This work determines the performance of a five-channel ice cloud retrieval scheme in context of numerical synthetic experiments and real-world data and examines the implications of these results on the global retrieval of ice cloud microphysical properties over the global oceans. This estimation-based scheme, designed from information content principles, uses a rigorous, state-dependent error analysis to combine measurements from the visible, near-infrared, and infrared spectral regions. In the synthetic experiments, the five-channel scheme performed as well or better in terms of retrieval bias and random error than the traditional split-window and Nakajima and King bispectral retrieval techniques for all states of the atmosphere. Although the five-channel scheme performed favorably compared to the other methods, the inherently large uncertainties associated with ice cloud physics dictate typical retrieval uncertainties in both IWP and effective radius of 30–40%. These relatively large uncertainties suggest caution in the strict interpretation of small temporal or spatial trends found in existing cloud products. In MODIS and CRYSTAL-FACE applications, the five-channel scheme exploited the strengths of each of the bispectral approaches to smoothly transition from a split-window type approach for thin clouds to a Nakajima and King type approach for thick clouds. Uniform application of such a retrieval scheme across different satellite and field measurement campaigns would provide a set of consistent cloud products to the user community, theoretically allowing the direct comparison of cloud properties for the climate processes studies found throughout the literature.
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