Hi @Wilton_Aguiar. We might have to wait until @CharlesTurner is back from leave to answer your question about using old versions. But I can help with accessing the data you want using the latest version.
The reason this takes so long is because these data include the 2D grid coordinates TLON, TLAT, ULON, ULAT in every single file. With its default arguments, xarray works hard to check that these coordinates are compatible at every time. This has come up a few times before, e.g. in the context of the cosima cookbook here.
You can pass some additional arguments when you open the data to tell xarray not to do these checks. This will speed things up:
experiment1 = "01deg_jra55v140_iaf_cycle4"
access_var_ice = 'aice'
esmds = cat[experiment1].search(variable=[access_var_ice], frequency="1day")
xarray_combine_by_coords_kwargs = dict(
compat="override",
data_vars="minimal",
coords="minimal",
join="outer",
)
access_variables_m = esmds.to_dataset_dict(
xarray_combine_by_coords_kwargs=xarray_combine_by_coords_kwargs
)
Or, if you want to filter based on the file_id before opening the data you can do something like:
file_id = 'seaIce.1day.d2:2.nc:5.ni:3600.nj:2700'
access_variables_m = esmds.search(file_id=file_id).to_dask(
xarray_combine_by_coords_kwargs=xarray_combine_by_coords_kwargs
)