Enabling Visualization and Geospatial Analysis of Atmospheric Science Data through Python

Python is an open source, easy-to-use programming language to work with atmospheric scientific data, however it can prove challenging to unfamiliar Python and data users. In addition, atmospheric science data are heterogenous in that they are collected across many instruments, stored in a variety of formats and require different software and visualization techniques. Python offers community contributed and tested modules and libraries for not only visualization of these data, but manipulating data into formats compatible within GIS and remote sensing software environments. The Global Hydrology Resource Center Data Active Archive Center (GHRC DAAC) has worked in collaboration with Earth, atmospheric and computer scientists to develop a series of Python-based data recipes in the form of Python scripts and iPython notebooks. These data recipes that instruct users on how to visualize and reformat by georeferencing and gridding data in order to bring it into it into GIS and remote sensing environments for further analysis. This presentation will outline the methods, Python libraries and modules used to generated these data recipes geared towards increasing the interoperability of atmospheric science data across a broad user community.