Predicting the bump

A forecasting method could help pilots chart new courses around patches of rough but clear air that can cause the sudden bumpiness and violent plummeting of aircraft.



Commercial aircraft encounter severe turbulence about 5,000 times each year, and the majority of these occur 10,000ft above the Earth’s surface. The new method gives pilots a way to avoid turbulence that is not associated with nearby thunderstorms or significant cloudiness.



To do so, it predicts energy associated with gravity waves – phenomena in the atmosphere that look like ocean waves but which can occur in clear air.



They can be created by air flow over mountains, frontal boundaries or other causes and result in what’s known as Clear Air Turbulence (CAT).



But the type of gravity wave that John Knox, an assistant professor in the department of geography at the University of Georgia‘s Franklin College of Arts and Sciences identified as a possible source of bumpiness comes from a different source – they are spontaneously generated and associated with jet streams at high altitudes, near cruising levels for aeroplanes.



There are predictive models in use now, and an improved version of the Graphical Turbulence Guidance (GTG) algorithm, currently the best CAT forecasting method, will soon be online for airline pilots, said Knox. But he noted that even the GTG does not have some of the desirable features of the method he has developed.



The new method is based on the Lighthill-Ford theory of spontaneous imbalance, developed by a British theoretician in the early 1990s. Knox and his colleagues spent several years turning this theory into a forecast tool.



The team first simplified the theory then developed an algorithm to use it to make predictions of turbulence. The algorithm was next tested on five months’ worth of high-resolution weather forecast model output from 2005-2006. The researchers then compared the algorithm’s prediction of turbulence to actual pilot observations of it.



The results of this statistical analysis demonstrated that the team’s method performed better than the best methods of CAT forecasting available during that period, said Knox.



He added that adoption of the new method could potentially create ‘major improvements in CAT forecasting’. Thousands of passengers who are fearful of ‘things that go bump in the flight’ hope he is correct.