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/vo_Omon_CCSM4_piControl_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | CCSM4 model output prepared for CMIP5 pre-industrial control |
| location | /shared/cmip5/data/piControl/ocean/mon/Omon/vo/NCAR.CCSM4/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/vo_Omon_CCSM4_piControl_r1i1p1.yaml |
| last updated | 2013-06-14 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, i: 320, j: 384, lev: 60, time: 6012, vertices: 4)
Coordinates:
* time (time) float64 2.92e+05 2.92e+05 ... 4.748e+05 4.748e+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=(120, 2), meta=np.ndarray>
lev_bnds (time, lev, bnds) float64 dask.array<chunksize=(120, 60, 2), meta=np.ndarray>
lat_vertices (time, j, i, vertices) float32 dask.array<chunksize=(120, 384, 320, 4), meta=np.ndarray>
lon_vertices (time, j, i, vertices) float32 dask.array<chunksize=(120, 384, 320, 4), meta=np.ndarray>
vo (time, lev, j, i) float32 dask.array<chunksize=(120, 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
references: Gent P. R., et.al. 2011: The Community Clim...
initialization_method: 1
physics_version: 1
tracking_id: 21bee6c2-e7a2-43ef-b62e-1ecc747f7e68
acknowledgements: The CESM project is supported by the Nation...
cesm_casename: b40.1850.track1.1deg.006
cesm_repotag: ccsm4_0_beta23
cesm_compset: B1850TR1CN
resolution: f09_g16 (0.9x1.25_gx1v6)
forcing_note: Additional information on the external forc...
processed_by: strandwg on silver.cgd.ucar.edu at 20120206...
processing_code_information: Last Changed Rev: 526 Last Changed Date: 20...
product: output
experiment: pre-industrial control
frequency: mon
creation_date: 2012-02-06T15:14:31Z
history: 2012-02-06T15:14:31Z 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: 1
cmor_version: 2.7.1xarray.Dataset
- bnds: 2
- i: 320
- j: 384
- lev: 60
- time: 6012
- vertices: 4
- time(time)float642.92e+05 2.92e+05 ... 4.748e+05
- bounds :
- time_bnds
- units :
- days since 0000-01-01 00:00:00
- calendar :
- noleap
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([292015. , 292045. , 292074.5, ..., 474788.5, 474819. , 474849.5])
- 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 245 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 245 Tasks 1 Chunks Type float32 numpy.ndarray
- time_bnds(time, bnds)float64dask.array<chunksize=(120, 2), meta=np.ndarray>
Array Chunk Bytes 96.19 kB 2.11 kB Shape (6012, 2) (132, 2) Count 150 Tasks 50 Chunks Type float64 numpy.ndarray - lev_bnds(time, lev, bnds)float64dask.array<chunksize=(120, 60, 2), meta=np.ndarray>
Array Chunk Bytes 5.77 MB 126.72 kB Shape (6012, 60, 2) (132, 60, 2) Count 200 Tasks 50 Chunks Type float64 numpy.ndarray - lat_vertices(time, j, i, vertices)float32dask.array<chunksize=(120, 384, 320, 4), meta=np.ndarray>
- units :
- degrees_north
Array Chunk Bytes 11.82 GB 259.52 MB Shape (6012, 384, 320, 4) (132, 384, 320, 4) Count 200 Tasks 50 Chunks Type float32 numpy.ndarray - lon_vertices(time, j, i, vertices)float32dask.array<chunksize=(120, 384, 320, 4), meta=np.ndarray>
- units :
- degrees_east
Array Chunk Bytes 11.82 GB 259.52 MB Shape (6012, 384, 320, 4) (132, 384, 320, 4) Count 200 Tasks 50 Chunks Type float32 numpy.ndarray - vo(time, lev, j, i)float32dask.array<chunksize=(120, 60, 384, 320), meta=np.ndarray>
- standard_name :
- sea_water_y_velocity
- long_name :
- Sea Water Y Velocity
- units :
- m s-1
- original_name :
- VVEL
- comment :
- VVEL units from cm s-1 to m s-1
- original_units :
- centimeter/s
- history :
- 2012-02-06T15:14:05Z altered by CMOR: Converted units from 'centimeter/s' to 'm s-1'. 2012-02-06T15:14:05Z altered by CMOR: replaced missing value flag (9.96921e+36) with standard missing value (1e+20).
- cell_methods :
- time: mean (interval: 30 days)
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_ocean_fx_CCSM4_piControl_r0i0p0.nc
Array Chunk Bytes 177.30 GB 3.89 GB Shape (6012, 60, 384, 320) (132, 60, 384, 320) Count 150 Tasks 50 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
- 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 :
- 21bee6c2-e7a2-43ef-b62e-1ecc747f7e68
- 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.006
- cesm_repotag :
- ccsm4_0_beta23
- cesm_compset :
- B1850TR1CN
- 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 silver.cgd.ucar.edu at 20120206 -081404.961
- processing_code_information :
- Last Changed Rev: 526 Last Changed Date: 2012-02-05 16:49:28 -0700 (Sun, 05 Feb 2012) Repository UUID: d2181dbe-5796-6825-dc7f-cbd98591f93d
- product :
- output
- experiment :
- pre-industrial control
- frequency :
- mon
- creation_date :
- 2012-02-06T15:14:31Z
- history :
- 2012-02-06T15:14:31Z 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 :
- 1
- cmor_version :
- 2.7.1