Installation of Julia and ClimaLand

ClimaLand is provided as a Julia package, so it requires having Julia installed. Information about Julia packages is available on the Julia website.

First, download and install Julia by following the instructions at https://julialang.org/downloads/. Then, you can launch a Julia REPL by running julia --project and install the ClimaLand.jl package by running the following within the REPL:

using Pkg
Pkg.add(ClimaLand)

Running a simple soil model

Now that we have Julia installed, let's set up and run a simple ClimaLand simulation! You can follow along by copying the following code segments into your REPL.

First we import the necessary Julia packages:

import ClimaParams as CP
using ClimaLand
using ClimaLand.Domains
using ClimaLand.Soil
import ClimaLand.Simulations: LandSimulation, solve!
import ClimaLand.Parameters as LP
using Dates

Choose a floating point precision, and get the parameter set, which holds constants used across CliMA models. Note: we use SI units unless otherwise specified. See our Physical Units documentation for more information.

FT = Float32
default_params_filepath =
    joinpath(pkgdir(ClimaLand), "toml", "default_parameters.toml")
toml_dict = LP.create_toml_dict(FT, default_params_filepath);
earth_param_set = LP.LandParameters(toml_dict);

We will run this simulation on a column domain with 1 meter depth, at a lat/lon location near Pasadena, California.

zmax = FT(0)
zmin = FT(-1.0)
longlat = FT.((-118.1, 34.1))
domain = Domains.Column(; zlim = (zmin, zmax), nelements = 10, longlat);
surface_space = domain.space.surface;

We choose the initial and final simulation times as DateTimes, and a timestep in seconds.

start_date = DateTime(2008);
stop_date = start_date + Second(60 * 60 * 72);
dt = 1000.0;

The soil model takes in 2 forcing objects, atmosphere and radiation, which we read in from ERA5 data.

era5_ncdata_path =
    ClimaLand.Artifacts.era5_land_forcing_data2008_path(; lowres = true);
atmos, radiation = ClimaLand.prescribed_forcing_era5(
    era5_ncdata_path,
    surface_space,
    start_date,
    earth_param_set,
    FT,
);

Now, we can create the EnergyHydrology model. This constructor uses default parameters and parameterizations, but these can also be overwritten, which we'll demonstrate in later tutorials.

model = Soil.EnergyHydrology{FT}(
    domain,
    (; atmos, radiation),
    toml_dict,
);

Define a function to set initial conditions for the prognostic variables.

function set_ic!(Y, p, t0, model)
    Y.soil.ϑ_l .= FT(0.24);
    Y.soil.θ_i .= FT(0.0);
    T = FT(290.15);
    ρc_s = Soil.volumetric_heat_capacity.(
        Y.soil.ϑ_l,
        Y.soil.θ_i,
        model.parameters.ρc_ds,
        model.parameters.earth_param_set,
    );
    Y.soil.ρe_int .=
        Soil.volumetric_internal_energy.(
            Y.soil.θ_i,
            ρc_s,
            T,
            model.parameters.earth_param_set,
        );
end

Now construct the LandSimulation object, which contains the model and additional timestepping information.

simulation = LandSimulation(start_date, stop_date, dt, model; set_ic!, user_callbacks = ());

Now we can run the simulation!

solve!(simulation);

That's it! For more complex examples and pretty plots, please see the tutorial section of our docs.

Atmospheric forcing data citation: Hersbach, Hans, et al. "The ERA5 global reanalysis." Quarterly journal of the royal meteorological society 146.730 (2020): 1999-2049.