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Real-time visualization of the East China Sea based on priceton ocean model and volume rendering

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3 Author(s)
Liangying Wei ; School of Ocean and Earth Science, Tongji University, Shanghai, China ; Huiping Xu ; Ding Liu

This paper presents a real-time three dimensional visualization system of the East China Sea, composed by an ocean model with volume rendering technology and a marine GIS system. In the system, the spatiotemporal marine data of East China Sea is retrieved from an ocean modeling called the Princeton Ocean Model (POM), which is a sigma coordinate, free surface ocean model with embedded turbulence and wave submodels, and wet-dry capability. The East China Sea model is implemented on a 1/15 ° × 1/15 ° horizontal curvilinear orthogonal grid with 16 sigma levels. The system rewrites the Princeton Ocean Model on to provide a whole control upon the model. In the rewritten POM code, data calculated from every time step is transferred to the drawing module for the real time visualization; also, users can in turn modulate parameters and setups of the model or reload initial and boundary conditions during the simulation any time they want to. The paper puts its emphasis on the visualization of the three dimensional physical data-fields of the East China Sea, in which the three dimensional physical data comes from every single internal time step while two dimensional physical data like surface elevation comes from every single external time step. With the data calculated, the virtual environment is established on modern OpenGL rendering techniques complex. Volume rendering technology as well as its optimal methods is used to rebuild the three-dimensional ocean data-fields. GPU techniques and C for graphics (Cg) are also used for a better perform of the volume rendering. Finally, the ocean model and its visualization are integrated into a marine GIS system. The system is trying not only to reveal a realistic ocean environment of the East China Sea, but also to reproduce the scene of the distribution of the three dimensional physical scalar data (e.g. temperature) to the life.

Published in:

2010 18th International Conference on Geoinformatics

Date of Conference:

18-20 June 2010