Summer 2021 Unidata Interns Wrap Up Their Projects
04 August 2021
The Unidata Program Center's three summer student interns — Lydia Bunting from Texas Tech University, Connor Cozad from the College of Charleston in South Carolina, and Isabelle Pfander from Willamette University in Oregon — 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, 2021. You can find videos of their presentations to the UPC staff on the Unidata Seminar Series page.
[Read More]02 July 2021
The MetPy development team is looking for anyone who has used MetPy to take the 2021 MetPy Users Survey. The survey should only take approximately 5 minutes and is completely anonymous.
[Read More]29 April 2021
Version 1.0.1 of MetPy is now available. MetPy is a collection of tools in Python for reading, visualizing, and performing calculations with weather data. The project aims to mesh well with the rest of the scientific Python ecosystem, including the Numpy, Scipy, and Matplotlib projects, adding functionality specific to meteorology.
[Read More]Unidata Staff Teach MetPy at AMS Python for Climate and Meteorology Short Course
30 March 2021
Providing hands-on training in the use of scientific software is a key component of Unidata's service to the geoscience education and research community. Three members of the Unidata Program Center staff recently took part in teaching an American Meteorological Society Short Course on Python for Climate and Meteorology, held virtually over four half-day sessions March 2, 4, 9 & 11, 2021.
[Read More]28 January 2021
Version 1.0 of the MetPy collection of tools in Python for reading, visualizing, and performing calculations with weather data was released on December 22, 2020. MetPy provides tested, reusable Python components suitable to a wide array of tasks common in meteorological and atmospheric science applications, including scripted data visualization and analysis. In adding this functionality, MetPy aims to mesh well with the broader scientific Python ecosystem — widely used projects including Numpy, Scipy, Matplotlib, xarray, and others.
[Read More]
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