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Parvis: Parallel Analysis Tools and New Visualization Techniques for Ultra-Large Climate Data Sets

The large volume of data currently produced by climate models is overwhelming the current, decades-old visualization workflow. The traditional methods for visualizing climate output also have not kept pace with changes in the types of grids used, the number of variables involved, and the number of different simulations performed with a climate model or the feature-richness of high-resolution simulations.

The bottleneck to producing climate model images is not always the drawing of the image on the screen but rather the calculations that must be performed on the climate model output before an image can be made. Parvis will speed up this post-processing, or analysis, phase of climate visualization by developing a new Parallel Climate Analysis Library (ParCAL) that will vastly improve the speed of climate data analysis compared to the current serial tools. ParCAL will build on currently available software technology that will also permit calculations to be performed in parallel on many different numerical grids. We will interface ParCAL with popular climate modeling tool the NCAR Command Language ( NCL).

We are also exploring the use of existing tools such as  Swift and  Pagoda to bring immediate speed-ups to climate model post-processing workflow.

ParCAL development

We will be building ParCAL on top of the  MOAB,  Intrepid, and  PNetCDF libraries.

Current workflow improvements

Trac Starting Points

For a complete list of local wiki pages, see TitleIndex.