This week we grid a METAR field and make a contour plot!

This week learn a couple of ways to place text markers for heights on your Skew-T!

The netcdf-c library filters API in version 4.7.4 has been deprecated in favor of a modified version that unfortunately may cause incompatibilties for users.

The initial reason for the incompatible changes was to support the use of filters in the new NCZarr code. The changes were not completely thought out so it was decided to remove them and revert to previous behaviors. At some future point, the filter mechanism will be extended to support filters for NCZarr, but these will be proper extensions: the existing, reverted, filter API will continue to be supported with no user-visible modifications.

Unfortunately, some advanced users of netcdf filters may experience some compilation or execution problems for previously working code because of these reversions. In that case, please revise your code. Apologies are extended for any inconvenience. Note that it is possible to detect which mechanism is in place at build time.

In summary, the changes are of the following kinds:

• Some functions were renamed for consistency.
• Revert the way that the function nc_inq_var_filter was indicating no filters existed.
• Some auxilliary functions for parsing textual filter specifications have been moved to netcdf_aux.h.
• All of the "filterx" functions have been removed.
• The undocumented function nc_filter_remove was deleted.

See the Github document https://github.com/Unidata/netcdf/blob/master/NUG/filters.md for details.

Want to try out the newest release candidate for MetPy 1.0.0? Learn how to find out what's new and install the RC2!

Unidata is looking for community contributions to the Jupyter Notebook service, which provides Jupyter Notebooks to facilitate accessing, exploring, and visualizing datasets in the TDS. Users who have written Notebooks that interface with TDS datasets (or Python scripts that can be converted) or are interested in creating one can contribute in one of two ways (or both!):

1. Contribute a generic viewer that would be a useful in a typical THREDDS Data server (see the GitHub issue here).
2. Contribute a viewer for a specific dataset, data type, or catalog included in the Unidata THREDDS Data Server (see GitHub issue here).

The issues above are eligible for Hacktoberfest: you get Hacktoberfest credit and help the Unidata community! For more information on contributing and some helpful links, visit the GitHub issues above.

Happy hacking!