NASA is funding the development of a prototype system to provide aircraft with updates about severe storms and turbulence as they fly across remote ocean regions. Scientists at the U.S. National Center for Atmospheric Research (NCAR) in Boulder, Colorado and colleagues at the University of Wisconsin are developing a system that combines satellite data and computer weather models with advanced artificial intelligence techniques.
The system is designed to help guide pilots away from intense weather. This is a subject of considerable current interest because of the crash of an Airbus A330-200 operating Air France flight AF447 into the Atlantic Ocean on June 1, with the loss of all 228 people on board, as it tried to navigate past large thunderstorms in a tropical region beyond the scanning range of land-based radar.
A variety of NASA spacecraft observations are being used in the project, including data from NASA’s Terra, Aqua, Tropical Rainfall Measuring Mission, CloudSat and CALIPSO satellites. The prototype system will identify areas of turbulence in clear regions of the atmosphere as well as within storms. It is on track for testing next year.
Pilots on selected transoceanic routes will receive real-time turbulence updates and provide feedback. When the system is finalized, it will provide pilots and ground-based controllers with text-based maps and graphical displays showing regions of likely turbulence and storms.
NCAR currently provides real-time maps of turbulence at various altitudes over the continental United States. Scientists are building on this expertise to identify turbulence over oceans. The team has created global maps of clear air turbulence based on global computer weather models that include winds and other instabilities in the atmosphere. Drawing on satellite images of storms, the scientists also have created global views of the tops of storm clouds. Higher cloud tops often are associated with more intense storms, although not necessarily with turbulence.
The next step is to pinpoint areas of possible turbulence within and around intense storms. The team will study correlations between storms and turbulence over the continental United States, where weather is closely observed, and then infer patterns of turbulence for storms over oceans.
In addition to providing aircraft and ground controllers with up-to-the-minute maps of turbulence, the NCAR team is using an artificial intelligence technique, known as “random forests”, to provide short-term forecasts. Random forests have proven useful for forecasting thunderstorms over land. They consist of many decision trees, each of which gives a yes-or-no decision on crucial elements of the storm at future points in time and space. This enables scientists to forecast the movement and strength of the storm during the next few hours.