Metereological data analysis and visualization with MetPy

Date and Time: 
Friday 2018 Apr 6th
CG Auditorium
Ryan May and John Leeman

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. 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. Dynamical meteorology serves as a backdrop for these activities, with motivating examples for case studies such as geostrophic vorticity advection and frontogenesis. 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 final session will be aimed at developing a Jupyter Notebook that will launch each attendee to bring something tangible home from the course.

Speaker Description: 

Ryan May is a software engineer at UCAR/Unidata, working on Python software and training for the atmospheric science community. Currently, he is the core developer of the MetPy and Siphon Python packages, as well as a member of the development team for the matplotlib Python visualization library.

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