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Improve Eady figure #145
Improve Eady figure #145
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paper/paper.md
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@@ -72,7 +72,7 @@ An example of a problem involving small-scale flow features is showcased in \aut | |||
![In this simulation of baroclinic instability in the Eady problem, a background buoyancy gradient and corresponding thermal wind generates a sub-mesoscale eddy, roughly following the setup of @taylor:2016. | |||
To this physical setup, we added a medium complexity (9 tracers) biogeochemical model, some components of which are shown above. | |||
On top of this, we added particles modelling the growth of sugar kelp, which are free-floating and advected by the flow, and carbon dioxide exchange from the air. | |||
Thanks to Julia's speed and efficiency the above model (1 km × 1 km × 100 m with 64 × 64 × 16 grid points) took about 30 minutes of computing time to simulate 10 days of evolution on an Nvidia P100 GPU. | |||
Thanks to Julia's speed and efficiency the above model (1 km × 1 km × 100 m with 512 × 512 × 64 grid points) took about X minutes of computing time to simulate 10 days of evolution on an Nvidia A100 GPU. | |||
Panel (a) shows the domain with the colour representing the concentration of various biogeochemical tracer fields: inorganic carbon, organic carbon (dissolved and particulate), phytoplankton, and nutrients. | |||
The increase in organic carbon concentration in the centre of the eddy can be seen, as well as carbon being subducted (most visible in the xz face in the organic carbon). |
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@johnryantaylor I will update this caption when I have made the new figure, but do you want to add a sentence about the physics visible at the high resolution?
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Good point - I suggested a sentence above
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u, v, w = model.velocities | ||
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# Periodically save the velocities and vorticity to a file. |
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# Periodically save the velocities and vorticity to a file. | |
# Periodically save the velocities to a file. |
paper/figures/eady.jl
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n = 32 | ||
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x = arch_array(arch, [repeat([-200.0, -100.0, 0.0, 100.0, 200.0], 1, 5)...] .+ Lx / 2) |
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x = arch_array(arch, [repeat([-200.0, -100.0, 0.0, 100.0, 200.0], 1, 5)...] .+ Lx / 2) | |
x = arch_array(arch, [repeat([-200.0, -100.0, 0.0, 100.0, 200.0], 1, 5)...] .+ Lx / 2) |
Also, where does this 5
come from? Seems hardcoded. Should we define a variable so that it's clearer how one can change it?
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I'll update this since there was an issue here too
paper/figures/eady.jl
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particles = SLatissima(; architecture = arch, | ||
x, y, z, | ||
A = arch_array(arch, 5.0 .* ones(n)), N = arch_array(arch, 0.01.* ones(n)), C = arch_array(arch, 0.18.* ones(n)), |
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A = arch_array(arch, 5.0 .* ones(n)), N = arch_array(arch, 0.01.* ones(n)), C = arch_array(arch, 0.18.* ones(n)), | |
A = arch_array(arch, 5.0 .* ones(n)), N = arch_array(arch, 0.01 .* ones(n)), C = arch_array(arch, 0.18 .* ones(n)), |
paper/figures/eady.jl
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schedule = TimeInterval(6hours), | ||
filename = "eady_particles.jld2", | ||
overwrite_existing = true) |
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schedule = TimeInterval(6hours), | |
filename = "eady_particles.jld2", | |
overwrite_existing = true) | |
schedule = TimeInterval(6hours), | |
filename = "eady_particles.jld2", | |
overwrite_existing = true) |
paper/figures/eady.jl
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particles = SLatissima(; architecture = arch, | ||
x, y, z, | ||
A = arch_array(arch, 5.0 .* ones(n)), N = arch_array(arch, 0.01.* ones(n)), C = arch_array(arch, 0.18.* ones(n)), | ||
latitude = 57.5, |
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where does this latitude value comes from? is this the value that corresponds to the f
value we use above?
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It was arbitrary for fast kelp growth, but I've changed now to correspond to the coriolis force.
paper/paper.md
Outdated
@@ -72,7 +72,7 @@ An example of a problem involving small-scale flow features is showcased in \aut | |||
![In this simulation of baroclinic instability in the Eady problem, a background buoyancy gradient and corresponding thermal wind generates a sub-mesoscale eddy, roughly following the setup of @taylor:2016. | |||
To this physical setup, we added a medium complexity (9 tracers) biogeochemical model, some components of which are shown above. | |||
On top of this, we added particles modelling the growth of sugar kelp, which are free-floating and advected by the flow, and carbon dioxide exchange from the air. | |||
Thanks to Julia's speed and efficiency the above model (1 km × 1 km × 100 m with 64 × 64 × 16 grid points) took about 30 minutes of computing time to simulate 10 days of evolution on an Nvidia P100 GPU. | |||
Thanks to Julia's speed and efficiency the above model (1 km × 1 km × 100 m with 512 × 512 × 64 grid points) took about X minutes of computing time to simulate 10 days of evolution on an Nvidia A100 GPU. |
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"X minutes" needs to be replaced with the number
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Yeah not quite finished running!
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some remarks
Do we think the eady plot is now sufficiently clear and large enough text? |
It doesn't have the colorbars or kelp line plot but I don't think they add much to the demonstration value of the plot. |
I think I would like to add to one of the sentences about performance an acknowledgement of and reference for KA/JuliaGPU |
I've also just noticed that the reference for Oceananigans isn't at the first instance it was mentioned, should we change? |
Co-authored-by: johnryantaylor <[email protected]>
Fontsizes for axis labels don't seem to have increased. Have they? |
sediment.denitrification_params.E * log(reactivity) ^ 2 + | ||
sediment.denitrification_params.F * log(O₂) * log(reactivity)) / (Cᵐⁱⁿ * day) | ||
=# |
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shall we delete these commented code?
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I guess so, might be better todo in #138 since I've made a lot of changes to the sediment there
Co-authored-by: Navid C. Constantinou <[email protected]>
Oh I see! Okie then! Yes! Much better!
Try 0.8*min / max ? Ideally I'd like a bit more contrast for the left-part of the figure. But it's also fine as is! |
This PR addresses #140 and increases the model resolution.
Closes #140