Check Out this Podcast with Unidata's MetPy Developers

Want to hang out with the MetPy developers, but can't make it to the Unidata Program Center? Crank up your podcast app and spend a pleasant hour with Unidata's Ryan May, Sean Arms, and John Leeman, who visited with host Tobias Macey of the Podcast.__init__ podcast last week.

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MetPy 0.4.3 Released

MetPy version 0.4.3 has been released. This fixes a few more minor issues in the 0.4 series. For full release notes see: https://github.com/Unidata/MetPy/releases/tag/v0.4.3

MetPy packages are available for Conda on the conda-forge channel, and for pip from the Python Package Index.

Let us know if you run into any problems, either at MetPy's issue tracker, or on the Unidata python-users list.

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MetPy 0.4.2 Released

MetPy version 0.4.2 has been released. This fixes a few more minor issues in the 0.4 series. For full release notes see: https://github.com/Unidata/MetPy/releases/tag/v0.4.2

MetPy packages are available for Conda on the conda-forge channel, and for pip from the Python Package Index.

Let us know if you run into any problems, either at MetPy's issue tracker, or on the Unidata python-users list.

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MetPy 0.4.1 Released

MetPy version 0.4.1 has been released. This fixes a few minor issues in the 0.4 release. Highlights of features added in the 0.4 release:

  • New calculations: Saturation mixing ratio, Equivalent potential temperature, Coriolis parameter, and Level of free convection (LFC)
  • Provisional support for objective analysis/regridding (Barnes, Cressman, Nearest Neighbor, Natural Neighbor, and Radial Basis Function Interpolation)
  • Support for downloading upper air data from Wyoming and Iowa State archives
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Unidata’s Jupyter Notebook Gallery

Jupyter Notebooks

As part of an ongoing effort at the Unidata Program Center to bring Python-based workflows to the atmospheric science community, UPC developers have created the Unidata Jupyter Notebook Gallery to showcase tools and techniques that may be of interest to community members. The gallery is a collection of Jupyter notebooks that demonstrate ways to work with atmospheric science data using Python. The notebooks use a variety of tools available in the Python ecosystem, including several developed by Unidata.

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