  Fractals have been at the heart of geophysical and geospatial studies in the
recent past. We examine the emergent fractal character of water vapor
distributions above the surface of the Earth as a function of both image
resolution (number of pixels) and moisture content percentile. We calculate
physically relevant quantities such as fractal dimension, number of clusters,
and size of the largest cluster with varying vapor percentile using
computational methods and algorithms. Our analysis unravels a potential
multi-fractal character of the data which we construct using the box-counting
method to calculate the generalized dimension. We examine the nature of the
percolation that occurs as the vapor percentile is varied and comment on the
universality class of the transition. We test the applicability of Korcak's law
on our system and determine the quality of the fit using the
Kolmogorov-Smirnoff statistic. We show that the fractal character of the
distribution is exact as a function of image resolution and approximate in some
regimes as a function of the vapor percentiles.
