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Multi-model ensemble predictions of aviation turbulence

Storer, L. N., Gill, P. G. and Williams, P. D. (2019) Multi-model ensemble predictions of aviation turbulence. Meteorological Applications, 26 (3). pp. 416-428. ISSN 1350-4827

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To link to this item DOI: 10.1002/met.1772

Abstract/Summary

Turbulence remains one of the leading causes of aviation incidents. Climate change is predicted to increase the occurrence of Clear‐Air Turbulence (CAT), and therefore forecasting turbulence will become more important in the future. Currently the two World Area Forecast Centres (WAFCs) use deterministic numerical weather prediction models to predict clear‐air turbulence operationally, it has been shown that ensemble forecasts improve the forecast skill of traditional meteorological variables. This study applies multi‐model ensemble forecasting to aviation turbulence for the first time. It is shown in a 12‐month global trial from May 2016 to April 2017, that combining two different ensembles yields a similar forecast skill to a single model ensemble, and yields an improvement in forecast value at low cost/loss ratios. This finding is consistent with previous work showing that the use of ensembles in turbulence forecasting is beneficial. Using a multi‐model approach is an effective way to improve the forecast skill and provide pilots and flight planners with more information about the forecast confidence, allowing them to make a more informed decision about what action needs to be taken, such as diverting around the turbulence or requiring passengers and flight attendants to be seatbelted. The multi‐model ensemble approach is intended to be made operational by both WAFCs in the near future and this study lays the foundations to make this possible.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:80735
Publisher:Royal Meteorological Society

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