CCSM4 model output prepared for CMIP5 abrupt 4XCO2
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_abrupt4xCO2_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | CCSM4 model output prepared for CMIP5 abrupt 4XCO2 |
| location | /shared/cmip5/data/abrupt4xCO2/ocean/mon/Omon/so/NCAR.CCSM4/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/so_Omon_CCSM4_abrupt4xCO2_r1i1p1.yaml |
| last updated | 2013-06-14 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, i: 320, j: 384, lev: 60, time: 1812, vertices: 4)
Coordinates:
* time (time) float64 6.753e+05 6.753e+05 ... 7.303e+05 7.303e+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>
so (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: abrupt4xCO2
source: CCSM4
model_id: CCSM4
forcing: GHG (CO2 only, instantaneously to 4X)
parent_experiment_id: piControl
parent_experiment_rip: r1i1p1
branch_time: 2.0
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: 6f9fd82b-e65a-4282-9baa-12af2f1c0c1f
acknowledgements: The CESM project is supported by the Nation...
cesm_casename: b40.abrupt4xco2.1deg.001
cesm_repotag: ccsm4_0_beta45
cesm_compset: B1850CN
resolution: f09_g16 (0.9x1.25_gx1v6)
forcing_note: Additional information on the external forc...
processed_by: strandwg on mirage4 at 20120603 -195556.885
processing_code_information: Last Changed Rev: 837 Last Changed Date: 20...
product: output
experiment: abrupt 4XCO2
frequency: mon
creation_date: 2012-06-04T01:56:01Z
history: 2012-06-04T01:56:01Z 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 abrup...
parent_experiment: pre-industrial control
modeling_realm: ocean
realization: 1
cmor_version: 2.8.1xarray.Dataset
- bnds: 2
- i: 320
- j: 384
- lev: 60
- time: 1812
- vertices: 4
- time(time)float646.753e+05 6.753e+05 ... 7.303e+05
- bounds :
- time_bnds
- units :
- days since 0000-01-01 00:00:00
- calendar :
- noleap
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([675265.5, 675295. , 675324.5, ..., 730288.5, 730319. , 730349.5])
- 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=(120, 2), meta=np.ndarray>
Array Chunk Bytes 28.99 kB 1.92 kB Shape (1812, 2) (120, 2) Count 48 Tasks 16 Chunks Type float64 numpy.ndarray - lev_bnds(time, lev, bnds)float64dask.array<chunksize=(120, 60, 2), meta=np.ndarray>
Array Chunk Bytes 1.74 MB 115.20 kB Shape (1812, 60, 2) (120, 60, 2) Count 64 Tasks 16 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 3.56 GB 235.93 MB Shape (1812, 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=(120, 384, 320, 4), meta=np.ndarray>
- units :
- degrees_east
Array Chunk Bytes 3.56 GB 235.93 MB Shape (1812, 384, 320, 4) (120, 384, 320, 4) Count 64 Tasks 16 Chunks Type float32 numpy.ndarray - so(time, lev, j, i)float32dask.array<chunksize=(120, 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 :
- 2012-06-04T01:55:56Z altered by CMOR: Converted units from 'gram/kilogram' to '1'. 2012-06-04T01:55:56Z 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_abrupt4xCO2_r0i0p0.nc areacello: areacello_fx_CCSM4_abrupt4xCO2_r0i0p0.nc volcello: volcello_fx_CCSM4_abrupt4xCO2_r0i0p0.nc
Array Chunk Bytes 53.44 GB 3.54 GB Shape (1812, 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 :
- abrupt4xCO2
- source :
- CCSM4
- model_id :
- CCSM4
- forcing :
- GHG (CO2 only, instantaneously to 4X)
- parent_experiment_id :
- piControl
- parent_experiment_rip :
- r1i1p1
- branch_time :
- 2.0
- 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 :
- 6f9fd82b-e65a-4282-9baa-12af2f1c0c1f
- 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.abrupt4xco2.1deg.001
- cesm_repotag :
- ccsm4_0_beta45
- 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 mirage4 at 20120603 -195556.885
- processing_code_information :
- Last Changed Rev: 837 Last Changed Date: 2012-06-03 10:12:06 -0600 (Sun, 03 Jun 2012) Repository UUID: d2181dbe-5796-6825-dc7f-cbd98591f93d
- product :
- output
- experiment :
- abrupt 4XCO2
- frequency :
- mon
- creation_date :
- 2012-06-04T01:56:01Z
- history :
- 2012-06-04T01:56:01Z 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 abrupt 4XCO2
- parent_experiment :
- pre-industrial control
- modeling_realm :
- ocean
- realization :
- 1
- cmor_version :
- 2.8.1