CCSM4 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/so_Omon_CCSM4_piControl_r2i1p1.yaml")
ds=cat.netcdf.read()
Metadata
title | CCSM4 model output prepared for CMIP5 pre-industrial control |
location | /shared/cmip5/data/piControl/ocean/mon/Omon/so/NCAR.CCSM4/r2i1p1 |
tags | gridded,global,model,monthly |
catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/so_Omon_CCSM4_piControl_r2i1p1.yaml |
last updated | 2013-06-14 |
Dataset Contents
<xarray.Dataset> Dimensions: (bnds: 2, i: 320, j: 384, lev: 60, time: 1872, vertices: 4) Coordinates: * time (time) float64 3.479e+05 3.479e+05 ... 4.047e+05 4.048e+05 * lev (lev) float64 5.0 15.0 25.0 ... 4.875e+03 5.125e+03 5.375e+03 * j (j) int32 1 2 3 4 5 6 7 8 ... 377 378 379 380 381 382 383 384 * i (i) int32 1 2 3 4 5 6 7 8 ... 313 314 315 316 317 318 319 320 lat (j, i) float32 dask.array<chunksize=(384, 320), meta=np.ndarray> lon (j, i) float32 dask.array<chunksize=(384, 320), meta=np.ndarray> Dimensions without coordinates: bnds, vertices Data variables: time_bnds (time, bnds) float64 dask.array<chunksize=(84, 2), meta=np.ndarray> lev_bnds (time, lev, bnds) float64 dask.array<chunksize=(84, 60, 2), meta=np.ndarray> lat_vertices (time, j, i, vertices) float32 dask.array<chunksize=(84, 384, 320, 4), meta=np.ndarray> lon_vertices (time, j, i, vertices) float32 dask.array<chunksize=(84, 384, 320, 4), meta=np.ndarray> so (time, lev, j, i) float32 dask.array<chunksize=(84, 60, 384, 320), meta=np.ndarray> Attributes: institution: NCAR (National Center for Atmospheric Resea... institute_id: NCAR experiment_id: piControl source: CCSM4 model_id: CCSM4 forcing: Sl GHG SS Ds SD BC MD OC Oz AA (all fixed a... parent_experiment_id: N/A parent_experiment_rip: N/A branch_time: 0.0 contact: cesm_data@ucar.edu comment: CESM home page: http://www.cesm.ucar.edu references: Gent P. R., et.al. 2011: The Community Clim... initialization_method: 1 physics_version: 1 tracking_id: 83fcfc6d-3148-47d3-b284-5404fcb5badf acknowledgements: The CESM project is supported by the Nation... cesm_casename: b40.1850.track1.1deg.006a cesm_repotag: ccsm4_0_beta53 cesm_compset: B1850CN resolution: f09_g16 (0.9x1.25_gx1v6) forcing_note: Additional information on the external forc... processed_by: strandwg on mirage3 at 20120614 -112128.004 processing_code_information: Last Changed Rev: 881 Last Changed Date: 20... product: output experiment: pre-industrial control frequency: mon creation_date: 2012-06-14T17:21:45Z history: 2012-06-14T17:21:45Z CMOR rewrote data to c... Conventions: CF-1.4 project_id: CMIP5 table_id: Table Omon (12 January 2012) 980e0aeb02de42... title: CCSM4 model output prepared for CMIP5 pre-i... parent_experiment: N/A modeling_realm: ocean realization: 2 cmor_version: 2.8.1
xarray.Dataset
- bnds: 2
- i: 320
- j: 384
- lev: 60
- time: 1872
- vertices: 4
- time(time)float643.479e+05 3.479e+05 ... 4.048e+05
- bounds :
- time_bnds
- units :
- days since 0000-01-01 00:00:00
- calendar :
- noleap
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([347861.020833, 347890. , 347919.5 , ..., 404708.5 , 404739. , 404769.5 ])
- lev(lev)float645.0 15.0 ... 5.125e+03 5.375e+03
- bounds :
- lev_bnds
- units :
- m
- axis :
- Z
- positive :
- down
- long_name :
- ocean depth coordinate
- standard_name :
- depth
array([5.000000e+00, 1.500000e+01, 2.500000e+01, 3.500000e+01, 4.500000e+01, 5.500000e+01, 6.500000e+01, 7.500000e+01, 8.500000e+01, 9.500000e+01, 1.050000e+02, 1.150000e+02, 1.250000e+02, 1.350000e+02, 1.450000e+02, 1.550000e+02, 1.650984e+02, 1.754790e+02, 1.862913e+02, 1.976603e+02, 2.097114e+02, 2.225783e+02, 2.364088e+02, 2.513702e+02, 2.676542e+02, 2.854837e+02, 3.051192e+02, 3.268680e+02, 3.510935e+02, 3.782276e+02, 4.087846e+02, 4.433777e+02, 4.827367e+02, 5.277280e+02, 5.793729e+02, 6.388626e+02, 7.075633e+02, 7.870025e+02, 8.788252e+02, 9.847059e+02, 1.106204e+03, 1.244567e+03, 1.400497e+03, 1.573946e+03, 1.764003e+03, 1.968944e+03, 2.186457e+03, 2.413972e+03, 2.649001e+03, 2.889385e+03, 3.133405e+03, 3.379793e+03, 3.627670e+03, 3.876452e+03, 4.125768e+03, 4.375392e+03, 4.625190e+03, 4.875083e+03, 5.125028e+03, 5.375000e+03])
- j(j)int321 2 3 4 5 6 ... 380 381 382 383 384
- units :
- 1
- long_name :
- cell index along second dimension
array([ 1, 2, 3, ..., 382, 383, 384], dtype=int32)
- i(i)int321 2 3 4 5 6 ... 316 317 318 319 320
- units :
- 1
- long_name :
- cell index along first dimension
array([ 1, 2, 3, ..., 318, 319, 320], dtype=int32)
- lat(j, i)float32dask.array<chunksize=(384, 320), meta=np.ndarray>
- standard_name :
- latitude
- long_name :
- latitude coordinate
- units :
- degrees_north
- bounds :
- lat_vertices
Array Chunk Bytes 491.52 kB 491.52 kB Shape (384, 320) (384, 320) Count 75 Tasks 1 Chunks Type float32 numpy.ndarray - lon(j, i)float32dask.array<chunksize=(384, 320), meta=np.ndarray>
- standard_name :
- longitude
- long_name :
- longitude coordinate
- units :
- degrees_east
- bounds :
- lon_vertices
Array Chunk Bytes 491.52 kB 491.52 kB Shape (384, 320) (384, 320) Count 75 Tasks 1 Chunks Type float32 numpy.ndarray
- time_bnds(time, bnds)float64dask.array<chunksize=(84, 2), meta=np.ndarray>
Array Chunk Bytes 29.95 kB 1.92 kB Shape (1872, 2) (120, 2) Count 48 Tasks 16 Chunks Type float64 numpy.ndarray - lev_bnds(time, lev, bnds)float64dask.array<chunksize=(84, 60, 2), meta=np.ndarray>
Array Chunk Bytes 1.80 MB 115.20 kB Shape (1872, 60, 2) (120, 60, 2) Count 64 Tasks 16 Chunks Type float64 numpy.ndarray - lat_vertices(time, j, i, vertices)float32dask.array<chunksize=(84, 384, 320, 4), meta=np.ndarray>
- units :
- degrees_north
Array Chunk Bytes 3.68 GB 235.93 MB Shape (1872, 384, 320, 4) (120, 384, 320, 4) Count 64 Tasks 16 Chunks Type float32 numpy.ndarray - lon_vertices(time, j, i, vertices)float32dask.array<chunksize=(84, 384, 320, 4), meta=np.ndarray>
- units :
- degrees_east
Array Chunk Bytes 3.68 GB 235.93 MB Shape (1872, 384, 320, 4) (120, 384, 320, 4) Count 64 Tasks 16 Chunks Type float32 numpy.ndarray - so(time, lev, j, i)float32dask.array<chunksize=(84, 60, 384, 320), meta=np.ndarray>
- standard_name :
- sea_water_salinity
- long_name :
- Sea Water Salinity
- units :
- 1
- original_name :
- SALT
- comment :
- SALT
- original_units :
- gram/kilogram
- history :
- 2012-06-14T17:21:29Z altered by CMOR: Converted units from 'gram/kilogram' to '1'. 2012-06-14T17:21:29Z altered by CMOR: replaced missing value flag (9.96921e+33) with standard missing value (1e+20).
- cell_methods :
- time: mean (interval: 30 days)
- cell_measures :
- area: areacello volume: volcello
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_ocean_fx_CCSM4_piControl_r0i0p0.nc areacello: areacello_fx_CCSM4_piControl_r0i0p0.nc volcello: volcello_fx_CCSM4_piControl_r0i0p0.nc
Array Chunk Bytes 55.21 GB 3.54 GB Shape (1872, 60, 384, 320) (120, 60, 384, 320) Count 48 Tasks 16 Chunks Type float32 numpy.ndarray
- institution :
- NCAR (National Center for Atmospheric Research) Boulder, CO, USA
- institute_id :
- NCAR
- experiment_id :
- piControl
- source :
- CCSM4
- model_id :
- CCSM4
- forcing :
- Sl GHG SS Ds SD BC MD OC Oz AA (all fixed at 1850 values)
- parent_experiment_id :
- N/A
- parent_experiment_rip :
- N/A
- branch_time :
- 0.0
- contact :
- cesm_data@ucar.edu
- comment :
- CESM home page: http://www.cesm.ucar.edu
- references :
- Gent P. R., et.al. 2011: The Community Climate System Model version 4. J. Climate, doi: 10.1175/2011JCLI4083.1
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- 83fcfc6d-3148-47d3-b284-5404fcb5badf
- acknowledgements :
- The CESM project is supported by the National Science Foundation and the Office of Science (BER) of the U.S. Department of Energy. NCAR is sponsored by the National Science Foundation. Computing resources were provided by the Climate Simulation Laboratory at the NCAR Computational and Information Systems Laboratory (CISL), sponsored by the National Science Foundation and other agencies.
- cesm_casename :
- b40.1850.track1.1deg.006a
- cesm_repotag :
- ccsm4_0_beta53
- cesm_compset :
- B1850CN
- resolution :
- f09_g16 (0.9x1.25_gx1v6)
- forcing_note :
- Additional information on the external forcings used in this experiment can be found at http://www.cesm.ucar.edu/CMIP5/forcing_information
- processed_by :
- strandwg on mirage3 at 20120614 -112128.004
- processing_code_information :
- Last Changed Rev: 881 Last Changed Date: 2012-06-13 21:57:41 -0600 (Wed, 13 Jun 2012) Repository UUID: d2181dbe-5796-6825-dc7f-cbd98591f93d
- product :
- output
- experiment :
- pre-industrial control
- frequency :
- mon
- creation_date :
- 2012-06-14T17:21:45Z
- history :
- 2012-06-14T17:21:45Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table Omon (12 January 2012) 980e0aeb02de4233251f100571014e41
- title :
- CCSM4 model output prepared for CMIP5 pre-industrial control
- parent_experiment :
- N/A
- modeling_realm :
- ocean
- realization :
- 2
- cmor_version :
- 2.8.1