Add probabilistic measures with observational uncertainty recommended by Ferro (2017). Eric has written some code to do them, but they need to be put in the right place and connected correctly. Also, they currently calculate the scores for each category, so they will also need to be averaged over the categories.

Describe the New Feature

The scores are unbiased scores that allow for observational uncertainty to be taken into account. They are also proper scores.

Acceptance Testing

List input data types and sources.
Describe tests required for new functionality.

These should take the same data types as the current scores available in MET such as crps. Not sure how to test them as Ferro does not really demonstrate on a data set. Perhaps we could ask him to give us a small data set with his own answers to check our code on?

Time Estimate

I expect it will take a day to add it in.

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, METdataio, METviewer, METexpress, METcalcpy, METplotpy

New Feature Checklist

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