numerically solves the Shallow-Water Equations on a $\beta$-plane using finite-difference methods

allows the user to define custom heat-forcing $Q$

GillMatsuno.jl can be installed via

] add GillMatsuno

Due to the recent improvements in memory allocations in Julia, GillMatsuno.jlv2 works best in Julia v1.5 and above, but can work from v1.3 onwards.

Using GillMatsuno.jl

There are four components to running a model in GillMatsuno.jl. They are:

Grid G

Domain parameters D

Heat Source Q

Simulation Setup S

1. Defining the Grid G

GillMatsuno.jl uses a staggered Arakawa C-Grid. The Grid G is generated via the function GenerateGrid, as follows

G = GenerateGrid(size = (nx,ny), x = (xmin,xmax), y = (ymin,ymax))

It is to be noted that the shallow-water equations to be solved have been nondimensionalized. Typical values of xmin and xmax are O(25) (negative and positive respectively), and O(10) for ymin and ymax.

2. Defining the Domain Parameters D

We define the domain parameters using the DomainProperties() function. The default values are:

α represents the damping coefficient on the winds induced by the heat-forcing (default: α = 0.1)

β is the Coriolis Factor (nondimensionalized to β = 0.5 as the default)

g and H represent gravity and the height of the domain (both nondimensionalized to 1 as default)

D = DomainParameters(α=0.2,β=0.5,g=1.0,H=1.0)

3. Defining the Heat Source Q

The heat source Q is analogous to a mass source/sink. As of now, Q can only be defined as a gaussian peak (or the cumulative sums of gaussian peaks), though we aim to extend this to equatorial bands.

Q can be defined via the function QfieldProperties

Lx and Ly are the non-dimensionalized widths of the Q in the x- and y-directions respectively

Qx and Qy denote the location of the center of Q

4. Setting up the Simulation S

The simulation structure S is defined as follows:

S = CreateSimulation(δt=5e-4,tt=50,ft=0.5,fnc="test.nc")

Where we have that

δt is the model timestep

tt is the total model runtime

ft is the output frequency in model runtime

So, using the parameters above, we see that the model is ran for 10^6 timesteps, with the fields output every 10000 steps to the netCDF file test.nc.

5. Running the Simulation

With the fields we have defined above, we put them into the function runGillMatsuno(S,G,[Q],D), and then we can extract the fields and do plotting/analysis, as you wish!

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