| Summary: | Abstract Nowadays, due to the expansion of people’s living ranges and the impact of human life on the natural environment, climate changes fiercely than before. In order to observe the changing climate environment accurately, multi-modal sensors are used to collect the various data around us, and we could analyze and predict the weather based on these collected data. One of the applications is 3D visualization simulation, and the 3D visualization simulation of cloud data has always been the research hotspot in the field of computer graphics and meteorology. Currently, it is a key challenge to resolve the problems of 3D cloud simulation, such as reducing complexity of modeling and computation and improving the real-time performance. Technically, a method for data modeling and optimizing based on Weather Research and Forecasting (WRF) is proposed in this paper, aiming to solve the problems of the existing 3D cloud simulation and realize 3D virtual simulation of real-world cloud data. According to the characteristics (e.g., color, size, shape) of the cloud, the spherical particle system is designed to model, and the initial color, size, shape, and other attributes are given to these spherical particles to realize the modeling of WRF cloud data. From the perspective of new particles’ generation, the level of detail (LOD) technique, based on the relationship between the quantity of new generated spherical particles and the distance of the viewpoint, is used to change the quantity of new particles generated in real time according to the distance of the simulated scene distance. Finally, illumination model is introduced to render and simulate the modeling particles. Experimental simulation results verify the effectiveness of this method in improving the modeling and rendering speed of cloud data as well as the fidelity of the 3D virtualization model.
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