Get Started

WAVI.jl is a software package to simulate the flow of ice sheets. At its heart, it is a piece of software that solves equations that describe the flow of ice on continental lengthscales.

Here at WAVI.jl, we're trying to make our code as accessible and friendly as possible.

Installation

You will need to install Julia to run WAVI.jl.

You can install the latest version of WAVI using Julia's in-build package manager:

Installation

using Pkg
Pkg.add(PackageSpec(url="https://github.com/RJArthern/WAVI.jl.git"))

# Coming soon!
Pkg.add("WAVI"))

Usage

As an example, we can run the MISMIP+ experiment, the latest ice sheet model intercomparison.

First, we set up the grid along with other model parameters. We'll use a grid with 80x10 grid points and 8km resolution in both dimensions, and 4 vertical levels:

Grid Setup

using WAVI

grid = Grid(
    nx = 80,
    ny = 10,
    nσ = 4,
    dx = 8000.,
    dy = 8000.,
    u_iszero = ["north"],
    v_iszero = ["east", "west"]
)

bed = WAVI.mismip_plus_bed 
params = Params(accumulation_rate = 0.3)
solver_params =  SolverParams(maxiter_picard = 1)

Then we define the model, and we define timestepping parameters for out forwards simulations.

We'll want to run the simulation to steady state for 10000 years with a timestep of 0.5 years.

Finally we define our simulation using our model and timestepping parameters:

Model & Simulation definition

model = Model(
    grid = grid,
    bed_elevation = bed,
    params = params
)

timestepping_params = TimesteppingParams(
    dt = 0.5,
    end_time = 10000.
)

simulation = Simulation(
    model = model,
    timestepping_params = timestepping_params
)

With simulation defined, it's ready to go, let's run!

Running the model

run_simulation!(simulation)

It's as easy as that: entry into the state of the art ice sheet model intercomparison 😎.

Repository & Documentation

Discover more use cases in WAVI.jl's extensive documentation:

WAVI.jl Repository WAVI.jl Documentation

Extending WAVI

There are several other tools which help make WAVI easier to use at scale.