The Unidata Program Center's summer student intern Josh Clark has come to the end of his summer appointment. After a summer of widely varying projects, Josh gave an overview of his accomplishments to the UPC staff on July 31, 2015.
Josh graduated from the University of Northern Colorado in the spring of 2015 with a B.S. in Meteorology. After spending the summer at the Unidata Program Center, he is headed to the graduate program at San Jose State's Fire Weather Research Lab.
Editor's note: Josh Clark was a Unidata Summer Intern in 2015. He graduated from the University of Northern Colorado (UNC) in the spring of 2015 with a B.S. in Meteorology, and is headed to the graduate program at San Jose State's Fire Weather Research Lab starting in the Fall of 2015.
An example EdexPy interface (click to enlarge)
It is hard to believe my time here at Unidata has come and gone so quickly! Next week, I imagine it will be back to the “harsh” reality of being a student — sitting on a beach somewhere near Monterey or perhaps fly fishing the Sierras over the next twenty days awaiting the start of my first year of graduate school at San Jose State. What a terrible reality that will be!
This experience at Unidata and UCAR has been an incredible opportunity and I am privileged to have been afforded these ten weeks. When I started here, I envisioned an entirely different internship than what previous interns had completed. Rather than developing one particular project, I focused my time on gaining a greater understanding of software engineering as a whole and contributing to existing Unidata projects. I found a comfortable spot working with Unidata Python developers Ryan May and Sean Arms, and within one week I had learned a great deal about unit testing, code health, automated testing, and version control. Later, I would implement these principles in my first Python library, MesoPy.
An AMS Short Course on Open Source Radar Software will be held on the 13th of September 2015 in Norman, Oklahoma preceding the 37th Conference on Radar Meteorology. Preliminary programs, registration, hotel, and general information on the conference are available on the AMS conference web site.
MetPy is an Open Source project aimed at providing a Pythonic library for meteorological data analysis that meshes well with the rest of the scientific Python ecosystem. The project heavily leverages the work already done by the Numpy, Scipy, and Matplotlib projects, and adds on top functionality specific to meteorology: plotting (e.g. Skew-Ts), calculations, and reading files (e.g. WSR-88D NIDS files).
Editor's note: Florita Rodriguez is a 2014 Unidata Summer Intern from Marble Falls, TX. She graduated with a Bachelor of Science in Meteorology from Texas A&M University in May, 2014.
I created this hurricane track IPython notebook for all to enjoy. This project was suggested to me by some Python enthusiasts here at Unidata and while I was familiar with IPython and its notebook feature, this was a great opportunity for me to explore the interactive use provided by IPython interactive widgets and how to create an interactive environment in which National Hurricane Center data could be visualized.
The IDV group recently received a request from a researcher to have the IDV display CF-compliant netCDF trajectory files. The IDV already has some limited capacity to handle these data. However, this particular request requires the IDV handle multiple trajectories in one CF-compliant file, which is currently not supported by the IDV. We would like to assist this researcher with these data.
Library software like netCDF or HDF5 provides access to multidimensional data by array indices, but we would often rather access data by coordinates, such as points on the Earth's surface or space-time bounding boxes. This blog, with an accompanying iPython notebook, explores some issues with correctness and efficiency in accessing data by coordinates instead of array indices in a real-world example.
