Tellus: Series A, Dynamic Meteorology and Oceanography (Sep 2015)
Cyclones, windstorms and the IMILAST project
Abstract
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.
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