Feature/turn off stability #72
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5c97fb1 Fix pre-processing pipeline (#67) bece914 Implement WhiteNoise stochastic parameterization 0bcb3e3 Configure SAM to save python state to disk ce8ba17 Implement Nudging (#56) 735d179 Use CF-style names for the SAM interface (#55) 5eb0761 Automate report generation for new cases eb714a5 Add hyperdiffusion of humidity 00817a7 Add temperature hyper-diffusion bd7ef38 Use held suarez velocity damping in SAM c1c9566 Make the meridional boundary size a namelist option 963c740 Refactor the hyperdiffusion code 751589a Pass LHF and SHF to python with debiasing 30ed4cb Enhance SAM diagnostics and enable CMT (#35) d932615 Revert changes to surface scheme b3fe192 Run SAM with the new scheme 221b163 Post-process SAM on olympus 91c68ad Add dosgsthermo option c5a324e Fix sam-NN interface for refactored models cf9d7cc Fix incosistent types equinox zenith angle code 3b05ccd Mask neural network near N/S boundaries 478f757 Retrieve U and V from python state 51f91f0 Fix bug with netCDF output for FQTNN and FSLNN c9e7bb5 Fix SAM + NN execution in docker e1e0aaf Compile SAM with double precision 686f565 Fix bug with default_parameters 303a4b1 Output and analyze FQTNN and FSLINN 47b7a77 Use RUNDATA from inside docker image db199aa Changing damping and SGS schemes 3ea7605 Fix the SAM python scripts ff2245d Make hyper-diffusivity a namelist option 1292d57 Reduce hyperdiffusion coefficient 0d779f7 Add horizontal hyper diffusion to SAM a4ecf1e Do not recompile SAM when MICRO_RAD changes 69f2e05 Save neural network Prec,LHF, and SHF to OUT_2D git-subtree-dir: ext/sam git-subtree-split: 5c97fb113e4a98f270d4ad7f8f0f8465cb3e9c6a
Previously we assumed that loss = l_consistency + l_stability, and could not turn off the penalty. I made the configuration of the stepper more versatile and added an option "alpha" for so that loss = l_consit + alpha * l_stab
The simulation is located at: data/runs/model280-epoch5.debiased/ This simulation does not blow up immediately but does develop grid-scale storms. This could occur because of the debiasing procedure though.
nbren12
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Nov 13, 2020
* Configure weight of instability penalty Previously we assumed that loss = l_consistency + l_stability, and could not turn off the penalty. I made the configuration of the stepper more versatile and added an option "alpha" for so that loss = l_consit + alpha * l_stab * Run simulation with no instability penalty The simulation is located at: data/runs/model280-epoch5.debiased/ This simulation does not blow up immediately but does develop grid-scale storms. This could occur because of the debiasing procedure though.
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