CanESM5 output prepared for CMIP6
Load in Python
from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/thetao_Omon_CanESM5_piControl_r1i1p1f1_gn.yaml")
ds=cat.netcdf.read()Metadata
| title | CanESM5 output prepared for CMIP6 |
| location | /shared/cmip6/data/piControl/ocean/mon/Omon/thetao/CCCma.CanESM5/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/thetao_Omon_CanESM5_piControl_r1i1p1f1_gn.yaml |
| last updated | 2021-03-31 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, i: 360, j: 291, lev: 45, time: 12000, vertices: 4)
Coordinates:
* time (time) float64 1.223e+06 1.223e+06 ... 1.588e+06
* lev (lev) float64 3.047 9.454 16.36 ... 5.375e+03 5.625e+03
* j (j) int32 0 1 2 3 4 5 6 ... 284 285 286 287 288 289 290
* i (i) int32 0 1 2 3 4 5 6 ... 353 354 355 356 357 358 359
latitude (j, i) float64 dask.array<chunksize=(291, 360), meta=np.ndarray>
longitude (j, i) float64 dask.array<chunksize=(291, 360), meta=np.ndarray>
Dimensions without coordinates: bnds, vertices
Data variables:
time_bnds (time, bnds) float64 dask.array<chunksize=(120, 2), meta=np.ndarray>
lev_bnds (time, lev, bnds) float64 dask.array<chunksize=(120, 45, 2), meta=np.ndarray>
vertices_latitude (time, j, i, vertices) float64 dask.array<chunksize=(120, 291, 360, 4), meta=np.ndarray>
vertices_longitude (time, j, i, vertices) float64 dask.array<chunksize=(120, 291, 360, 4), meta=np.ndarray>
thetao (time, lev, j, i) float32 dask.array<chunksize=(120, 45, 291, 360), meta=np.ndarray>
Attributes:
CCCma_model_hash: 24718c8346665b218729640ffe79d263b76456c4
CCCma_parent_runid: rc3-pictrl
CCCma_pycmor_hash: 33c30511acc319a98240633965a04ca99c26427e
CCCma_runid: rc3.1-pictrl
Conventions: CF-1.7 CMIP-6.2
YMDH_branch_time_in_child: 5201:01:01:00
YMDH_branch_time_in_parent: 5201:01:01:00
activity_id: CMIP
branch_method: Spin-up documentation
branch_time_in_child: 1223115.0
branch_time_in_parent: 1223115.0
contact: ec.cccma.info-info.ccmac.ec@canada.ca
creation_date: 2019-05-02T00:40:05Z
data_specs_version: 01.00.29
experiment: pre-industrial control
experiment_id: piControl
external_variables: areacello volcello
forcing_index: 1
frequency: mon
further_info_url: https://furtherinfo.es-doc.org/CMIP6.CCCma.C...
grid: ORCA1 tripolar grid, 1 deg with refinement t...
grid_label: gn
history: 2019-05-02T00:40:05Z ;rewrote data to be con...
initialization_index: 1
institution: Canadian Centre for Climate Modelling and An...
institution_id: CCCma
mip_era: CMIP6
nominal_resolution: 100 km
parent_activity_id: CMIP
parent_experiment_id: piControl-spinup
parent_mip_era: CMIP6
parent_source_id: CanESM5
parent_time_units: days since 1850-01-01 0:0:0.0
parent_variant_label: r1i1p1f1
physics_index: 1
product: model-output
realization_index: 1
realm: ocean
references: Geophysical Model Development Special issue ...
source: CanESM5 (2019):
aerosol: interactive
atmo...
source_id: CanESM5
source_type: AOGCM
sub_experiment: none
sub_experiment_id: none
table_id: Omon
table_info: Creation Date:(20 February 2019) MD5:374fbe5...
title: CanESM5 output prepared for CMIP6
variable_id: thetao
variant_label: r1i1p1f1
version: v20190429
license: CMIP6 model data produced by The Government ...
