Volume Rendering Multivariate Data to Visualize Meteorological Simulations: A Case Study

نویسندگان

  • Joe Michael Kniss
  • Charles D. Hansen
چکیده

High resolution computational weather models are becoming increasing complex. However, the analysis of these models has not benefited from recent advancements in volume visualization. This case study applies the ideas and techniques from multi-dimensional transfer function based volume rendering to the multivariate weather simulations. The specific goal of identifying frontal zones is addressed. By combining temperature and humidity as a multivariate field, the frontal zones are more readily identified thereby assisting the meteorologists in their analysis tasks.

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تاریخ انتشار 2002