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

Liming Lin; Donghai Huang; Yuda Zhong

doi:10.1117/12.2671570

16 March 2023 Meteorological data modeling and 3D visualization based on adaptive grid structure

Liming Lin, Donghai Huang, Yuda Zhong

Proceedings Volume 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022); 125930I (2023) https://doi.org/10.1117/12.2671570
Event: 2nd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 2022, Guangzhou, China

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.

Citation Download Citation

Liming Lin, Donghai Huang, and Yuda Zhong "Meteorological data modeling and 3D visualization based on adaptive grid structure", Proc. SPIE 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 125930I (16 March 2023); https://doi.org/10.1117/12.2671570

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