Aircraft Turbulence

Definition: Frequent fliers invariably experience turbulence, differential air motions that shake the aircraft and its passengers.

Size: Turbulence that affects aircraft occurs on scales of tens to hundreds of meters.

Duration: Though individual bumps last about a second, the eddies in the air flow that cause the bumps probably last tens of seconds; some flights experience turbulence for many minutes at a time.

Geographic preference: None. Clear-air turbulence is most common in the vicinity of upper air fronts, which are associated with strong three-dimensional wind shears. Clear-air turbulence is also common, and may be severe, in mountain wave situations. Turbulence in convective clouds is taken for granted because of the up-and-down air motions, but pilots try to avoid thunderstorms.

Turbulence is the leading cause of non-fatal injury to flight attendants and passengers. Under the Federal Aviation Administration’s (FAA’s) Safer Skies Program, the Commercial Aviation Safety Team commissioned the Turbulence Joint Safety Analysis Team to study the increasing rate of air carrier turbulence incidents and accidents from 1987 to 2000. The average annual cost of the rare fatality and all non-fatal injuries combined for all airlines is approximately $26 million.

Because of the ephemeral nature of turbulence, its existence is almost always inferred and predicted from the larger-scale wind field. Aircraft experiencing turbulence routinely inform following aircraft about what to expect.

Measurements in clear and cloudy air on the scale of tens to hundreds of meters every few seconds are needed to detect aircraft turbulence. If this is ever to become a practical reality, it may have to be done from the aircraft itself. The prediction of aircraft turbulence will be based on parameterizations (approximations in computer models that account for physical processes too small to be captured on the grid of points where model computations occur) for many years to come. It has yet to be shown that observations of turbulence can lead to better predictions of turbulence in models.

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