Measuring Clustering in Clouds Using Non-Rayleigh Signal Statistics

Abstract

Abstract The clustering or clumping of droplets appears to be nearly ubiquitous in clouds. Clustering likely plays roles in a number of different physical processes, from the growth of hail, to snow aggregation, to the growth of raindrops, to cloud radiation, and even to what one means by a size distribution. Of more immediate concern, clustering may, at times, affect aircraft icing by introducing important fluctuations in the concentration of supercooled cloud water sufficient to alter the density of the ice collected, and hence, the aerodynamics of the wing (lift). Yet, the intensity of clustering in clouds is spatially and temporally variable and not easy to measure. What few observations there are have been restricted to one-dimensional aircraft measurements sampling very tiny volumes. It would be useful to have a method for measuring clustering over an area and to identify regions of significant clustering that aircraft should avoid during icing conditions, for example. A radar technique based upon a scanning procedure that uses non-Rayleigh signal statistics for quantifying clustering intensity in clouds is proposed. Such observations may enhance the safety of aircraft flying in icing conditions and may elucidate the spatial organization of clustering in clouds. Such measurements appear to be within current technological capabilities.