AN ANALYSIS OF THE EFFECT OF DECREASING THE SIZE RESOLUTION IN 2 TECHNIQUES TO SOLVE THE STOCHASTIC COLLECTION EQUATION FOR GROWING CLOUD DROPS

A comparison is made between the methods for solving the stochastic co llection equation of Berry and Reinhardt, using 72 categories, and the method of moments as improved by Tzivion et al., using only 36 classe s. The computations, carried out for different kernels and several ini tial mean drop radii, showed that the numerical acceleration inherent to the Bleck's method is also present in the approach of Tzivion et al ., but in a weaker form. This acceleration depends on the type of kern el and, for cloud conditions allowing coalescence development, it rema ins between acceptable limits and decreases with time. When the method of moments is run for 72 categories, the numerical acceleration pract ically disappears. Although, in terms of mass storage, the requirement s of both methods are the same, in terms of computational speed, this approach has advantages over Berry and Reinhardt's method for use in c loud models with detailed description of microphysical processes.