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A NN parameterization to test in the neverworld framework #18
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@xkykai, why don't you improve Oceananigans' |
cc @xkykai |
@simone-silvestri should this be the nonlocal Ri-based parameterization that we have implemented? Let me retrain the model with varying Prandtl number in positive and negative Ri regimes then I can incorporate this. |
It looks like you have an improvement to the current |
Yes I have, let me retrain with some slight modifications then I'll put it in! |
@simone-silvestri could you add me as a collaborator? I have updated the |
@xkykai I added you as a collaborator, but I think the idea was to add this parameterization directly to Oceananigans (not here) and to remove the parameterization from here. I think the idea is to modify the formulation and parameters |
Okay, in practice that means renaming Also do you think we should still keep the original |
What is the difference? They seem very similar, can they be implemented within a common framework using simple abstractions? |
This PR adds a NN closure to the neverworld representing the subgrid-scale fluxes of unrepresented mesoscale eddies in the large-scale circulation.
To be tested with a grid-size of 1/4 or 1/2 of a degree.
The neural network (provided by @Etienne-Meunier) uses values from https://github.com/chzhangudel/Forpy_CNN_GZ21/blob/smartsim/testNN.py
PR in collaboration with
@Etienne-Meunier and @vopikamm