Quasi-Geostrophic model in Firedrake
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License: MIT License
Quasi-Geostrophic model in Firedrake
License: MIT License
Add the following tests:
Test the MinDx feature.
Test the noise convergence (of the mean or a statistic)
Allow the variance argument in the quasi_geostrophic
model to be removed and replaced by an OU process, which IT'S variance is then given in place of the variance argument, allow this to be correlated (easily, as it's just scalar OU) between pairs of two-level simulations.
Create a random infinite dimensional initial condition for the QG model in way that was discussed in meeting:
Solve one time-step, with random forcing (additive to q
to find psi
), and use that as new initial condition.
Allow an argument to be entered to correlate the noise input to another system (a coarse / fine version) so that it can be prescribed at every time-step
Update on how to do this:
d
. Best way to do this is provide a tuple of FunctionSpace
s, or just one FunctionSpace
and deduce from this.d
, then access like that.u_
helmholtz solution sums, and then use this for input for projection for coarse self.forcing
).u_
solution to first fine u_
solution to make up coarse)Adjust two_level_quasi_geostrophic
so that any MeshHierarchy.refinements_per_level
can be used
q
in the initial condition (with random psi
).Make sure that the system is not being propagated forward different time-steps at the start (I.C.) for different resolutions. Try doing a standard time-step, say 1.0. (By altering self.qg_class.const_dt
- like what is done for coarse on two-level) Then all resolutions should be solved once for same time
.
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