Statistical Characterization and Modeling of Raindrop Spectra Time Series for Different Climatological Regions

Abstract

A large data set of raindrop size distribution (RSD) measurements collected with the Joss-Waldvogel disdrometer (JWD) and the 2-D video disdrometer (2DVD) in the U.K., Greece, Japan, and the U.S. are analyzed and modeled. This work extends a previous effort devoted to the exploitation of U.K. data and the design of a stochastic procedure to randomly generate synthetic RSD intermittent time series. This study seeks to: (1) explore the differences of RSD-derived moments for distinct hydroclimate regions, ranging from tropics to subtropics and mid and northern latitudes; (2) compare the governing parameters of the normalized gamma RSD for both stratiform and convective events and perform a sensitivity analysis by using different best fitting techniques; (3) exploit the time-correlation structure of the estimated RSD parameters as the input of a vector autoregressive stationary model used to simulate time series (or horizontal profiles) of RSDs and, consequently, its moments as the rain rate and concentration; and (4) characterize the distribution of the inter-rain duration and rain duration to design a semi-Markov chain to represent the intermittency feature of the rainfall process in a climatological framework. This climatological analysis and the related stochastic RSD generation model may find useful applications within both hydrometeorology and radio propagation.