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.

African easterly waves (AEWs) are identified in numerical model analyses using an objective technique based on the 700-hPa streamfunction field. This method has been developed to (i) reduce the amount of manual data interpretation, (ii) reduce the likelihood of unrelated phenomena being identified as AEWs, and (iii) facilitate completely objective comparisons between AEWs with different structures on multiple scales, in order to describe their variability. Results show this method performs well when compared to methods of AEW identification used in previous studies. The objective technique is used to analyze all AEWs that originated over tropical North Africa during July–September (JAS) 2004. Results indicate that the “average” AEW in this period bears a close resemblance to composite structures from previous research. However, there is marked variability in the characteristics and ultimate fate of AEWs. Most AEWs of JAS 2004 are first identified east of the Greenwich meridian and develop as they move westward. Mature structures over the African continent varied, ranging from isolated potential vorticity maxima confined equatorward of the objectively defined African easterly jet to broad cross-jet structures symptomatic of both baroclinic and barotropic growth. As many as 80% of the cases fell into the second category. After leaving the West African coast, 45% of the AEWs in JAS 2004 were associated with tropical cyclogenesis in either the Atlantic or Pacific Ocean basins.

SUMMARYA systematic and objective procedure is developed for applying the simple cyclone classi cation scheme of Petterssen and Smebye. This method uses a height-attributable solution of the quasi-geostrophic ! equation to identify and quantify the relative importance of upper-and lower-tropospheric forcing and also the time trend in the horizontal spacing of the forcing at these two levels. By applying this classi cation method to a sample of cyclogenesis events, during their maximum intensi cation stage, from the Fronts and Atlantic Storm-Track EXperiment eld experiment, the Type A and Type B scheme of Petterssen and Smebye is reproduced and extended to include a Type C. Type C consists of upper-level dominated cyclones that form at high latitudes and in their initial stages resemble comma-cloud-type polar lows. Detailed examples of each of the three types are presented. Some cyclones can undergo more than one period of development and it is found that each development period can be classi ed as a different cyclogenesis category, A or B: these cyclones are classi ed as hybrid Type A=B. There is some evidence that cyclone forecast accuracy depends on cyclone type, thereby suggesting the potential for this method to be used to assign con dence levels for forecasts of cyclogenesis produced by numerical weather-prediction models. Type B cyclones appear more dif cult to predict, because their development depends, initially, on the interaction between signi cant features in the upper and lower troposphere.

Synoptic-scale cyclonic features provide an inescapable focal point for operational forecasting, whilst the merits of tracking such features are increasingly being recognized in the climate change field. Close association with adverse and extreme weather is the main motivator. Here a new and highly sophisticated set of techniques to detect, classify and track the full range is developed. A revised conceptual model of cyclone development provided the initial framework, ensuring a solid bond with forecasting practice, whilst also connecting closely to baroclinic life-cycle concepts. Building on this, cyclones are detected using a hybrid of geopotential minimum/vorticity maximum techniques, whilst incorporating important extensions to ensure that vorticity can be used at high resolution (∼50 km) and that features on fronts take priority. To track the features across time, at intervals of 12 h or less, feature attributes in the association process are used. Additionally, an upper-tropospheric steering wind is employed to estimate future and past positions. This facilitates 'half-time tracking', a new approach that has clear-cut advantages over 'full-time tracking' employed elsewhere.In detection tests, comparing with subjectively-drawn charts, the feature hit rate was 84%, and the false alarm ratio 17%, whilst in a simple tracking test the association failure rate was just 2%. These values compare very favourably with previous studies.One key application is discussed. This involves processing ensemble output to provide wide-ranging real-time products tailor-made to forecasters' needs. Products include track-following plume diagrams, for various cyclone attributes, and storm-track strike probability plots for different thresholds of severity.

A new equitable score is developed for monitoring precipitation forecasts and for guiding forecast system development. To accommodate the difficult distribution of precipitation, the score measures the error in 'probability space' through use of the climatological cumulative distribution function. For sufficiently skilful forecasting systems, the new score is less sensitive to sampling uncertainty than other established scores. It is therefore called here the 'Stable Equitable Error in Probability Space' (SEEPS). Weather is partitioned into three categories: 'dry', 'light precipitation' and 'heavy precipitation'. SEEPS adapts to the climate of the region in question so that it assesses the salient aspects of the local weather, encouraging 'refinement' and discouraging 'hedging'. To permit continuous monitoring of a system with resolution increasing in time, forecasts are verified against point observations. With some careful choices, observation error and lack of representativeness of model grid-box averages are found to have relatively little impact. SEEPS can identify key forecasting errors including the overprediction of drizzle, failure to predict heavy large-scale precipitation and incorrectly locating convective cells. Area averages are calculated taking into account the observation density. A gain of ∼2 days, at lead times of 3-9 days, over the last 14 years is found in extratropical scores of forecasts made at the European Centre for Medium-Range Weather Forecasts (ECMWF). This gain is due to system improvements, not the increased amount of data assimilated. SEEPS may also be applicable for verifying other quantities that suffer from difficult spatio-temporal distributions. Copyright c 2010 Royal Meteorological Society Key Words: equitability; probability space; sampling uncertainty; refinement; hedging