cmor_version: 3.4.0
tracking_id: hdl:21.14100/2d8b9652-371a-426b-a9ff-7ae911f...xarray.Dataset
- bnds: 2
- i: 360
- j: 291
- lev: 45
- time: 12000
- vertices: 4
- time(time)float641.223e+06 1.223e+06 ... 1.588e+06
- bounds :
- time_bnds
- units :
- days since 1850-01-01 0:0:0.0
- calendar :
- 365_day
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([1223130.5, 1223160. , 1223189.5, ..., 1588038.5, 1588069. , 1588099.5])
- lev(lev)float643.047 9.454 ... 5.375e+03 5.625e+03
- bounds :
- lev_bnds
- units :
- m
- axis :
- Z
- positive :
- down
- long_name :
- ocean depth coordinate
- standard_name :
- depth
array([3.046773e+00, 9.454049e+00, 1.636397e+01, 2.389871e+01, 3.220929e+01, 4.148185e+01, 5.194513e+01, 6.387905e+01, 7.762451e+01, 9.359412e+01, 1.122835e+02, 1.342823e+02, 1.602840e+02, 1.910925e+02, 2.276233e+02, 2.708962e+02, 3.220169e+02, 3.821444e+02, 4.524429e+02, 5.340197e+02, 6.278525e+02, 7.347150e+02, 8.551112e+02, 9.892289e+02, 1.136922e+03, 1.297724e+03, 1.470893e+03, 1.655472e+03, 1.850365e+03, 2.054414e+03, 2.266454e+03, 2.485371e+03, 2.710133e+03, 2.939812e+03, 3.173588e+03, 3.410756e+03, 3.650712e+03, 3.892950e+03, 4.137047e+03, 4.382654e+03, 4.629485e+03, 4.877303e+03, 5.125919e+03, 5.375177e+03, 5.624952e+03]) - j(j)int320 1 2 3 4 5 ... 286 287 288 289 290
- units :
- 1
- long_name :
- cell index along second dimension
array([ 0, 1, 2, ..., 288, 289, 290], dtype=int32)
- i(i)int320 1 2 3 4 5 ... 355 356 357 358 359
- units :
- 1
- long_name :
- cell index along first dimension
array([ 0, 1, 2, ..., 357, 358, 359], dtype=int32)
- latitude(j, i)float64dask.array<chunksize=(291, 360), meta=np.ndarray>
- standard_name :
- latitude
- long_name :
- latitude
- units :
- degrees_north
- bounds :
- vertices_latitude
Array Chunk Bytes 838.08 kB 838.08 kB Shape (291, 360) (291, 360) Count 495 Tasks 1 Chunks Type float64 numpy.ndarray - longitude(j, i)float64dask.array<chunksize=(291, 360), meta=np.ndarray>
- standard_name :
- longitude
- long_name :
- longitude
- units :
- degrees_east
- bounds :
- vertices_longitude
Array Chunk Bytes 838.08 kB 838.08 kB Shape (291, 360) (291, 360) Count 495 Tasks 1 Chunks Type float64 numpy.ndarray
- time_bnds(time, bnds)float64dask.array<chunksize=(120, 2), meta=np.ndarray>
Array Chunk Bytes 192.00 kB 1.92 kB Shape (12000, 2) (120, 2) Count 300 Tasks 100 Chunks Type float64 numpy.ndarray - lev_bnds(time, lev, bnds)float64dask.array<chunksize=(120, 45, 2), meta=np.ndarray>
Array Chunk Bytes 8.64 MB 86.40 kB Shape (12000, 45, 2) (120, 45, 2) Count 400 Tasks 100 Chunks Type float64 numpy.ndarray - vertices_latitude(time, j, i, vertices)float64dask.array<chunksize=(120, 291, 360, 4), meta=np.ndarray>
- units :
- degrees_north
Array Chunk Bytes 40.23 GB 402.28 MB Shape (12000, 291, 360, 4) (120, 291, 360, 4) Count 400 Tasks 100 Chunks Type float64 numpy.ndarray - vertices_longitude(time, j, i, vertices)float64dask.array<chunksize=(120, 291, 360, 4), meta=np.ndarray>
- units :
- degrees_east
Array Chunk Bytes 40.23 GB 402.28 MB Shape (12000, 291, 360, 4) (120, 291, 360, 4) Count 400 Tasks 100 Chunks Type float64 numpy.ndarray - thetao(time, lev, j, i)float32dask.array<chunksize=(120, 45, 291, 360), meta=np.ndarray>
- standard_name :
- sea_water_potential_temperature
- long_name :
- Sea Water Potential Temperature
- comment :
- Diagnostic should be contributed even for models using conservative temperature as prognostic field.
