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Wireless communications occurring in and about structures, vehicles, and other non-ideal environments are susceptible to channel fading due to multi-path conditions. For mobile communications, channels are typically modeled as Rician or, as a worst-case, Rayleigh. Emerging wireless systems, e.g., wireless sensor networks, have been shown to experience fading even more severe. We propose a metric, the 10% fade depth, by which large channel data sets can be readily distilled to characterize the fading environment be it Rician or hyper-Rayleigh. The metric is compared with the K-factor and applied to illustrate benefits of selection and polarization diversity.