In the spring of 2020, Unidata made an offer of resources through the Science Gateway project in order to facilitate online learning in response to the ongoing COVID-19 epidemic. Since that time, nearly three hundred and fifty users — mostly undergraduates in atmospheric science programs — have been able to take advantage of cloud-based resources to access pre-configured computational notebooks for learning and teaching objectives.
For the fall 2020 term, Unidata is once again offering to provide universities (or individual instructors) access to cloud-based JupyterHub servers tailored to the needs of university atmospheric science courses and workshops. By using the Unidata Science Gateway, instructors can add Jupyter notebooks used in their coursework to a dedicated JupyterHub hosted using Unidata's resources in the NSF Jetstream cloud. Once logged in to the JupyterHub, individual students access pre-configured computing environments that allow them to work with the notebooks interactively, making and saving their own alterations to existing notebooks or creating their own new notebooks.
The Unidata Program Center's three summer student interns — Russell Manser from Texas Tech University, Caitlyn McAllister from Embry Riddle Aeronautical University in Florida, and Lauren Prox from George Mason University — have come to the end of their summer appointments. After a summer of dedicated work they presented the results of their projects to the UPC staff on July 28, 2020. You can find videos of their presentations to the UPC staff on the Unidata Seminar Series page.
During the beginning of my internship, I devoted a great deal of time learning how to use Git and Github to collaborate on software development projects. After gaining this experience, I began improving documentation for a variety of Unidata remote repositories. I started with the netCDF-C repository and then moved on to the MetPy, Siphon, and Python Training remote repositories. This work was significant as it ensured that software users were able to locate resources, properly download software, and learn how to operate the software via informational materials.
During the duration of this summer's internship program I hit the ground running by learning how to code in Python. Before this internship, I had only opened Python a few times while attending classes and did a little coding in this language for a collaborative project at my university. I familiarized myself over the first month by using the workshops available in JupyterLab provided by Unidata. I learned everything from loops to using the THREDDS data sever to plot variables. Outside of the language, I got to learn how an online community works with GitHub to share and process software and data. I also learned about development environments, which I had no clue about before. I will definitely be using all of these tools moving forward.
Coming into this summer, my goal was to integrate Dask Array support into MetPy. I knew that this was an ambitious task, but I am happy to say that I made progress toward accomplishing it!
There are a few AWIPS configuration changes to EDEX to address the change in GFS FV3 model data. As of June 16, 2020 NCEP changed the Vertical Velocity and Total Precipitation parameters in the GFS FV3 suite that come over NOAAPort. Read on for more detailed information about the changes from NCEP and Unidata.
