Dynamic typhoon visualization based on the integration of vector and scalar fields

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Abstract

Typhoons and other marine meteorological disasters often bring significant losses to human beings, and their data are characterized by multiple sources and scales, making traditional visualization methods unable to accurately express the characteristics and movement trends of the disasters. To address the above problems, this study proposes a typhoon dynamic visualization method based on the integration of vector and scalar fields. To address the above problems, this study proposes a typhoon dynamic visualization method based on the integration of vector and scalar fields. The method uses the ray casting method to visualize the volume rendering of typhoon scalar data, proposes a hybrid interpolation method to improve the visualization efficiency, and introduces the Sobel operator to achieve the edge enhancement of the volume rendering effect. Meanwhile, a particle system approach is used for dynamic visualization of typhoon vector data, where the tedious particle motion calculation is divided into two parts: parallel tracking and dynamic rendering to improve the visualization efficiency, and the Lagrangian field representation of the particle system is achieved. The experimental results show that the typhoon visualization method proposed in this study has better comprehensive visual effects, with a rendering frame rate greater than 44, and is able to stably and smoothly express the continuous spatio-temporal dynamic visualization features of typhoon.This study is conducive to the understanding of the evolution law of marine meteorological disasters and the adoption of disaster prevention and mitigation measures, and is of great significance for the expression of marine meteorological data such as typhoons and the analysis of their spatial and temporal changes.

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Feng, C., Qin, T., Ai, B., Ding, J., Wu, T., & Yuan, M. (2024). Dynamic typhoon visualization based on the integration of vector and scalar fields. Frontiers in Marine Science, 11. https://doi.org/10.3389/fmars.2024.1367702

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