Logo Logo
Switch Language to German

Scheck, Leonhard; Frèrebeau, Pascal; Buras-Schnell, Robert and Mayer, Bernhard (2016): A fast radiative transfer method for the simulation of visible satellite imagery. In: Journal of Quantitative Spectroscopy & Radiative Transfer, Vol. 175: pp. 54-67

Full text not available from 'Open Access LMU'.


A computationally efficient radiative transfer method for the simulation of visible satellite images is presented. The top of atmosphere reflectance is approximated by a function depending on vertically integrated optical depths and effective particle sizes for water and ice clouds, the surface albedo, the sun and satellite zenith angles and the scattering angle. A look-up table (LUT) for this reflectance function is generated by means of the discrete ordinate method (DISORT). For a constant scattering angle the reflectance is a relatively smooth and symmetric function of the two zenith angles, which can be well approximated by the lowest-order terms of a 2D Fourier series. By storing only the lowest Fourier coefficients and adopting a non-equidistant grid for the scattering angle, the LUT is reduced to a size of 21 MB per satellite channel. The computation of the top of atmosphere reflectance requires only the calculation of the cloud parameters from the model state and the evaluation and interpolation of the reflectance function using the compressed LUT and is thus orders of magnitude faster than DISORT. The accuracy of the method is tested by generating synthetic satellite images for the 0.6 mu m and 0.8 mu m channels of the SEVIRI instrument for operational COSMO-DE model forecasts from the German Weather Service (DWD) and comparing them to DISORT results. For a test period in June the root mean squared absolute reflectance error is about 10(-2) and the mean relative reflectance error is less than 2% for both channels. For scattering angles larger than 170 degrees the rapid variation of reflectance with the particle size related to the backscatter glory reduces the accuracy and the errors increase by a factor of 3-4. Speed and accuracy of the new method are sufficient for operational data assimilation and high-resolution model verification applications. (C) 2016 Elsevier Ltd. All rights reserved.

Actions (login required)

View Item View Item