The Grid Analysis and Display System (GrADS), , developed by the Center for Ocean-Land-Atmosphere Studies (COLA), is an interactive desktop tool for easy access, manipulation, and visualization of earth science data. The power of GrADS stems from its easy of use, speed and availability on a wide number of platforms. The Python interface to GrADS (PyGrADS) is an alternative method of scripting GrADS that can take advantage of the unique capabilities of Python, and gives you access to a wealth of numerical and scientific software available on this platform.

PyGrADS uses the same 5-Dimensional data environment of GrADS: the four conventional dimensions (longitude, latitude, vertical level, and time) plus an optional 5th dimension that is designed to be used for ensembles. Because PyGrADS is based on GrADS, it supports many data file formats, including binary (stream or sequential), GRIB (version 1 and 2), NetCDF, HDF (version 4 and 5), and BUFR (for station data). PyGrADS has the ability to use the very fast native GrADS visualization capabilities, or alternatively use the power of Matplotlib or VTK for volumetric visualizations.

PyGrADS offers a generic GrADS class that can be used for general purpose python scripting, as well as a customization of the popular IPython interpreter that has the same look-and-feel of the classic GrADS command line interface. This interactive environment is designed to facilitate the learning of python by regular GrADS users.

In this talk we will present a general overview of the capabilities of PyGrADS, followed by 2 real world applications. First, we will demonstrate how PyGrADS can be used to compare gridded fields from the GEOS-5 global forecasting system to in-situ and airborne measurements gathered during NASA's DISCOVER-AQ field campaign. We will conclude with a discussion of how PyGrADS has been used to implement a web-based GrADS client that runs entirely in your browser.