Application of a Monte Carlo integration method to collision and coagulation growth processes of hydrometeors in a bin-type model

New algorithms for calculating the collision-coagulation growth process of hydrometeors were developed and implemented into a bin cloud microphysics model in order to improve its computational efficiency. Computation of collision-coagulation growth is a bottleneck in the bin-type cloud microphysics calculation that takes a large amount of computing time. Improvement in the efficiency of the process can significantly reduce computing time. In this study, a new stochastic algorithm was developed and implemented into the collision-coagulation growth process of a nonhydrostatic cloud model. Simulations showed that the computing time was reduced by about 90%. We verified that the error range of the simulation results from the new scheme is much smaller than the internal variability involved the traditional bin-type model and also in the real atmosphere. The newly developed scheme was implemented into the mesoscale operational model of the Japan Meteorological Agency. The precipitation field was accurately simulated in a numerical weather prediction simulation.