Improving Understanding and Diagnosis of Jet-Stream Turbulence

Turbulence is the leading cause of weather-related aircraft incidents and the underlying cause of many people's fear of air travel. One estimate of turbulence indicates over 63,000 encounters with moderate-or-greater turbulence and 5000 encounters with severe-or-greater turbulence annually. In 34 years, the US reported 883 fatalities associated with turbulence. Turbulence can also damage aircraft, by tearing off winds and engines, as happened in an extreme turbulent event over Colorado in 1992. The economic costs of turbulence are more than just injuries and damage, with flight delays, inspections, repairs, and post-accident investigations also taking their toll. Estimates of the total cost to US carriers alone are nearly $200 million annually. Although the costs of turbulence to UK/EU airlines and over EU airspace are not available, assuming the occurrence of turbulence and the density of air travel are similar to that over the US and that the EU is about the same size as the US, then costs should be comparable.

Moreover, climate change is exacerbating the problem. Midlatitude turbulence diagnosed from climate projections increase under increasing atmospheric carbon dioxide, with a doubling or trebling later this century. Thus, the costs of turbulence due to climate change will lead to a substantial increase in turbulent events. Clear-air turbulence, abbreviated as CAT, is turbulence that occurs away from clouds in clear air. CAT is difficult for pilots to detect and for forecasters to predict. One of the reasons that it is difficult to predict is that CAT is believed to have multiple sources and no single forecasting tool works for all of the sources.

One suspected source of CAT is the release of hydrodynamic instability, an imbalance between different forces in the atmosphere that lead to large and rapid accelerations of the air. Such accelerations may produce atmospheric phenomena such as roll-type circulations or wave-like motions that result in CAT. Presently, we have an incomplete understanding of how hydrodynamic instability forms, releases, produces turbulence, and returns to stability.

In this proposed research, we will look at observations of turbulence from three sources. One is from a vertically pointing radar in Wales that can detect turbulence at the jet stream. A second one is from pilots manually reporting turbulence. A third is from automated instrumentation aboard aircraft. We will use these observations to understand the conditions in which CAT forms and its relationship to hydrodynamic instability.

Because these observations are snapshots in time from single measurements, computer model simulations of real and idealised weather phenomena that produce CAT will be critical to determine how the instability forms, how the instability and resulting turbulence evolves, and how the atmosphere returns to balance after the release of the instability. Within the context of the results from the observations, we will construct the life cycle of CAT from its origin, to its growth, to its demise.

Given these new insights, we will develop tools for model output (called diagnostics) to quantify the impacts from the release of the instability and evaluate the performance of these diagnostics over North America, the North Atlantic Ocean, and Europe. In this way, improved understanding of the CAT life cycle will lead to better predictions of jet-stream turbulence, as well as reduced costs and injuries to passengers and flight crew.