Testing the two-layer model for correcting near-cloud reflectance enhancement using LES/SHDOM-simulated radiances

Wen, G., A. Marshak, T. VĂ¡rnai, and R.C. Levy (2016), Testing the two-layer model for correcting near-cloud reflectance enhancement using LES/SHDOM-simulated radiances, J. Geophys. Res., 121, 9661-9674, doi:10.1002/2016JD025021.
Abstract

A transition zone exists between cloudy skies and clear sky; such that, clouds scatter solar radiation into clear-sky regions. From a satellite perspective, it appears that clouds enhance the radiation nearby. We seek a simple method to estimate this enhancement, since it is so computationally expensive to account for all threedimensional (3-D) scattering processes. In previous studies, we developed a simple two-layer model (2LM) that estimated the radiation scattered via cloud-molecular interactions. Here we have developed a new model to account for cloud-surface interaction (CSI). We test the models by comparing to calculations provided by full 3-D radiative transfer simulations of realistic cloud scenes. For these scenes, the Moderate Resolution Imaging Spectroradiometer (MODIS)-like radiance fields were computed from the Spherical Harmonic Discrete Ordinate Method (SHDOM), based on a large number of cumulus fields simulated by the University of California, Los Angeles (UCLA) large eddy simulation (LES) model. We find that the original 2LM model that estimates cloud-air molecule interactions accounts for 64% of the total reflectance enhancement and the new model (2LM + CSI) that also includes cloud-surface interactions accounts for nearly 80%. We discuss the possibility of accounting for cloud-aerosol radiative interactions in 3-D cloud-induced reflectance enhancement, which may explain the remaining 20% of enhancements. Because these are simple models, these corrections can be applied to global satellite observations (e.g., MODIS) and help to reduce biases in aerosol and other clear-sky retrievals.

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Research Program
Radiation Science Program (RSP)
Mission
CALIPSO

 

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