Add 2d variance metrics to reservoir training #2361
Merged
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
This adds scalar metrics for the mean vertically-summed grid-scale variance of outputs in the x, y plane. Since the prognostic run reservoir predictions have issues with too much grid-scale noise in column-integrated quantities, I would like to see how the hyperparameters affect this in offline evaluation. I don't have area or pressure thicknesses saved in the data, so this is a very rough way of estimated the variance in column-integrated quantities.
During synchronization of the reservoir the
_rc_out
precipitable water field has a higher variance than the_hyb_in
field, which suggests that this should be visible in offline evaluation.