630 Effectiveness of using Gridded Forecast Data in Hyperspectral Radiative Transfer

Wednesday, 9 January 2013
Exhibit Hall 3 (Austin Convention Center)
Steven T. Fiorino, Air Force Institute of Technology, Wright Patterson AFB, OH; and M. F. Via, K. J. Keefer, S. M. Shirey, J. T. Engel, and B. J. Elmore

This study demonstrates the effectiveness of using gridded numerical weather prediction (NWP) data from the NOMADS (NOAA National Operational Model Archive & Distribution System) website in hyperspectral radiative transfer analyses and high energy laser (HEL) mission planning software. The radiative transfer analysis code utilized is the Laser Environmental Effects Definition and Reference (LEEDR) model and the HEL mission planning software is the high energy laser tactical decision aid (HELTDA). Analyses of example HEL mission engagements are described which are based on: (1) geographic location and associated atmospheric effects, defined through the LEEDR model, and (2) laser performance and engagement dynamics via the HELTDA code. These models enable the creation of climatologically- or NWP-derived vertical profiles of temperature, pressure, water vapor content, optical turbulence, and atmospheric particulates and hydrometeors as they relate to line-by-line or band-averaged layer extinction coefficient magnitude at any wavelength from the 350 nm to 8.6 m. The output derived from NWP data are compared to seasonal, generalized boundary layer, and time of day variations for a range of relative humidity percentile conditions to determine optimum efficiency in a specific environment. Climatologically-based aerosol concentrations and optical properties are assumed for all scenarios. Results show that coupling the forecast/nowcast weather data with climatological properties for aerosols and turbulence offers some significant advantages in HELTDA that optimize potential laser weapon engagements, whether air-to-air, air-to-surface, or surface-to-air (or space) scenarios. These advantages are quantified and described.
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