I'm excited to finally announce the release of Tropycal v0.3! In addition to new features & bug fixes, Tropycal can now be installed via conda-forge!
Documentation (newly updated): tropycal.github.io/tropycal/
GitHub: github.com/tropycal/tropy
Sample script: github.com/tropycal/sampl
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Thanks to help from , Tropycal is now up on conda-forge, and can be simply installed using:
conda install -c conda-forge tropycal
The documentation was previously broken, but has now been fixed. Check it out for how to use Tropycal's functionality!
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As we saw this year with Hurricanes Ida & Henri, tropical cyclones can cause major flooding.
Thanks to excellent work at from and Lapenta intern , the WPC tropical cyclone rainfall database can be easily read into & plotted with #Tropycal!
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Another new addition to Tropycal is a Cartopy plotting utility.
For those that want to bypass the default plotting options & directly plot storm tracks on existing matplotlib/Cartopy axes, this new functionality adds a "plot_storm()" method to the axes!
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It should be noted that there are several non-backwards compatible changes with this release. For more information, read the release notes:
github.com/tropycal/tropy
As always, we always appreciate feedback & welcome any contributions to #Tropycal!
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A couple other minor notes:
- multiple JTWC realtime best track data sources experienced outages this summer. Initializing a Realtime object now gives the user an option to pick the source to try & read in.
- Realtime objects now read in invests designated by NHC.
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Wooo! Getting it up on conda-forge was a goal for a while so it's awesome that it's finally a reality 😃
