PyAOS

Editor’s Note: This post, by Kimberly Hoogewind of Purdue University, is the first in a series of short posts about the talks given at the Third Symposium on Advances in Modeling and Analysis Using Python, held at the 93rd AMS Annual Meeting, from January 7–9, 2013, in Austin, TX. The full program of the Symposium, with links to abstracts and presentation screencasts are available online.

With the field of atmospheric science becoming an increasingly more computing- and data-intensive discipline, it should come as no surprise that this translates to a higher demand for scientists to possess programming/scripting, data management, analysis, and visualization skills. For many though, the thought of transforming into a hybrid meteorologist/computer programmer can be very overwhelming. Kelton Halbert’s talk at the 2013 AMS Python Symposium entitled “Forecasting and Analysis with Python: So Easy, a Caveman Can Do It,” however, demonstrated that learning to program with Python does not have to be a tremendous undertaking, especially for those with little to no programming experience. Why? Kelton is only 17 years old and still in high school! Continue reading →