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Height-based Deep Hot Jupiter Forcing#391

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Thomas Bendall (tommbendall) wants to merge 5 commits intoMetOffice:mainfrom
tommbendall:TBendall/deep_hot_jupiter_forcing
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Height-based Deep Hot Jupiter Forcing#391
Thomas Bendall (tommbendall) wants to merge 5 commits intoMetOffice:mainfrom
tommbendall:TBendall/deep_hot_jupiter_forcing

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PR Summary

Sci/Tech Reviewer:
Code Reviewer:

This PR is an attempt to improve the stability of the deep hot Jupiter test case, through some setting tweaks and also through a change to the temperature forcing. The temperature forcing is written as a function of height rather than pressure, which removes a potential feedback in the dynamics as the pressure evolves (and thus the forcing with it).

Details

  • I have changed the deep hot Jupiter temperature forcing to be specified as a function of height, rather than pressure
  • the coefficients have been derived in offline code (see below)
  • changed two settings for the deep hot Jupiter test to improve stability
  • edited the corresponding unit-test, which has involved updating a hard-coded answer

Derivation of coefficients

The relaxation frequency, day-time and night-time temperatures are all defined through a polynomial expansion of log(sigma) -- essentially a scaled log(pressure) variable. The initial Exner pressure field for the deep hot Jupiter test does not depend on longitude or latitude, so it is possible to translate between log(sigma) and a log(height) coordinate. The relaxation frequency, day-time and night-time temperatures can then be written as a polynomial expansion of log(height) instead.

The attached python code computes these coefficients:
forcing_coeffs.py

The following plots show that the new coefficients ensure that the vertical profiles match:
newton_freq
T_day
T_night

Code Quality Checklist

  • I have performed a self-review of my own code
  • My code follows the project's style guidelines
  • Comments have been included that aid understanding and enhance the readability of the code
  • My changes generate no new warnings
  • All automated checks in the CI pipeline have completed successfully

Testing

  • I have tested this change locally, using the LFRic Apps rose-stem suite
  • If any tests fail (rose-stem or CI) the reason is understood and acceptable (e.g. kgo changes)
  • I have added tests to cover new functionality as appropriate (e.g. system tests, unit tests, etc.)
  • Any new tests have been assigned an appropriate amount of compute resource and have 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

Security Considerations

  • I have reviewed my changes for potential security issues
  • Sensitive data is properly handled (if applicable)
  • Authentication and authorisation are properly implemented (if applicable)

Performance Impact

  • Performance of the code has been considered and, if applicable, suitable performance measurements have been conducted

AI Assistance and Attribution

  • Some of the content of this change has been produced with the assistance 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

  • Where appropriate I have updated documentation related to this change and confirmed that it builds correctly

PSyclone Approval

  • If you have edited any PSyclone-related code (e.g. PSyKAl-lite, Kernel interface, optimisation scripts, LFRic data structure code) then please contact the TCD Team

Sci/Tech Review

  • I understand this area of code and the changes being added
  • The proposed changes correspond to the pull request description
  • Documentation is sufficient (do documentation papers need updating)
  • Sufficient testing has been completed

(Please alert the code reviewer via a tag when you have approved the SR)

Code Review

  • All dependencies have been resolved
  • Related Issues have been properly linked and addressed
  • CLA compliance has been confirmed
  • Code quality standards have been met
  • Tests are adequate and have passed
  • Documentation is complete and accurate
  • Security considerations have been addressed
  • Performance impact is acceptable

@tommbendall Thomas Bendall (tommbendall) added the KGO This PR contains changes to KGO label Mar 24, 2026
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