Describe the New Feature

This work is related to dtcenter/METplus#??? (insert issue number here) which describes enhancing METplus for use in computing and quantifying stratospheric diagnostics. While some portions of that work will be done in Python, some enhancements to the MET code is needed as well. This top-level issue describes those changes. However, it should be further broken down into actionable pieces prior to beginning work.

1. The stratospheric diagnostics are based on either zonal or meridional mean fields. Consider enhancing MET to derive these means on-the-fly in any tool that can process multiple input fields (including Grid-Stat and Series-Analysis). Adding it to MODE would also be useful. The meridional mean is computed by averaging data values across all latitudes for each longitude. The zonal mean is computed by averaging data values across all longitudes for each latitude. Compute the 1D mean arrays for each input level and store the meridional or zonal mean as a 2D field. One dimension is the lat or lon and the other dimension is the vertical level.

Question: Can this only be computed for LatLon inputs or should it be computed for all input projection types?

2. Add support for a semi-structured grid type. The spatial information of the mean fields described above can be stored in a new semi-structured grid class. Recommend making this grid class flexible enough to store 5 variations of data types:
   • Zonal mean field with dimensions (lat, vertical level)
   • Meridional mean field with dimensions (lon, vertical level)
   • Vertical cross-section field with dimensions (points, vertical level) where points are located by (lat, lon) location.
   • Hovmoller field with dimensions (lat, time)
   • Hovmoller field with dimensions (lon, time)

In general, the semi-structured grid class should store (lat, lon) info for the first dimension and vertical level or time for second. Note that the xy_to_latlon() and latlon_to_xy() functions from the Grid base class warrant careful consideration.

3. Add support a totally unstructured grid type. This is really just for storing a set of lat/lon points and corresponding data values. Those lat/lon values can probably just be stored in a 1D, rather than 2D, array. This may be useful for handling unstructured grid data from MPAS and Elfrich. Note that operations like smoothing and interpolating (other than nearest neighbor) should result in an error.

Note: Lots of additional definition is required.

Acceptance Testing

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Describe tests required for new functionality.

Time Estimate

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Issues should represent approximately 1 to 3 days of work.

Sub-Issues

Consider breaking the new feature down into sub-issues.

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Relevant Deadlines

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Funding Source

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Define the Metadata

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Define Related Issue(s)

Consider the impact to the other METplus components.

• METplus, MET, METdatadb, METviewer, METexpress, METcalcpy, METplotpy

New Feature Checklist

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• Complete the issue definition above, including the Time Estimate and Funding source.
• Fork this repository or create a branch of develop.
  Branch name: feature_<Issue Number>_<Description>
• Complete the development and test your changes.
• Add/update log messages for easier debugging.
• Add/update unit tests.
• Add/update documentation.
• Push local changes to GitHub.
• Submit a pull request to merge into develop.
  Pull request: feature <Issue Number> <Description>
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  Select: Reviewer(s) and Linked issues
  Select: Repository level development cycle Project for the next official release
  Select: Milestone as the next official version
• Iterate until the reviewer(s) accept and merge your changes.
• Delete your fork or branch.
• Close this issue.