An Efficient Hybrid Method for Animating the Growth of Large-Scale Cumulus-Type Cloud

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We present an efficient method for creating large-scale animations of vertical developing cumulus-type cloud growth. The dynamics of cloud formation, growth, and motion are complex phenomena, and depicting these dynamics remains a significant challenge in the area of simulation and animation of natural phenomena in computer graphics. A novel aspect of this paper is the combination of a physical simulation method and a stochastic simulation method for obtaining an animation of large-scale phenomena with effects that are more natural. The physical simulation method is used to accurately solve fluid dynamics on a relatively small scale and prepare a 3D primitive pattern of a realistic animation of cloud growth. The stochastic simulation method uses 1/fβ noise functions and performs a large-scale simulation of an air current caused by the rising and condensation of water vapor due to the thermal effect. Many copies of the 3D primitive pattern are recursively mapped into the air current to constitute a large-scale continuous cloud growth. This combination of the physical and stochastic simulation methods can animate large-scale phenomena efficiently without enormous computational time and memory. The physical and stochastic simulations are achieved by particle-based methods, and the mapping is applied on simulated particles. Experimental results show that the proposed method efficiently creates realistic animations of large-scale cumulus and cumulonimbus clouds.