Aviation Turbulence Ensemble Techniques

Buchanan, Piers

doi:10.1007/978-3-319-23630-8_14

Cited by 2 publications

(5 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The more skilful the model, the higher the maximum value will be (but the actual value will depend on the cost/loss ratio of the user), and if the value is higher for all cost/loss ratios then that model will be the most useful for any consumer (as the cost/loss ratio may vary depending on the consumer); this is known as sufficiency (Ehrendorfer and Murphy, ). Gill and Buchanan () and Buchanan () showed that probability turbulence forecasts have greater value than deterministic forecasts, so this project will aim to show by combining ensembles that the value can be further increased.…”

Section: Verification Methodsmentioning

confidence: 99%

“…To verify the forecasts, aircraft observations from a fleet of Boeing 747 and 777 aircraft were used and created a contingency table of results. From this the results were analysed to show that the multi‐model ensemble system is as skilful as a single model ensemble, which follows on from the work of Gill and Buchanan () and Buchanan ().…”

Section: Conclusion and Further Workmentioning

confidence: 99%

“…To help include jet stream uncertainty in the forecasts, Gill and Buchanan () and Buchanan () showed that using an ensemble of simulations improved the forecast skill. An ensemble forecast is a collection of many simulations of the same event with each outcome equally likely.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multi‐model ensemble predictions of aviation turbulence

Storer

Gill

Williams

2019

Meteorological Applications

View full text Add to dashboard Cite

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.

show abstract

Section: Verification Methodsmentioning

confidence: 99%

Section: Conclusion and Further Workmentioning

confidence: 99%

See 1 more Smart Citation

Multi‐model ensemble predictions of aviation turbulence

Storer

Gill

Williams

2019

Meteorological Applications

View full text Add to dashboard Cite

show abstract

“…4.1, 4.2, and 4.3 is that they do not convey uncertainty. To resolve this issue, Gill and Buchanan (2014) and Buchanan (2016) trialled the use of ensemble forecasting for aviation turbulence. An ensemble is a collection of forecast runs, each of which is considered to be equally likely.…”

Section: Ensemble Forecastingmentioning

confidence: 99%

“…The studies by Buchanan (2014) andBuchanan (2016) then combined the predictors in a manner similar to Sharman et al (2006), using an iterative scheme to maximise the forecast skill. Again, the studies showed that the ensemble forecast was more skillful than a single model deterministic forecast.…”

Section: Ensemble Forecastingmentioning

confidence: 99%

Aviation Turbulence: Dynamics, Forecasting, and Response to Climate Change

Storer

Williams

Gill

2018

Pure Appl. Geophys.

View full text Add to dashboard Cite

Abstract-Atmospheric turbulence is a major hazard in the aviation industry and can cause injuries to passengers and crew. Understanding the physical and dynamical generation mechanisms of turbulence aids with the development of new forecasting algorithms and, therefore, reduces the impact that it has on the aviation industry. The scope of this paper is to review the dynamics of aviation turbulence, its response to climate change, and current forecasting methods at the cruising altitude of aircraft. Aviationaffecting turbulence comes from three main sources: vertical wind shear instabilities, convection, and mountain waves. Understanding these features helps researchers to develop better turbulence diagnostics. Recent research suggests that turbulence will increase in frequency and strength with climate change, and therefore, turbulence forecasting may become more important in the future. The current methods of forecasting are unable to predict every turbulence event, and research is ongoing to find the best solution to this problem by combining turbulence predictors and using ensemble forecasts to increase skill. The skill of operational turbulence forecasts has increased steadily over recent decades, mirroring improvements in our understanding. However, more work is needed-ideally in collaboration with the aviation industry-to improve observations and increase forecast skill, to help maintain and enhance aviation safety standards in the future.

show abstract

Aviation Turbulence Ensemble Techniques

Cited by 2 publications

References 15 publications

Multi‐model ensemble predictions of aviation turbulence

Multi‐model ensemble predictions of aviation turbulence

Aviation Turbulence: Dynamics, Forecasting, and Response to Climate Change

Contact Info

Product

Resources

About