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NASA Research Will Help Aircraft Avoid Ocean Storms and Turbulence

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 National Center for Atmospheric Research (NCAR) in Boulder, CO — in partnership with the University of Wisconsin — are developing a system that combines satellite data and computer weather models with artificial intelligence techniques.

“Turbulence is the leading cause of injuries in commercial aviation,” said John Haynes, program manager in the Earth Science Division’s Applied Sciences Program at NASA Headquarters in Washington, DC. “This new work to detect the likelihood of turbulence associated with oceanic storms using key space-based indicators is of crucial importance to pilots.”

The system is designed to help guide pilots away from intense weather. 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. 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.

“Pilots currently have little weather information as they fly over remote stretches of the ocean, which is where some of the worst turbulence occurs,” said scientist John Williams, one of the project leads at NCAR. “Providing pilots with at least an approximate picture of developing storms could help guide them safely around areas of potentially severe turbulence.”

In addition to providing aircraft and ground controllers with up-to-theminute maps of turbulence, the NCAR team is turning to an artificial intelligence technique, known as “random forests,” to provide short-term forecasts. Random forests consist of many decision trees that each cast a yes or no “vote” 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.

For more information, visit www.nasa.gov/home/hqnews/2009/ jul/HQ09-154_Turbulence_Research.html.