Open AbbySh opened 5 months ago
Thanks for using xMIP @AbbySh. Do you have a code snippet that I can use to produce this error? That will make it much easier to look into this.
from xmip.utils import google_cmip_col
from xmip.preprocessing import combined_preprocessing
from xmip.postprocessing import concat_experiments, merge_variables
cat = col.search(
variable_id=['tos', 'sos', 'chl', 'mlotst', 'spco2', 'dpco2'],
table_id='Omon', # monthly ocean output only
experiment_id=['historical','ssp245'],
require_all_on=['source_id', 'member_id', 'grid_label'] # this ensures that results will have all variables and experiments available
)
ddict = cat.to_dataset_dict(
preprocess=combined_preprocessing,
xarray_open_kwargs=dict(use_cftime=True),
aggregate=False
)
ds = merge_variables(ddict)
ds = concat_experiments(ds)
This should reproduce it, let me know!
Taking a look now.
I was just able to run this without error on the LEAP-Pange hub ('pangeo/pangeo-notebook:2023.08.29'
):
from xmip.utils import google_cmip_col
from xmip.preprocessing import combined_preprocessing
from xmip.postprocessing import concat_experiments, merge_variables
col = google_cmip_col()
cat = col.search(
variable_id=['tos', 'sos', 'chl', 'mlotst', 'spco2', 'dpco2'],
table_id='Omon', # monthly ocean output only
experiment_id=['historical','ssp245'],
require_all_on=['source_id', 'member_id', 'grid_label'] # this ensures that results will have all variables and experiments available
)
ddict = cat.to_dataset_dict(
preprocess=combined_preprocessing,
xarray_open_kwargs=dict(use_cftime=True),
aggregate=False
)
ds = merge_variables(ddict)
ds = concat_experiments(ds)
The only change is the
col = google_cmip_col()
line. Is it possible that you had some broken collection object still in memory?
The resulting datasets look like the time was concatenated properly:
from xmip.postprocessing: concat_experiments, merge_variables are not working on CESM2 members. Example error/warning:
This causes historical not to combine with future (in our case, ssp245)