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Mountain wave detection as an aviation hazard awareness tool for GOES-R
Anthony Wimmers, CIMSS/Univ. of Wisconsin, Madison, WI; and W. F. Feltz
In a recent study, The National Aviation Safety Data Analysis Center (NASDAC) reported 548 aircraft accidents due to turbulence in the United States over a ten-year period, 115 of which involved fatalities. Sixteen of these accidents directly cite mountain wave turbulence as the cause. Mountain waves are a type of gravity wave caused by the vertical displacement of air in the lee of a mountain ridge, and they cause hazardous flight conditions during wave-breaking, interference or extreme amplitudes. The phenomena are often observed by satellite, and notable cases seen in satellite images often relate directly to collocated commercial aircraft observations of high “Eddy Dissipation Rate,” which, in spite of its name, is a measure of sudden and dangerous inertial disturbances experienced by the aircraft.
The GOES-R Algorithm Working Group includes the detection of aviation hazards among its responsibilities; however, the need remains for a product that detects mountain waves as a flight-support tool. In this project, we employ a newly developed method for detecting mountain waves for implementation as a mountain wave aviation hazard awareness product for GOES-R. Our new method is an image processing algorithm that accurately detects wave patterns in the water vapor channel imagery of the GOES-12 imager and MODIS instruments, and reports their wavelength, direction and intensity. It operates in clear as well as cloudy signal. The product is validated with in situ Eddy Dissipation Rate data. In addition, the benefits of expanding this tool to the multi-channel water vapor bands of GOES-12 will be discussed.
Poster Session , Poster Session - GOES-R
Wednesday, 20 January 2010, 2:30 PM-4:00 PM
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