A Parallel Visualization Framework For Massive Climate Data

Visualization of climate data helps climate scientists understand the climate evolution pattern, discover the new phenomenon, and predict the weather. It can also benefit ordinary users observe the weather information in an intuitive fashion, and make effective decision. Although there is much software that partially addresses the challenging problem of high-quality climate data visualization, they can hardly handle massive, high resolution and heterogeneous climate data.This thesis presents our effort on designing and implementing of a practical framework, which seeks to meet the requirement of our collaboration researchers in China Meteorological Administration (CMA). The presented framework is capable of handling large-scale and high resolution climate data as well as supporting heterogeneous data. Meanwhile, it provides a new mechanism of multi-user exploration of climate data.This framework is cross-platform and flexible, and is convenient to integrate new features.