- units :
- degC
- original_name :
- votemper
- cell_methods :
- area: mean where sea time: mean
- cell_measures :
- area: areacello volume: volcello
Array Chunk Bytes 226.28 GB 2.26 GB Shape (12000, 45, 291, 360) (120, 45, 291, 360) Count 300 Tasks 100 Chunks Type float32 numpy.ndarray
- CCCma_model_hash :
- 24718c8346665b218729640ffe79d263b76456c4
- CCCma_parent_runid :
- rc3-pictrl
- CCCma_pycmor_hash :
- 33c30511acc319a98240633965a04ca99c26427e
- CCCma_runid :
- rc3.1-pictrl
- Conventions :
- CF-1.7 CMIP-6.2
- YMDH_branch_time_in_child :
- 5201:01:01:00
- YMDH_branch_time_in_parent :
- 5201:01:01:00
- activity_id :
- CMIP
- branch_method :
- Spin-up documentation
- branch_time_in_child :
- 1223115.0
- branch_time_in_parent :
- 1223115.0
- contact :
- ec.cccma.info-info.ccmac.ec@canada.ca
- creation_date :
- 2019-05-02T00:40:05Z
- data_specs_version :
- 01.00.29
- experiment :
- pre-industrial control
- experiment_id :
- piControl
- external_variables :
- areacello volcello
- forcing_index :
- 1
- frequency :
- mon
- further_info_url :
- https://furtherinfo.es-doc.org/CMIP6.CCCma.CanESM5.piControl.none.r1i1p1f1
- grid :
- ORCA1 tripolar grid, 1 deg with refinement to 1/3 deg within 20 degrees of the equator; 361 x 290 longitude/latitude; 45 vertical levels; top grid cell 0-6.19 m
- grid_label :
- gn
- history :
- 2019-05-02T00:40:05Z ;rewrote data to be consistent with CMIP for variable thetao found in table Omon.; Output from $runid
- initialization_index :
- 1
- institution :
- Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC V8P 5C2, Canada
- institution_id :
- CCCma
- mip_era :
- CMIP6
- nominal_resolution :
- 100 km
- parent_activity_id :
- CMIP
- parent_experiment_id :
- piControl-spinup
- parent_mip_era :
- CMIP6
- parent_source_id :
- CanESM5
- parent_time_units :
- days since 1850-01-01 0:0:0.0
- parent_variant_label :
- r1i1p1f1
- physics_index :
- 1
- product :
- model-output
- realization_index :
- 1
- realm :
- ocean
- references :
- Geophysical Model Development Special issue on CanESM5 (https://www.geosci-model-dev.net/special_issues.html)
- source :
- CanESM5 (2019): aerosol: interactive atmos: CanAM5 (T63L49 native atmosphere, T63 Linear Gaussian Grid; 128 x 64 longitude/latitude; 49 levels; top level 1 hPa) atmosChem: specified oxidants for aerosols land: CLASS3.6/CTEM1.2 landIce: specified ice sheets ocean: NEMO3.4.1 (ORCA1 tripolar grid, 1 deg with refinement to 1/3 deg within 20 degrees of the equator; 361 x 290 longitude/latitude; 45 vertical levels; top grid cell 0-6.19 m) ocnBgchem: Canadian Model of Ocean Carbon (CMOC); NPZD ecosystem with OMIP prescribed carbonate chemistry seaIce: LIM2
- source_id :
- CanESM5
- source_type :
- AOGCM
- sub_experiment :
- none
- sub_experiment_id :
- none
- table_id :
- Omon
- table_info :
- Creation Date:(20 February 2019) MD5:374fbe5a2bcca535c40f7f23da271e49
- title :
- CanESM5 output prepared for CMIP6
- variable_id :
- thetao
- variant_label :
- r1i1p1f1
- version :
- v20190429
- license :
- CMIP6 model data produced by The Government of Canada (Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada) is licensed under a Creative Commons Attribution ShareAlike 4.0 International License (https://creativecommons.org/licenses). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and at https:///pcmdi.llnl.gov/. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.
- cmor_version :
- 3.4.0
- tracking_id :
- hdl:21.14100/2d8b9652-371a-426b-a9ff-7ae911fa27c9