Morrison-Gettelman microphysics #161
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
…ics and Arakawa-Wu adjustment schemes for FV3
…ics and Arakawa-Wu adjustment schemes for SCM
|
All regression tests passed on Theia/Intel - ready to merge. rt_ccpp_hybrid.log |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
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Outdated suggestions cannot be applied.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 PR replaces #151 (see description there) and solves the bit-for-bit differences between the CCPP reference run (Theia, Intel18) and the CCPP runs by
adding a compiler flag that ensures consistent math results from the gamma function to micro_mg2_0.F90 and micro_mg3_0.F90 for both the FV3 and CCPP codes (required for the dynamic CCPP build only)
adding an interstitial scheme that was previously missed that calculates the Arakawa-Wu adjustment to microphysics tendencies (required for the standalone and static CCPP builds)
The bulk of the work behind this PR and associated PRs (see below) was done by @dudhia and @grantfirl.