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Mountain wave detection as an aviation hazard awareness tool for GOES-R
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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.