Meteorological data modeling and 3D visualization based on adaptive grid structure

Liming Lin, Donghai Huang, Yuda Zhong
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Abstract

Aiming at the problems of high modeling complexity and low rendering efficiency of existing visualization methods of real meteorological cloud data, a 3D visualization method of meteorological cloud data based on adaptive far-field grid structure of region of interest is proposed. Methods The region of interest was extracted to generate an adaptive far-field grid structure, which was applied to cloud particle modeling. The fine resolution of the region of interest was kept, and the number of particles in other regions was optimized. Finally, the rendering of 3D cloud images was completed. Simulation results based on WRF model meteorological cloud data show that the above grid structure can speed up rendering and rendering on the basis of ensuring the rendering quality, and can better display the morphology and structural characteristics of real clouds.
基于自适应网格结构的气象数据建模与三维可视化
针对现有真实气象云数据可视化方法建模复杂度高、渲染效率低的问题,提出了一种基于感兴趣区域自适应远场网格结构的气象云数据三维可视化方法。方法提取感兴趣区域,生成自适应远场网格结构,并将其应用于云粒子建模。在保持感兴趣区域的精细分辨率的同时,优化了其他区域的粒子数量。最后,完成三维云图的绘制。基于WRF模式气象云数据的仿真结果表明,上述网格结构可以在保证绘制质量的基础上加快绘制和渲染速度,并能更好地显示真实云的形态和结构特征。
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