Multi-model ensemble predictions of aviation turbulence

Abstract

Turbulence remains one of the leading causes of aviation incidents. Climate change is predicted to increase the occurrence of clear-air turbulence 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 fasten their seatbelts. 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.