The meteorology curriculum at Valparaiso University (VU) is continuously evolving as new technology arises, and this includes Python. Python is becoming a staple in many VU meteorology courses, where an ever-increasing number of packages and libraries are in use. Adding a new programming language to the educational mix can create a steep learning curve for college students who lack a programming background, but we feel that an early introduction to Python helps to prepare students for immersion into the job market or further education in graduate school.
Students begin their Freshman year on a journey of meteorological education juxtaposed with the opportunity to build important computer programming skills. They begin with the basics of data analysis using Numpy, Pandas, etc. and leave the university with a full toolbox of Python knowledge. Students learn to create upper air soundings with a Skew-T using MetPy, make maps with Cartopy, and do surface, satellite, and model data analysis using a variety of atmospheric science applications including Unidata’s MetPy and Siphon packages. The resulting analyses are used for local, regional, continental, and global weather discussions. Our students regularly use their technical skills to answer meteorologically-relevant questions related to forecasts and research.
Above, students are shown engaged in a map discussion around recent light lake effect snow that occurred over the Valparaiso area. The image on screen is shown at left; it was generated from a Jupyter notebook using methods to plot GOES-16 satellite data, NEXRAD Radar data, and ASOS surface observations together on a map with Cartopy, Metpy, PyArt, and other Python packages.
Python is not only used in the teaching curriculum at VU — it is also important for the analysis and plotting of data collected by the department. Data from a 5-cm Doppler RADAR on the VU campus is processed using the PyArt package, and GOES-16 satellite data is processed using MetPy; both are plotted using the Cartopy package. Future work will include the combination of VU’s northern Indiana surface observation network with NWS ASOS stations to create surface analysis figures using MetPy and Cartopy.
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