Cumulus Cloud Field Morphology and Spatial Patterns Derived from High Spatial Resolution Landsat Imagery

Abstract

Detailed observations of cumulus cloud scales and processes are an essential ingredient in models that deal with (i) high spatial resolution cumulus ensembles; and (ii) parameterization of cloud radiative processes. The present investigation focuses on three aspects of the morphology of cumulus clouds: 1) the inhomogeneity as represented by the size distribution of clouds and cloud ?holes,? 2) the nearest-neighbor relationships regarding their sizes and mutual distances, and 3) the scales of their clustering. Distributionwise, cloud size can best be represented by a mixture of two power laws. Clouds of diameter below 1 km have the slope parameter ranging from about 1.4 to 2.3, while larger clouds have slopes ranging from 2.1 to 4.75. Furthermore, these clouds are bifractal in nature. The break in power law and fractal dimension occurs at a size critical to the cloud-scale processes in the following sense. First, this is the cloud size that makes the largest contribution to the extent of cloud cover. Second, there are indications that this is the size at which clouds begin to modify their environment. Cloud inhomogeneities have significant impact on radiative fluxes. The size distribution of holes in the cumulus clouds studied here have a single slope power law with estimated slopes close to 3; these holes have single fractal dimensions. Furthermore, the results suggest that as the cloud field matures, there is an increase in the number and size of the inhomogeneities along with increasing cloud size. Nearest-neighbor relationships are studied from two different perspectives. First, the nearest-neighbor separation distance is modeled by four probability distributions: lognormal, gamma, extreme-value and Weibull. Lognormal appears to provide the best fit. Second, the nearest-neighbor pair sizes and the associated separation distance are studied using a co-occurrence frequency approach of spatial point processes using second-order statistics. The largest frequency of nearest-neighbor pairs occurs at a distance of 200?300 m, with the largest absolute differences in cloud size found at separations of about 500 m. At larger separations, there is a tendency for the larger clouds to be closer to other large clouds, apparently through the modification of the environment. Nonlinear dependence between the sizes of nearest-neighbor cloud pairs increases with increasing cloud size. Cumulus cloud clustering scales are determined by using the classical Greig-Smith quadrat analysis technique. Clustering scales of about 15, 29, and 59 km are found for most of the ten cloud fields studied.