MetPy 0.7.0 has been released. This release has a wide collection of new features as well as minor bug fixes, including several contributions from our community. For full release notes see the GitHub Release Page.
In this week's MetPy Monday, we talk about the most recent release of MetPy, 0.7. This release saw a lot of work put into calculations, including some changes and new capabilities for kinematics functions that involve taking derivatives of fields. We also want to thank all of the community members (9 in total!) who contributed Pull Requests to this release.
Unidata community members Ivo Jimenez and Dr. Carlos Maltzahn from the University of California, Santa Cruz, along with Kevin Tyle from the University at Albany, will be presenting an AMS Short Course titled Reproducible Atmospheric Science Workflows Using Open Source Tools: An Introduction to the Popper Experimentation Protocol. The course focuses on an exciting new open-source toolset developed by researchers at UC Santa Cruz with specific tie-ins to reproducible workflows in atmospheric science modeling using the Weather Research and Forecasting model (WRF), both in research and the classroom.
Unidata developers Ryan May and John Leeman, together with Kevin Goebbert from Valparaiso University, will be teaching a one-day short course titled “Python for Dynamical Meteorology Using MetPy” at the 2018 AMS Annual Meeting in Austin, Texas. The format of the course is like that of our larger Python workshop, relying on Jupyter notebooks to teach several core concepts. The crux of the course is to access remote data sets and use MetPy to perform analyses relevant to synoptic/dynamic meteorology. The goal is to go beyond the traditional introduction to Python and work on some concrete, meteorology-specific problems. As a result, familiarity with Python, NumPy, and Matplotlib is assumed.
