Replace italics below with details for this issue.

Describe the New Feature

This use case will compute the Convective Triggering Potential (CTP) and Humidity Index (HI). These values will be passed to MET pointstat via the python embedding capability and METplotpy (or other plotting capability) to generate scatter plots of HI versus CTP to determine the land-atmosphere coupling regime (Findel and Elthair 2003 a,b).

See this short overview of CTP-HI for more details.

Acceptance Testing

Data needs include observations and model atmospheric profiles of temperature and humidity of the lowest 300 hPa above ground during early morning local time.

Radiosonde profiles, AMDAR profiles, profiles from other sources such as satellite or microwave radiometer if deemed high enough quality by user.

Basic functionality will be python should include ability to read in some user provided profile from any source and describe our required input format, then compute CTP and HI. Model ingest should be able to read UFS output at appropriate levels, compute CTP and HI on grid. The observed and modeled CTP-HI values will be passed to MET pointstat to compute model-obs differences across both metrics. Capability should also include the ability to produce scatter plots of modeled and observed HI versus CTP.

Describe tests required for new functionality.
Test computation of CTP for example observation
Test computation of HI for example observation
Test computation of CTP for example UFS file
Test computation of HI for example UFS file
Test model-observation comparison output in MET pointStat
Test plotting capability for model and observed CTP-HI data

Time Estimate

3 days

Sub-Issues

Consider breaking the new feature down into sub-issues.

• Observed atmospheric profile format definition and ingest
• Computation of observed CTP and HI
• Computation of model CTP and HI
• Python embedding MET pointStat output
• Basic plotting capabilities

Relevant Deadlines

31 Dec 2023

Funding Source

7750034 (UAlbany-NCAR METplus JTTI)

Define the Metadata

Assignee

• Select engineer(s) or no engineer required
• Select scientist(s) or no scientist required

Labels

• Select component(s)
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Projects and Milestone

• Select Repository and/or Organization level Project(s) or add alert: NEED CYCLE ASSIGNMENT label
• Select Milestone as the next official version or Future Versions

Define Related Issue(s)

Consider the impact to the other METplus components.

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

New Feature Checklist

See the METplus Workflow for details.

• 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.
• Add any new Python packages to the METplus Components Python Requirements table.
• Push local changes to GitHub.
• Submit a pull request to merge into develop.
  Pull request: feature <Issue Number> <Description>
• Define the pull request metadata, as permissions allow.
  Select: Reviewer(s) and Development 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.