An application of fractal box dimension to the recognition of mesoscale cloud patterns in infrared satellite images

Mesoscale cloud patterns are analyzed through the application of fractal box dimensions. Verification of fractal properties in satellite infrared images is carried out by computing box dimensions with two different methods and by computing the fraction of cloudy pixels for two sets of images: 174 are considered the ‘‘control series,’’ and 178 (for verification) are considered the ‘‘test series.’ ’ The main instabilities in the behavior of such dimensions are investigated from the simulation of circles filling space in several spatial distributions. It is shown that the box dimensions are sensitive to the increase of the area covered and to the spatial organization— that is, the number of cells, the spatial clustering, and the isotropy of the distribution of pixels. From a principal components analysis, the authors find six main patterns in the cloudiness for the control series. The three main patterns related to enhanced convection are the massive noncircular spread cloudiness, the highly isotropic distribution of cloud in several cells, and the most circular pattern associated with mesoscale convective com-plexes. The six patterns are separated into a cluster analysis, and the properties of each cluster are averaged and verified for the test series. This method is a simple and skillful procedure to recognize mesoscale cloud patterns in satellite infrared images. 1