Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: TypeError
Message: Couldn't cast array of type
struct<bounds: string, units: string, long_name: string, standard_name: string, axis: string, _FillValue: string>
to
{'long_name': Value('string'), 'molecular_weight': Value('string'), 'units': Value('string'), 'cell_methods': Value('string'), 'cell_measures': Value('string'), '_FillValue': Value('string')}
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2158, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<bounds: string, units: string, long_name: string, standard_name: string, axis: string, _FillValue: string>
to
{'long_name': Value('string'), 'molecular_weight': Value('string'), 'units': Value('string'), 'cell_methods': Value('string'), 'cell_measures': Value('string'), '_FillValue': Value('string')}Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
jax-gcm boundary conditions and emissions
Input data for jax-gcm
(jcm), a fully differentiable atmospheric GCM in JAX. Two tiers:
products/ — grid-independent source products
| store | contents | source |
|---|---|---|
ceds_anthro.zarr |
anthropogenic SO2/BC/OC/NH3 flux, sector-summed, 0.5°, monthly 1850–2023 + PI (1850–59) / PD (2005–14) climatologies | CEDS-CMIP-2025-04-18 (input4MIPs CMIP7) |
bb4cmip7.zarr |
open-burning SO2/BC/OC/NH3 flux, 0.25°, monthly 1850–2023 + PI/PD climatologies | DRES-CMIP-BB4CMIP7-2-0 |
era5_land_climo_2005-2014_0p25.nc |
skin/soil temperature, 3-layer soil water, snow depth, albedo, land-sea mask, 0.25° | ERA5 (NCAR RDA d633001) |
sso/sso_gmted2010_*.nc |
Lott & Miller (1997) subgrid-orography statistics from the 30″ GMTED2010 DEM | USGS GMTED2010 |
All fluxes are kg m⁻² s⁻¹. Regridding always starts from these — never from an already-regridded bundle.
bundles/ — per-grid, ready for the model
For each grid (t63 96×192, t106 160×320 Gaussian; ne30pg3
native columns), the files jcm.Model reads directly:
terrain.nc— orography + land-sea mask + six SSO fields (jcm-canonical layout)forcing_{pi,pd}.nc— 12-month SST/sea-ice (PCMDI-AMIP-1-1-10) + ERA5 land-surface climatology. PI SST/ice is the 1870–1879 mean, the earliest observed decade — no observational 1850 SST exists.emissions_{pi,pd}.nc— per-super-sector surface flux (surface_combustion,biomass_burning) × (SO2, BC, OC)dms.nc,dust.nc— Lana et al. (2011) seawater DMS; CAM dust erodibility<grid>_l{47,95}/ozone_{pi,pd}.nc— FZJ-CMIP-ozone-1-0 pre-interpolated to the ECHAM hybrid levels<grid>_l{47,95}/oxidants_{1850,2014}.nc— CAM OH/NO3/O3/H2O2 (L26 source, clamped above the CAM lid)
Usage
from jcm.data.remote import bundle_file
terrain = bundle_file("t63", "terrain.nc")
ozone = bundle_file("t63_l47", "ozone_pd.nc")
registry.json lists every file with size and sha256.
Licences and provenance
Emissions, ozone and SST/sea-ice derive from CMIP7 input4MIPs products (CC-BY-4.0). ERA5 derivatives are provided under the Copernicus licence terms. GMTED2010 is a public-domain USGS product. See each file's attributes for the exact source path and processing history.
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