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Cloud remote sensing with EPIC/DSCOVR observations: A sensitivity study with...

Gao, M., P. Zhai, Y. Yang, and Y. Hu (2019), Cloud remote sensing with EPIC/DSCOVR observations: A sensitivity study with radiative transfer simulations, J. Quant. Spectrosc. Radiat. Transfer, 230, 56-60, doi:10.1016/j.jqsrt.2019.03.022.
Abstract: 

The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) views nearly the whole sunlit face of the Earth with 10 spectral bands ranging from the UV to the nearinfrared, including two oxygen absorbing bands centered at 764 nm (A-band) and 687.75 nm (B-band). Clouds are among the primary remote sensing targets using EPIC images because of their important impacts on the Earth’s radiation budget. In order to facilitate the EPIC cloud data product development, we have built a radiative transfer simulator featuring flexible cloud microphysical parameters, gas absorptions, and the instrument line shape functions for each EPIC band. The radiative transfer simulator is used to explore the sensitivity of EPIC observations on liquid-phase cloud microphysical parameters, including optical depth, geometric thickness, and cloud top height. We found that the ratios of the reflectances in the oxygen A and B bands to their respective continuum measurements can be used to increase the confidence level of cloud masking over scenes with sun-glint. In addition, the 388 nm band can be used to differentiate low and high clouds with the uncertainty of roughly 2–3 km. Combining this information with the oxygen absorption bands, the cloud geometric thickness can be obtained with the rough uncertainty of 3–4 km.

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Mission: 
DSCOVR