The use of the Python programming language has grown immensely over the past decade and has become an essential tool within education, research, and industry within the atmospheric sciences. This course aims to go beyond a basic Python introduction and help attendees advance their ability to apply Python to practical problems in meteorology. This includes topics such as remote data access, calculation of derived quantities, and plotting of these quantities on map projections. As a more intermediate workshop, this workshop assumes a basic knowledge of Python syntax and some familiarity with scientific Python libraries like NumPy and Matplotlib.

The goal of the course is to have attendees learn how to apply Python to practical meteorology problems through use of the MetPy library. They will gain experience accessing remote datasets, using MetPy to calculate derived quantities, and plotting these quantities on weather maps, including station plots. Synoptic meteorology serves as a backdrop for these activities, with motivating examples for case studies such as visualization of satellite imagery, quasigeostrophic/isentropic analysis, and soundings.

This course is extensively hands-on through the use of Jupyter notebooks and will consist of one day of interactive lecture sessions with incorporated exercises that will be completed during the short course. In addition, the afternoon sessions will be aimed at developing Jupyter notebooks that will launch each attendee to bring something tangible home from the course. The instructors for the course are:

Dr. Ryan May, UCAR/Unidata, Dr. John Leeman, UCAR/Unidata, and Dr. Kevin Goebbert, Valparaiso University.

- Indicates paper has been withdrawn from meeting

- Indicates an Award Winner