[MITgcm-support] Help with internal wave breaking and shoaling parameterization package

[Nadav Mantel]

Hey everyone,

This is a topic that comes up every now and then but I would still really
appreciate someone's help.
I am running a non-hydrostatic regional model for the Gulf of Aqaba\Eilat,
an elongated semi-enclosed basin [~200 km long, ~30 km wide ~1000 m
deep] with an entry through a shallow sill in the south. The model runs
with a horizontal resolution of 300 m and 32 vertical layers with the
differences in depth of 5,10, 12.5, 15, 17.5, ... m and a time step of 10s.
I'm forcing tides through the southern boundary using the obcs package. The
barotropic flow crossing the Straits of Tiran (our shallow sill) creates
large amplitude (50 m in observations) internal waves along the gulf.

We would like to parameterize the shoaling and general breaking of the
internal waves using one of the many packages MITgcm has to offer but we
have had some troubles.

We first intended to use the KL10 package, yet we had uncharacteristic
seasonal mixing and when checking the viscosity output we had weird results
where in some places we got viscosity coefficients of 3 [m^2/s] whereas the
rest of the gulf is much smaller. It could be possibly due to non-linear
EOS, I saw in the mitgcm bug tracker that there are issues with anything
but linear EOS use in the package.

We moved on to the richardson number packages, starting with pp81 as it is
the simplest. Our problem was that we consistently got the maximum
viscosity (a default of 1) in almost all of the second layer, creating once
more uncharacteristic mixing with very large diffusivities (60 m^2/s).

We thought about using KPP as it was the package used in simulating the
gulf up until now, but it wasn't designed for this purpose and we are
skeptical it would produce good results.

Kind of at a loss at this point, and it would be really amazing to get
someone's feedback via zoom call on their experiences with internal wave
parameterization using any package for regional models.

Thanks,
Nadav Mantel
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