# Intake loading aice\_m as two separate datasets **URL:** \ **Category:** COSIMA\ **Tags:** help, cosima, access-om2, intake\ **Created:** [2 July 2026 06:50 UTC](https://forum.access-hive.org.au/t/intake-loading-aice-m-as-two-separate-datasets/6586 "2026-07-02T06:50:38Z")\ **Posts on this page:** 3\ **Page:** 1
**Author:** ![hrsdawson](https://sea2.discourse-cdn.com/flex020/user_avatar/forum.access-hive.org.au/hrsdawson/32/218_2.png) [@hrsdawson](https://forum.access-hive.org.au/u/hrsdawson)\ **Post date:** [2 July 2026 06:50 UTC](https://forum.access-hive.org.au/t/intake-loading-aice-m-as-two-separate-datasets/6586/1 "2026-07-02T06:50:38Z")
I’m trying to load the variable `aice_m` from the `01deg_jra55v140_iaf_cycle4`experiment using intake, but intake is returning two separate datasets for this one diagnostic. This is the code I’m using to read the data: ```auto dictionary = catalog['01deg_jra55v140_iaf_cycle4'].search(variable='aice_m').to_dataset_dict( xarray_open_kwargs={"chunks": -1 ,"decode_coords": False,}, xarray_combine_by_coords_kwargs={"compat": "override", "data_vars": "minimal", "coords": "minimal",},) ``` And this is the output: ```auto {'seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700.nkice:4.mean': Size: 2GB Dimensions: (time: 59, nj: 2700, ni: 3600) Coordinates: * time (time) datetime64[ns] 472B 1958-02-01 1958-03-01 ... 2017-01-01 Dimensions without coordinates: nj, ni Data variables: aice_m (time, nj, ni) float32 2GB dask.array Attributes: (12/14) title: sea ice model output for CICE contents: Diagnostic and Prognostic Variables source: Los Alamos Sea Ice Model (CICE) Version 5 time_period_freq: month_1 comment3: seconds elapsed into model date: 0 conventions: CF-1.0 ... ... intake_esm_attrs:file_id: seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700.n... intake_esm_attrs:frequency: 1mon intake_esm_attrs:realm: seaIce intake_esm_attrs:temporal_label: mean intake_esm_attrs:_data_format_: netcdf intake_esm_dataset_key: seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700.n..., 'seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700.mean': Size: 26GB Dimensions: (time: 673, nj: 2700, ni: 3600) Coordinates: * time (time) datetime64[ns] 5kB 1960-01-01 1960-02-01 ... 2019-01-01 Dimensions without coordinates: nj, ni Data variables: aice_m (time, nj, ni) float32 26GB dask.array Attributes: (12/14) title: sea ice model output for CICE contents: Diagnostic and Prognostic Variables source: Los Alamos Sea Ice Model (CICE) Version 5 time_period_freq: month_1 comment3: seconds elapsed into model date: 0 conventions: CF-1.0 ... ... intake_esm_attrs:file_id: seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 intake_esm_attrs:frequency: 1mon intake_esm_attrs:realm: seaIce intake_esm_attrs:temporal_label: mean intake_esm_attrs:_data_format_: netcdf intake_esm_dataset_key: seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700.mean} ``` The first dataset in this dictionary contains `aice_m` data from 1958 to 1959 and 2014 to 2017, while the second dataset contains all other time steps. @aekiss and I think this is because in the 1958-1959 & 2014-2017 years of the simulation, certain sea ice diagnostics were saved that used a grid coordinate called`nkice`. Even though `aice_m` doesn’t use this coordinate, intake doesn’t seem to recognise this, and instead groups them as separate datasets. Is there a way to make intake recognise this is one single dataset @CharlesTurner ? ---
**Author:** ![CharlesTurner](https://sea2.discourse-cdn.com/flex020/user_avatar/forum.access-hive.org.au/charlesturner/32/2518_2.png) [@CharlesTurner](https://forum.access-hive.org.au/u/CharlesTurner)\ **Post date:** [2 July 2026 08:51 UTC](https://forum.access-hive.org.au/t/intake-loading-aice-m-as-two-separate-datasets/6586/2 "2026-07-02T08:51:40Z")
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**Author:** ![CharlesTurner](https://sea2.discourse-cdn.com/flex020/user_avatar/forum.access-hive.org.au/charlesturner/32/2518_2.png) [@CharlesTurner](https://forum.access-hive.org.au/u/CharlesTurner)\ **Post date:** [3 July 2026 00:42 UTC](https://forum.access-hive.org.au/t/intake-loading-aice-m-as-two-separate-datasets/6586/3 "2026-07-03T00:42:51Z")
Yup, what you said about the cause of the issue is bang on. This has been a bit of a gripe of mine with our current catalog build system for a while, but a clean solution which doesn’t cause more problems than it solves has been eluding me. You can (hackily) fix it via (I’ve tested this & it works): ```python # The catalog you had: catalog = intake.cat.access_nri esm_ds = catalog['01deg_jra55v140_iaf_cycle4'].search(variable='aice_m') # And rewriting its entries to be loadable as one dataset df = esm_ds.df df['file_id'] = df['file_id'].str.replace('seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700.nkice:4', 'seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700') esm_ds.esmcat._df = df esm_ds.to_dask( xarray_open_kwargs={"chunks": -1 ,"decode_coords": False,}, xarray_combine_by_coords_kwargs={"compat": "override", "data_vars": "minimal", "coords": "minimal",} ) ``` which overwrites the file IDs to be compatible. It would be fairly straightforward to add a `merge_datasets` or something like that which would handle this for you, which might function as a decent halfway house for the time being. I’ll scratch my head a bit more and see if I can come up with a cleaner solution!