Physical Oceanography
A selection of gridded estimates of the ocean state for physical variables like temperature, salinity, and currents.
These data sets are made available by this package via the artifact system and retrieved from e.g. the Harvard Dataverse Repository.
They can be relatively large files, compared to the package codes, so they are therefore handled lazily (only downloaded when needed).
| Artifact path | File Type | Download Method |
|---|---|---|
| ECCOclim_path | NetCDF | lazy, by variable, dataverse |
| OCCAclim_path | NetCDF | lazy, by variable, dataverse |
| MITPROFclim_path | binary | lazy, whole, zenodo |
| ECCOdiags_path | JLD2 | lazy, whole, zenodo |
In ECCO_standard_plots (➭ code link) we visualize a set of summary statistics derived from full ocean state estimates as an example (ECCOdiags_path).
Basic Usage
using OceanStateEstimation
get_occa_variable_if_needed("SIarea")
readdir(OCCAclim_path)or
using OceanStateEstimation, MeshArrays
γ=GridSpec("LatLonCap",MeshArrays.GRID_LLC90)
tmp=OceanStateEstimation.get_ecco_files(γ,"ETAN")Bio-Geo-Chemical Climatology
CBIOMES-global (alpha version) is a global ocean state estimate that covers the period from 1992 to 2011. It is based on Forget et al 2015 for ocean physics MIT general circulation model and on Dutkiewicz et al 2015 for marine biogeochemistry and ecosystems Darwin Project model.
- CBIOMES_climatology_plot (➭ code link) : visualize the climatology maps interactively using Pluto.jl
- CBIOMES_climatology_create (➭ code link) : recreate the climatology file. The original is archived here in zenodo.
Or in the julia REPL, for example :
using OceanStateEstimation, NCTiles
OceanStateEstimation.CBIOMESclim_download()
fil_out=joinpath(CBIOMESclim_path,"CBIOMES-global-alpha-climatology.nc")
nc=NCTiles.NCDataset(fil_out,"r")