An Automated Method of Predicting Clear-Air Turbulence

Clear-air turbulence (CAT) prediction is vitally important to military aviation and the successful completion of Department of Defense (DoD) operations such as air to air refueling and new national defensive weapon systems such as directed energy platforms. The unique mission requirements of military aircraft often require strict avoidance of turbulent regions. Traditionally, weather forecasters have found it difficult to accurately predict CAT. In order to forecast regions where CAT might occur, forecasters must first determine the location of breaking waves caused by either Kelvin-Helmholtz instabilities or topographically forced internal gravity waves (mountain waves) in the atmosphere. The United States Air Force (USAF) 15th Operational Weather Squadron (15th OWS) requested an updated method of predicting CAT and this request was ranked as one of the highest priority research needs by the HQ USAF Director of Weather, Deputy Chief of Staff for Air and Space Operations. A new method of forecasting turbulence was developed in this work and the operational model was delivered to the 15th OWS for immediate inclusion into their operations. This method combines output from the Knapp-Ellrod index and the Naval Research Laboratory s Mountain Wave Forecast Model (MWFM) onto a single chart. Displaying these tools together allows forecasters to view both causes of CAT simultaneously. Furthermore, a new visualization tool is developed that allows a forecaster to view several layers at the same time as well as a composite chart to greatly reduce the time required to produce turbulence charts by OWS forecasting centers worldwide. Tests of forecast accuracy, as determined by pilot reports (PIREPS), between charts currently produced by USAF OWSs and this new method were compared, with the new method producing far superior forecast results. This method revolutionize