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Additional Functionalities

  • ClimateModels.jl : standard interface for modeling workflows, used in MITgcm.jl.
  • Climatology.jl : accessing gridded data sets and using ECCO solutions.
  • MeshArrays.jl : data structures for gridded model output.
  • Drifters.jl : particle tracking applications and pathway simulations.

More Examples

The notebook from JuliaCon2021 (MITgcm_tutorial_global_oce_biogeo.jl) reads and visualize results from the standard MITgcm configuration called tutorial_global_oce_biogeo.

Note

This notebook builds and runs tutorial_global_oce_biogeo from within Julia. Alternatively, the MITgcm documentation explains how to build and run tutorials at the command line in linux.

Format Conversions

MITgcm.findtiles — Function
findtiles(ni::Int,nj::Int,mygrid::gcmgrid)

Return a MeshArray map of tile indices, mytiles["tileNo"], for tile size ni,nj and extract grid variables accordingly.

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MITgcm.cube2compact — Function
cube2compact(x::Array)

Reshape from e.g. size (192, 32, 5) in cube format to (32, 192, 5) in compact format.

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MITgcm.compact2cube — Function
compact2cube(x::Array)

Reshape from e.g. size (32, 192, 5) in cube format to (192, 32, 5) in compact format.

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Formulas, Parameters

MITgcm.SeaWaterDensity — Function

SeaWaterDensity(Θ,Σ,Π,Π0)

Compute potential density (ρP), in situ density (ρI), and density referenced to PREF (Π0 in decibars) from potential temperature (Θ in °C), salinity (Σ in psu) and pressure (Π in decibars) according to the UNESCO / Jackett & McDougall 1994 equation of state.

Credits: code based on a Matlab implementation by B. Ferron Reference: https://www.jodc.go.jp/info/iocdoc/UNESCOtech/059832eb.pdf Check value: ρI = 1041.83267kg/m^3 for Θ=3°Celcius, Σ=35psu, Π=3000dbar

(ρP,ρI,ρR) = SeaWaterDensity(3.,35.5,3000.)
isapprox(ρI,1041.83267, rtol=1e-6)
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MITgcm.MixedLayerDepth — Function

MixedLayerDepth(Θ,Σ,Δ,mthd)

Compute mixed layer depth from potential temperature (Θ in °C), salinity (Σ in psu) and depth (Δ in method) according to various formulas (mthd == "BM", "Suga", "Kara"). Inputs must be dense vectors without any missing value (or NaN, etc).

D=collect(0.0:1.0:500.0); tmp=(1.0.-tanh.(5*(-1 .+ 2/D[end]*D)));
T=2.0 .+ 8.0*tmp; S=34.0 .+ 0.5*tmp;
(ρP,ρI,ρR) = SeaWaterDensity(T,S,D);

mld=MixedLayerDepth(T,S,D,"BM"); isapprox(mld,134.0)

using Plots
plot(ρP,-D,w=2,label="Potential Density",ylabel="Depth")
plot!(vec([ρP[1] ρP[end]]),-fill(mld,2),label="Mixed Layer Depth",w=2,c="black",s=:dash)
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