Abstract
UV-CDAT is a python-based set of tools that enable scientists to do end-to-end scientific data analysis and visualization within Python. UV-CDAT allows for data I/O over multiple scientific data formats (such as NetCDF, Grib2, pp, etc..). UV-CDAT understands, maintains and takes advantage of CF metadata. This drastically reduces the amount of data “preparation” scientists have to do before they can work with data. Results can be easily saved to a file or as one, two, or three-dimensional plots. This poster exposes some of UV-CDAT core features as they are used as the base tool for ACME workflow data analysis and visualization needs.