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Towards a better understanding of wind gusts: observations, processes, predictions and verification
Forecasting wind gusts may become the next major challenge in numerical weather prediction. With increasing computer power, operational NWP systems just entered the convective scale, allowing the model physics to simulate convective processes more explicitly. While this is very beneficial for precipitation forecasting, wind gusts are still a sub-grid scale phenomena relying on crude parametrizations. Furthermore, wind gusts cause large socio-economic damages every year. Wind gust predictions are getting higher relevance and load, e.g. for transport, aviation, urban development or public weather warnings. Yet forecast verification exhibits exceptionally low skill for wind gust predictions compared to other meteorological variables, which might also be impacted by a very sparse observational network. The spatial variability of wind gusts is probably as large as that of precipitation, but the observational network is much less dense and no equivalent to the spatial coverage of radar derived precipitation exists.
This session welcomes contributions which lead to a better understanding of the physical processes that determine wind gusts, and novel ideas/methods to improve wind gust forecasting and warnings in the future. More specifically, contributions on the following topics are welcome:
- Observations: The development of novel measurement tools for wind gusts (e.g. WindLIDARS) and suggestions for an optimized observational network in the future. Descriptions of the spatio-temporal variations of gusts.
- Explicit modelling: Small-scale model simulations (e.g. LES simulations) are a prerequisite to explicitly resolve the processes leading to wind gusts. Beside a better understanding of the physical processes they can be utilized to improve empirical approaches to approximate wind gusts more accurately.
- Wind gust forecasting and warnings: Methods to obtain guidance for wind gusts forecasts and warnings from operational weather forecasts, e.g. using historical observations by statistical postprocessing or forecast assimilation techniques. Prediction uncertainty of wind gusts.
- Climate monitoring: Long-term data sets for wind gusts as well as techniques for spatial wind gust analysis which are necessary for climate change adaptation and mitigation strategies
- Evaluation: The high-resolution model simulations on the one side and a sparse observational network on the other side require novel ideas in the verification of wind gusts simulations and warnings.