ClimaOcean.jl

🌎 Realistic ocean-only and coupled ocean + sea-ice simulations driven by prescribed atmospheres and based on Oceananigans and ClimaSeaIce.

ClimaOcean implements a framework for driving coupled ocean and sea ice simulations with prescribed atmospheres, using bulk formula to compute atmosphere-ocean, atmosphere-ice, and ocean-ice fluxes of heat, momentum, and freshwater. ClimaOcean builds off the Oceananigans framework, which provides tools for gridded finite volume computations on CPUs and GPUs and building ocean-flavored fluid dynamics simulations. ClimaSeaIce, which provides software for both stand-alone and coupled sea ice simulations, is also built with Oceananigans.

ClimaOcean's core abstractions are OceanSeaIceModel which encapsulates the ocean simulation, sea ice simulation, prescribed atmospheric state, atmospheric thermodynamic parameters, and parameterizations that define how the three communicate. ClimaOcean also implements ocean_simulation, a utility for building realistic, hydrostatic ocean simulations with Oceananigans ensuring compatibility with OceanSeaIceModel.

ClimaOcean is written in Julia by the Climate Modeling Alliance and heroic external collaborators.

Installation

ClimaOcean is a registered Julia package. So to install it,

1. Download Julia.

2. Launch Julia and type

julia> using Pkg

julia> Pkg.add("ClimaOcean")

Quick start

The following script implements a near-global ocean simulation initialized from the ECCO state estimate and coupled to a prescribed atmosphere derived from the JRA55-do reanalysis:

using Oceananigans
using Oceananigans.Units
using Dates, CFTime
import ClimaOcean

arch = GPU()
grid = LatitudeLongitudeGrid(arch,
                             size = (1440, 560, 10),
                             halo = (7, 7, 7),
                             longitude = (0, 360),
                             latitude = (-70, 70),
                             z = (-3000, 0))

bathymetry = ClimaOcean.regrid_bathymetry(grid) # builds gridded bathymetry based on ETOPO1
grid = ImmersedBoundaryGrid(grid, GridFittedBottom(bathymetry))

# Build an ocean simulation initialized to the ECCO state estimate on Jan 1, 1993
ocean = ClimaOcean.ocean_simulation(grid)
date  = DateTimeProlepticGregorian(1993, 1, 1)
set!(ocean.model, T = ClimaOcean.ECCOMetadata(:temperature; date),
                  S = ClimaOcean.ECCOMetadata(:salinity; date))

# Build and run an OceanSeaIceModel (with no sea ice component) forced by JRA55 reanalysis
atmosphere = ClimaOcean.JRA55PrescribedAtmosphere(arch)
coupled_model = ClimaOcean.OceanSeaIceModel(ocean; atmosphere)
simulation = Simulation(coupled_model, Δt=5minutes, stop_time=30days)
run!(simulation)

The simulation above achieves approximately 8 simulated years per day of wall time on an Nvidia H100 GPU.

We can leverage Oceananigans features to plot the surface speed at the end of the simulation:

u, v, w = ocean.model.velocities
speed = Field(sqrt(u^2 + v^2))
compute!(speed)

using GLMakie
heatmap(view(speed, :, :, ocean.model.grid.Nz), colorrange=(0, 0.5), colormap=:magma, nan_color=:lightgray)