Materialize buoyancy gradients for use in parameterizations #4837
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simone-silvestri
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benchmark performance
glwagner
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Oct 9, 2025
src/Models/HydrostaticFreeSurfaceModels/hydrostatic_free_surface_model.jl
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glwagner
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glwagner
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| arch = architecture(grid) | ||
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| # Maybe compute buoyancy gradients | ||
| compute_buoyancy_gradients!(buoyancy, grid, tracers; parameters = κ_parameters) |
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why does it take "κ_parameters"? These are the parameters for the turbulence closure? It's not clear why we would use that.
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right, I think we need some interior_parameters and surface_parameters.
glwagner
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Co-authored-by: Gregory L. Wagner <[email protected]>
Co-authored-by: Gregory L. Wagner <[email protected]>
…ce_model.jl Co-authored-by: Gregory L. Wagner <[email protected]>
glwagner
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The difference between main and this PR is staggering for all the CATKE functions On mainCATKE was the most expensive kernel On this PRTendencies take back their role of most heavy computations in the model |
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This PR introduces the precomputation of buoyancy gradients, which are required for most parameterization.
By doing this, we avoid heavyl interpolation of buoyancy computations (for example in slope computations or in Richardson number computations) speeding up significantly the parameterizations.