This guest post is written by Hannah Aizenman, one of our Google Summer of Code students.
If you’ve been interested in climate for a while (or longer than 15 minutes) you’ve probably heard of the hockey-stick, or the East Anglia email controversy, or seen yet another rant on climate change loaded with references to half-understandable topics discussed in papers you’d need a degree in geophysics or earth science to hope to understand, and a big old graph that seems to be nothing more than lines or a map and somewhat circle-like shapes. Even though climate data currently seems somewhat inscrutable, many people in the climate community want the data, and more importantly the science, to be understandable; therefore they are starting to allow anyone with an internet connection to interact with and visualize their data and tools, because one of the best ways to learn about something is to play with it.
My project for GSOC is to open up the process of creating visualizations to anyone who happens to stumble onto the Common Climate Project (CCP) web page, so that he or she can learn how choices in parameters and restrictions on the data, not magical manipulation and fabrication, yield graphs similar to the ones in all these papers.
The plan is to create a tool for generating graphs using data sets created and studied by members of the CCP, to host it on the CCP website, and to open-source it so that any lab can reuse it to make their own data easily explorable. The tool’s backend will be a wrapper for the brilliant matplotlib library, and it’ll also be open-sourced so that anybody can pick it up to make climate data graphs in python without having to learn the intricacies of the matplotlib library. It’ll also hopefully make a good demo for how to use matplotlib to make climate data graphs, so anybody with interest and a smidgen of programming skills can push the graphs further and maybe even contribute back more functions for doing visualizations.