual model of the life cycle of a typical windstorm-generating cyclone is developed. The model delineates three wind phenomena, the warm jet, the sting jet and the cold jet, and maps out the typical damage footprint left by each. Focussing on the boundary layer, the physical processes at work in each jet zone are investigated. These include the impact of near-surface stability and exposure on gust strength. Based on numerous cases, a generic description of the sting jet is provided, with many new features highlighted. This phenomenon looks to be unique in that exceptional gusts can be realised well inland because destabilisation is activated from above. We next investigate how well the widely-referenced ERA-Interim re-analysis, that has been a primary data source for IMILAST, can represent windstorms. In many ways, performance is suboptimal. Compared to a benchmark manually-analysed dataset, windstorm-generating cyclones generally do not deepen rapidly enough. In part, this is a resolution limitation. For one medium-sized cyclone, it is shown, using other models, that horizontal resolution of order 20 km or better is required to capture the most damaging winds. In the context of IMILAST, which has used data at resolutions ]80 km, this is a fundamental result. For this and other reasons, caution is clearly needed when inferring storm behaviour and severity from model-based metrics.

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.