Uncertainties in cloud phase and optical thickness retrievals from the Earth...

Meyer, K. G., Y. Yang, and S. Platnick (2016), Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC), Atmos. Meas. Tech., 9, 1785-1797, doi:10.5194/amt-9-1785-2016.
Abstract: 

This paper presents an investigation of the expected uncertainties of a single-channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud-temperature-threshold-based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC Sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phasedependent CER values. Uncertainty estimates are derived by comparing the single-channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a singlechannel COT retrieval is feasible for EPIC. For ice clouds, single-channel retrieval errors are minimal (< 2 %) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10 %, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

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Research Program: 
Atmospheric Composition Modeling and Analysis Program (ACMAP)
Mission: 
DSCOVR-EPIC