Costa Christopoulos

Original TC PR: https://github.com/CliMA/TurbulenceConvection.jl/commit/da2ae4e45838b4413fba50c267a21554db4641e7

This is somehow changing the behavior of non-socrates cases in the CI. See ie. life_cycle_tan2018 in the buildkite tests.

In that case I think we'll need to hard-code the random basis vector to match exactly what was used in the calibration config.

Does using `reproducible_rand` and `reproducible_randn` in the calibration config in the same way as in (https://github.com/CliMA/TurbulenceConvection.jl/pull/1058 ) solve the problem? After updating the namelist with the calibrated parameters for fno/rfm...

Isn't passing `rng` to `rand` and `randn` functionally similar to what Charlie proposed with `reproducible_rand` since a seed is set in that function and calls to it don't impact the...

Currently in CEDMF, based on Matt's config, the random feature vector is created like this. What we want to match between TC and CEDMF are the random numbers in `rf_fix_ent_params`...

So it sounds like the immediate priorities are to a) Use an average 30 mins around `t_end` - 6 to initialize the SCM + run for 6 hours and b)...

The SCM now uses a relaxation to LES profiles for `theta` and `qt` in the same manner as Zhaoyi's paper. Initial conditions for the SCM are the 1-hour LES mean...

#1298 nudges thetali, qt, U, and V to the GCM profile (initial LES profile). Edit (Ignacio): Before, we were nudging to LES profiles. This change is important because the steady-state...

@charleskawczynski `compute_turbulent_entrainment(param_set, εδ_model_vars)` will likely not be changed or overloaded by us, since we're only working on the dynamical entrainment.