Using Satellite, NWP, and Atmospheric Refraction Assessments to Enhance Radiative Transfer

This study merges gridded numerical weather prediction (NWP) data from the NOMADS (NOAA National Operational Model Archive & Distribution System), satellite data from the Atmospheric Infrared Sounder (AIRS), the Advanced Microwave Sounding Unit (AMSU), and Moderate-Resolution Imaging Spectroradiometer (MODIS) sensor suites, and makes comparisons to doppler radar data from NOAA's NEXRAD network and data from a Leosphere R-MAN 510 ultraviolet LIDAR (LIght Detection and Ranging) system to enhance radiative transfer modeling, inclusive of atmospheric refraction effects, and demonstrates the implications for remote sensing and laser propagation applications. The Laser Environmental Effects Definition and Reference (LEEDR) model's radiative transfer code was modified to ingest current and/or archived world-wide gridded numerical weather and satellite data, as well as probabilistic climatological information, thus enabling multi-dimensional realistic atmospheric profiles for traditional extinction analysis as well as more comprehensive light refraction and path radiance calculations. Implications for remote sensing applications are drawn directly from LEEDR and those for laser propagation by way of world-wide effectiveness analyses using the High Energy Laser End to End Operational Simulation (HELEEOS) and High Energy Laser Tactical Decision Aid (HELTDA). Collectively, these models enable the creation and application of numerically- or remote sensor-derived 4D 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 350 nm to 8.6 m. Climatologically-based aerosol concentrations and associated optical properties are assumed for all scenarios. Results demonstrate novel methods to obtain temperature, winds, turbulence, cloud base and top heights, and aerosol extinction values through a combination of NEXRAD and satellite-based remote sensor data. Structure functions of temperature, CT2, refractive index, Cn2, and wind velocity, Cv2, are derived over large volumes and compared to radar-derived data. Additionally, comparisons to ground-based LIDAR measurements and enhancements via numerical weather data are presented.