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PR Summary
Sci/Tech Reviewer: @melissaebrooks
Code Reviewer: @cameronbateman-mo
I developed aerosol AOD diagnostics in FCM 440
The outputs looked fine at low resolution, but recent high resolution modelling has indicated that I got the addressing wrong.
I made a bug fix branch in FCM 1089 and will now fix it in GitHub branch.
Code Quality Checklist
(Some checks are automatically carried out via the CI pipeline)
style guidelines
readability of the code
Testing
acceptable (eg. kgo changes)
tests, unit tests, etc.)
and have tests been allocated to an appropriate testing group (i.e. the
developer tests are for jobs which use a small amount of compute resource
and complete in a matter of minutes)
trac.log
Test Suite Results - lfric_apps - AOD_bug/run2
Suite Information
Task Information
❌ failed tasks - 1
✅ succeeded tasks - 1102
⌛ waiting tasks - 1
Security Considerations
Performance Impact
performance measurements have been conducted
AI Assistance and Attribution
of Generative AI tool name (e.g., Met Office Github Copilot Enterprise,
Github Copilot Personal, ChatGPT GPT-4, etc) and I have followed the
Simulation Systems AI policy
(including attribution labels)
Documentation
confirmed that it builds correctly
PSyclone Approval
inteface, optimisation scripts, LFRic data structure code) then please
contact the
tooscollabdevteam@metoffice.gov.uk
Sci/Tech Review
Please alert the code reviewer via a tag when you have approved the SR
Code Review