Accessibility navigation


Multi‐diagnostic multi‐model ensemble forecasts of aviation turbulence

Storer, L. N., Gill, P. G. and Williams, P. D. (2020) Multi‐diagnostic multi‐model ensemble forecasts of aviation turbulence. Meteorological Applications, 27 (1). e1885. ISSN 1350-4827

[img]
Preview
Text (Open Access) - Published Version
· Available under License Creative Commons Attribution.
· Please see our End User Agreement before downloading.

3MB
[img] Text - Accepted Version
· Restricted to Repository staff only

701kB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1002/met.1885

Abstract/Summary

Turbulence is one of the major weather hazards to aviation. Studies have shown that clear‐air turbulence may well occur more frequently with future climate change. Currently the two World Area Forecast Centres use deterministic models to generate forecasts of turbulence. It has been shown that the use of multi‐model ensembles can lead to more skilful turbulence forecasts. It has also been shown that the combination of turbulence diagnostics can also produce more skilful forecasts using deterministic models. This study puts the two approaches together to expand the range of diagnostics to include predictors of both convective and mountain wave turbulence, in addition to clear‐air turbulence, using two ensemble model systems. Results from a 12 month global trial from September 2016 to August 2017 show the increased skill and economic value of including a wider range of diagnostics in a multi‐diagnostic multi‐model ensemble.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:89111
Publisher:Royal Meteorological Society

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation