CNRM-CM5 model output prepared for CMIP5 pre-industrial control
Load in Python
from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/vo_Omon_CNRM-CM5_piControl_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | CNRM-CM5 model output prepared for CMIP5 pre-industrial control |
| location | /shared/cmip5/data/piControl/ocean/mon/Omon/vo/CNRM-CERFACS.CNRM-CM5/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/vo_Omon_CNRM-CM5_piControl_r1i1p1.yaml |
| last updated | 2013-06-14 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, i: 362, j: 292, lev: 42, time: 10200, vertices: 4)
Coordinates:
* time (time) float64 15.5 45.0 74.5 ... 2.885e+05 2.885e+05
* lev (lev) float64 5.022 15.08 25.16 ... 5.051e+03 5.35e+03
* j (j) int32 1 2 3 4 5 6 7 8 ... 285 286 287 288 289 290 291 292
* i (i) int32 1 2 3 4 5 6 7 8 ... 355 356 357 358 359 360 361 362
lat (j, i) float32 dask.array<chunksize=(292, 362), meta=np.ndarray>
lon (j, i) float32 dask.array<chunksize=(292, 362), 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, 42, 2), meta=np.ndarray>
lat_vertices (time, j, i, vertices) float32 dask.array<chunksize=(120, 292, 362, 4), meta=np.ndarray>
lon_vertices (time, j, i, vertices) float32 dask.array<chunksize=(120, 292, 362, 4), meta=np.ndarray>
vo (time, lev, j, i) float32 dask.array<chunksize=(120, 42, 292, 362), meta=np.ndarray>
Attributes:
institution: CNRM (Centre National de Recherches Meteorologiqu...
institute_id: CNRM-CERFACS
experiment_id: piControl
source: CNRM-CM5 2010 Atmosphere: ARPEGE-Climat (V5.2.1, ...
model_id: CNRM-CM5
forcing: N/A
parent_experiment_id: N/A
parent_experiment_rip: r1ip
branch_time: 0.0
contact: for all but decadal predictions : contact.CMIP5@m...
comment: Soil layers depth scheme is specific for mrlsl an...
references: See http://www.cnrm.meteo.fr/cmip5 - Follow model...
initialization_method: 1
physics_version: 1
tracking_id: 172d923a-df83-47a4-b6c3-125e1d66d7b5
product: output
experiment: pre-industrial control
frequency: mon
creation_date: 2011-10-11T18:43:44Z
history: 2011-10-11T18:43:44Z CMOR rewrote data to comply ...
Conventions: CF-1.4
project_id: CMIP5
table_id: Table Omon (26 July 2011) 25bb94a0408beca44c0f5b6...
title: CNRM-CM5 model output prepared for CMIP5 pre-indu...
parent_experiment: N/A
modeling_realm: ocean
realization: 1
cmor_version: 2.7.1xarray.Dataset
- bnds: 2
- i: 362
- j: 292
- lev: 42
- time: 10200
- vertices: 4
- time(time)float6415.5 45.0 ... 2.885e+05 2.885e+05
- bounds :
- time_bnds
- calendar :
- gregorian
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([1.550000e+01, 4.500000e+01, 7.450000e+01, ..., 2.884655e+05, 2.884960e+05, 2.885265e+05]) - lev(lev)float645.022 15.08 ... 5.051e+03 5.35e+03
- bounds :
- lev_bnds
- units :
- m
- axis :
- Z
- positive :
- down
- long_name :
- ocean depth coordinate
- standard_name :
- depth
array([5.021590e+00, 1.507854e+01, 2.516046e+01, 3.527829e+01, 4.544776e+01, 5.569149e+01, 6.604198e+01, 7.654591e+01, 8.727029e+01, 9.831118e+01, 1.098062e+02, 1.219519e+02, 1.350285e+02, 1.494337e+02, 1.657285e+02, 1.846975e+02, 2.074254e+02, 2.353862e+02, 2.705341e+02, 3.153741e+02, 3.729655e+02, 4.468009e+02, 5.405022e+02, 6.573229e+02, 7.995496e+02, 9.679958e+02, 1.161806e+03, 1.378661e+03, 1.615291e+03, 1.868071e+03, 2.133517e+03, 2.408583e+03, 2.690780e+03, 2.978166e+03, 3.269278e+03, 3.563041e+03, 3.858676e+03, 4.155628e+03, 4.453502e+03, 4.752021e+03, 5.050990e+03, 5.350272e+03]) - j(j)int321 2 3 4 5 6 ... 288 289 290 291 292
- units :
- 1
- long_name :
- cell index along second dimension
