This paper provides an inter-comparison study of various ground-based cloud retrieval algorithms that have been
developed to obtain cloud water content. The retrieval algorithms are classified into three types, statistical
parameterization algorithm, physical retrieval algorithm, and optimal iteration method. Analyses indicate that physical
retrieval algorithms are theoretically accurate, however, assumptions used in these methods make it challenging for them
to obtain highly reliable results. Empirical parameterization methods are simple and can be easily applied. However,
these methods are generally based on very limited cloud samples for certain types of clouds and locations, they have
much larger uncertainties. In contrast, the optimal iteration method seems to have relatively higher accuracies since the
retrieval results make the forward model simulations match observations. However, the accuracy of optimal iteration
method is highly dependent on the reliability of the forward models and the a priori information.
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