Community Tools for the Analysis and Visualization of Geoscientific Data (invited)

We present two Python modules developed in the Visualization and Enabling Technologies Section at NCAR for reading, writing, and visualizing geoscientific data. PyNIO provides robust file input and output for a number of commonly used scientific formats, including NetCDF, various HDF/HDF-EOS formats, shapefiles, and GRIB versions 1 and 2. PyNGL produces high quality custom-tailored 2D visualizations and has built-in support for unique grid structures. These tools are developed in parallel with NCL (NCAR Command Language), which is a self-contained scripting language like Python. The programming style is remarkably similar, allowing users easily to move between the NCL and Python languages. These tools are under continuous development, driven by a large and active international community. Extensive online documentation provides step-by-step tutorials for quickly acquiring the basics and moving on to more advanced endeavors. Current priorities include support for ultra-large climate datasets and the newest versions of the NetCDF and HDF file formats, and the ability to visualize vector data on triangular meshes.

These tools play an essential role in the post-processing infrastructure of a growing number of high-volume providers of atmospheric, ocean, and climate data. They are used by thousands of users from over 120 countries at foreign and domestic universities, national labs, supercomputing centers, government and military sites, weather forecast offices, research companies, and commercial entities. The prominent users include climate modelers, but other disciplines are also represented including atmospheric research, microbiology, hydrology, physics, astronomy, plasma simulation, and social sciences.

We will present an overview of these tools, show representative code samples, display a variety of scientific visualizations, and discuss future plans.