array([ 1, 2, 3, ..., 290, 291, 292], dtype=int32)
- i(i)int321 2 3 4 5 6 ... 358 359 360 361 362
- units :
- 1
- long_name :
- cell index along first dimension
array([ 1, 2, 3, ..., 360, 361, 362], dtype=int32)
- lat(j, i)float32dask.array<chunksize=(292, 362), meta=np.ndarray>
- standard_name :
- latitude
- long_name :
- latitude coordinate
- units :
- degrees_north
- bounds :
- lat_vertices
Array Chunk Bytes 422.82 kB 422.82 kB Shape (292, 362) (292, 362) Count 420 Tasks 1 Chunks Type float32 numpy.ndarray - lon(j, i)float32dask.array<chunksize=(292, 362), meta=np.ndarray>
- standard_name :
- longitude
- long_name :
- longitude coordinate
- units :
- degrees_east
- bounds :
- lon_vertices
Array Chunk Bytes 422.82 kB 422.82 kB Shape (292, 362) (292, 362) Count 420 Tasks 1 Chunks Type float32 numpy.ndarray
- time_bnds(time, bnds)float64dask.array<chunksize=(120, 2), meta=np.ndarray>
Array Chunk Bytes 163.20 kB 1.92 kB Shape (10200, 2) (120, 2) Count 255 Tasks 85 Chunks Type float64 numpy.ndarray - lev_bnds(time, lev, bnds)float64dask.array<chunksize=(120, 42, 2), meta=np.ndarray>
Array Chunk Bytes 6.85 MB 80.64 kB Shape (10200, 42, 2) (120, 42, 2) Count 340 Tasks 85 Chunks Type float64 numpy.ndarray - lat_vertices(time, j, i, vertices)float32dask.array<chunksize=(120, 292, 362, 4), meta=np.ndarray>
- units :
- degrees_north
Array Chunk Bytes 17.25 GB 202.95 MB Shape (10200, 292, 362, 4) (120, 292, 362, 4) Count 340 Tasks 85 Chunks Type float32 numpy.ndarray - lon_vertices(time, j, i, vertices)float32dask.array<chunksize=(120, 292, 362, 4), meta=np.ndarray>
- units :
- degrees_east
Array Chunk Bytes 17.25 GB 202.95 MB Shape (10200, 292, 362, 4) (120, 292, 362, 4) Count 340 Tasks 85 Chunks Type float32 numpy.ndarray - vo(time, lev, j, i)float32dask.array<chunksize=(120, 42, 292, 362), meta=np.ndarray>
- standard_name :
- sea_water_y_velocity
- long_name :
- Sea Water Y Velocity
- units :
- m s-1
- original_name :
- vo
- original_units :
- m/s
- history :
- 2011-10-11T18:43:35Z altered by CMOR: Converted units from 'm/s' to 'm s-1'.
- cell_methods :
- time: mean
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_ocean_fx_CNRM-CM5_piControl_r0i0p0.nc
Array Chunk Bytes 181.13 GB 2.13 GB Shape (10200, 42, 292, 362) (120, 42, 292, 362) Count 255 Tasks 85 Chunks Type float32 numpy.ndarray
- institution :
- CNRM (Centre National de Recherches Meteorologiques, Meteo-France, Toulouse,&
- institute_id :
- CNRM-CERFACS
- experiment_id :
- piControl
- source :
- CNRM-CM5 2010 Atmosphere: ARPEGE-Climat (V5.2.1, TL127L31); Ocean: &
- model_id :
- CNRM-CM5
- forcing :
- N/A
- parent_experiment_id :
- N/A
- parent_experiment_rip :
- r1ip
- branch_time :
- 0.0
- contact :
- for all but decadal predictions : contact.CMIP5@meteo.fr - METEO-FRANCE, CNRM/GMGEC/ASTER, CNRS URA 1357, 42 Av. Coriolis F-31057 TOULOUSE CEDEX 1 &
- comment :
- Soil layers depth scheme is specific for mrlsl and tsl - see variable-level comments. &
- references :
- See http://www.cnrm.meteo.fr/cmip5 - Follow model description link
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- 172d923a-df83-47a4-b6c3-125e1d66d7b5
- product :
- output
- experiment :
- pre-industrial control
- frequency :
- mon
- creation_date :
- 2011-10-11T18:43:44Z
- history :
- 2011-10-11T18:43:44Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table Omon (26 July 2011) 25bb94a0408beca44c0f5b601258a94e
- title :
- CNRM-CM5 model output prepared for CMIP5 pre-industrial control
- parent_experiment :
- N/A
- modeling_realm :
- ocean
- realization :
- 1
- cmor_version :
- 2.7.1