Intro

Climatologies are readily downloaded and accessed using the Scratch.jl artifact system as explained below.

Use Examples

ECCO

ECCO climatology files can downloaded using get_ecco_files. These files are for version 4 release 2, on the native model grid.

using Climatology
get_ecco_variable_if_needed("ETAN")

using MeshArrays, MITgcm, NetCDF
path=joinpath(ScratchSpaces.ECCO,"ETAN/ETAN")
γ=GridSpec("LatLonCap",MeshArrays.GRID_LLC90)
tmp=read_nctiles(path,"ETAN",γ,I=(:,:,1))

5×1 MeshArrays.gcmarray{Float64, 2, Matrix{Float64}}:
 [NaN NaN … NaN NaN; NaN NaN … NaN NaN; … ; NaN NaN … NaN NaN; NaN NaN … NaN NaN]
 [NaN NaN … NaN NaN; NaN NaN … NaN NaN; … ; NaN NaN … NaN NaN; NaN NaN … NaN NaN]
 [NaN NaN … NaN NaN; NaN NaN … NaN NaN; … ; NaN NaN … NaN NaN; NaN NaN … NaN NaN]
 [NaN NaN … NaN NaN; NaN NaN … NaN NaN; … ; NaN NaN … NaN NaN; NaN NaN … NaN NaN]
 [NaN NaN … NaN NaN; NaN NaN … NaN NaN; … ; NaN NaN … NaN NaN; NaN NaN … NaN NaN]

Precomputed quantities shown in ECCO_standard_plots.jl can be downloaded separately.

Climatology.ECCOdiags_add("release2")
readdir(ScratchSpaces.ECCO)

1-element Vector{String}:
 "ETAN"

OCCA

get_occa_variable_if_needed("SIarea")
readdir(ScratchSpaces.OCCA)

1-element Vector{String}:
 "SIarea.0406clim.nc"

CBIOMES

To retrieve the CBIOMES climatology, in the julia REPL for example :

withenv("DATADEPS_ALWAYS_ACCEPT"=>true) do
	path_clim1=datadep"CBIOMES-clim1"
	readdir(path_clim1)
end

1-element Vector{String}:
 "CBIOMES-global-alpha-climatology.nc"

And the files, now found in datadep"CBIOMES-clim1", can then be read using other libraries.

using NCDatasets
path_clim1=datadep"CBIOMES-clim1"
fil=joinpath(path_clim1,"CBIOMES-global-alpha-climatology.nc")
nc=NCDataset(fil,"r")
keys(nc)

21-element Vector{String}:
 "SST"
 "land"
 "t"
 "lat"
 "lon"
 "climatology_bounds"
 "tim"
 "Chl"
 "EuphoticDepth"
 "MLD"
 ⋮
 "Rrs412"
 "Rrs443"
 "Rrs490"
 "Rrs510"
 "Rrs555"
 "Rrs670"
 "SSS"
 "TKE"
 "WindSpeed"

MITprof

To retrieve the MITprof climatologies :

withenv("DATADEPS_ALWAYS_ACCEPT"=>true) do
	readdir(datadep"MITprof-clim1")
end

9-element Vector{String}:
 "S_OWPv1_M_eccollc_90x50.bin"
 "T_OWPv1_M_eccollc_90x50.bin"
 "basin_masks_eccollc_90x50.bin"
 "sigma_S_eccollc.bin"
 "sigma_S_mad_feb2013.bin"
 "sigma_S_nov2015.bin"
 "sigma_T_eccollc.bin"
 "sigma_T_mad_feb2013.bin"
 "sigma_T_nov2015.bin"

Path Names

Gridded fields are mostly retrieved from Harvard Dataverse. These can be relatively large files, compared to the package codes, so they are handled lazily (only downloaded when needed). Precomputed diagnostics have also been archived on zenodo.org.

Functions Reference

CBIOMESclim_download()

ECCOdiags_add(nam::String)

using Climatology
datadep"ECCO4R1-stdiags"
datadep"ECCO4R2-stdiags"
datadep"ECCO4R3-stdiags"
datadep"ECCO4R4-stdiags"
datadep"ECCO4R5-stdiags"
datadep"OCCA2HR1-stdiags"

ERA5_OISST_download()

MITPROFclim_download()

OISSTstats_download()

__init__standard_diags()

get_ecco_files(γ::gcmgrid,v::String,t=1)

using MeshArrays, Climatology, MITgcm
γ=GridSpec(ID=:LLC90)
Climatology.get_ecco_variable_if_needed("oceQnet")
tmp=read_nctiles(joinpath(ScratchSpaces.ECCO,"oceQnet/oceQnet"),"oceQnet",γ,I=(:,:,1))

get_ecco_variable_if_needed(v::String)

get_ecco_velocity_if_needed()

get_occa_variable_if_needed(v::String)

get_occa_velocity_if_needed()

unpackDV(filepath)