Limb Correction of Individual Infrared Channels Used in RGB Composite Products

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Tuesday, 6 January 2015: 2:00 PM
231ABC (Phoenix Convention Center - West and North Buildings)
Nicholas J. Elmer, University of Alabama, Huntsville, AL; and E. Berndt, G. J. Jedlovec, and F. J. LaFontaine
Manuscript (1.1 MB)

RGB (Red-Green-Blue) composites combine images from several spectral channels into one composite image to aid in the quick, real-time analysis of atmospheric processes. However, the limb effect, a result of an increasing optical path length of the absorbing atmosphere between the satellite and the earth as scan angle increases, interferes with the qualitative interpretation of RGB composites at large scan angles. Additionally, limb effects make the comparison of similar products from multiple satellite sensors difficult. Recent work indicates that correcting for limb effects in the basic channel imagery using simple statistical relationships greatly improves the utility of the derived RGB imagery. However, it is hypothesized that the limb correction coefficients vary with respect to latitude, season, surface emissivity, and cloud cover. This presentation will highlight an improved approach to the limb correction of several RGB composite products (Air Mass, Dust, and Fog/Low Cloud) using varying coefficients. The Joint Center for Satellite and Data Assimilation (JCSDA) Community Radiative Transfer Model (CRTM) simulated top of atmosphere brightness temperatures at varying scan angles for infrared channels corresponding to the Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Suomi NPP Visible Infrared Imaging Radiometer Suite (VIIRS), and Meteosat-10 Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensors. A subset of European Center for Medium-Range Weather Forecasts (ECMWF) temperature, specific humidity, and ozone mixing ratio profiles from March 2013 through February 2014 were used as input to the CRTM. To ensure the ECMWF atmospheric profiles were representative of atmospheric conditions, they were compared to corresponding profiles from Aqua AIRS and rawinsondes. The simulated brightness temperatures were used to determine the best fit slope of the linear relationship between the natural logarithm of the cosine of the scan angle and the difference of the simulated brightness temperature at nadir and on the limb. The correction coefficients were then analyzed for variability with respect to latitude, season, cloud cover, and surface type and applied to produce improved limb corrected imagery. Applications of the results will be presented, as well as multiple case studies demonstrating the improved functionality of limb corrected RGB composites.