We developed a procedure for using data for attenuation σ of the marine atmosphere at λ = 0.55 μm and Ångström parameter α in the visible range for the estimation of aerosol particle size spectrum. We evaluated the aerosol microstructure in the marine atmospheric boundary layer (MABL). To eliminate the effect of the upper troposphere and stratosphere, we assumed that the optical characteristics of the microstructure are average for the typical marine atmosphere. The sought-for MABL microstructure is parameterized by the sum of two fractions, each having a log-normal distribution (the fine and large components). The problem amounts to determining six unknown parameters from two characteristics. In accordance with experimental data as well as with theoretical aerosol models, the total particle concentration n and the fraction of the large component c2 are assumed to be constant for the central regions of the world ocean. In this way, the problem can be reduced to the determination of the acceptable value area of the remaining four parameters. For all models situated in this area, values of σ and α fall within some intervals Δσ and Δα, specific for each aerosol type. Since the problem is ambiguous, the number of models comprising an acceptable ensemble is great. So this number is equal to 5972 in the example that illustrates our procedure. It is noteworthy, however, that all the models entering the ensembles have a similar microstructure within the active radius interval of 0.02–3 μm, which is the main interval that governs the transmittance in the 0.3–1 μm spectral range. The average curve that can be plotted for the entire ensemble can be used as a solution to the problem, which is the main result of this study. We are also concerned with how aerosol transmittance measurements in one of the infrared channels could be used to diminish the ambiguity of the problem. The answer depends on the specific aerosol structure. In most cases, additional IR data in one channel barely decreases the ambiguity of the problem. However, such data might be useful for some other distributions. We consider the effect of six IR channels in our example.
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