CCSM4 model output prepared for CMIP5 1 percent per year CO2
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_CCSM4_1pctCO2_r1i1p1.yaml")
ds=cat.netcdf.read()
Metadata
title | CCSM4 model output prepared for CMIP5 1 percent per year CO2 |
location | /shared/cmip5/data/1pctCO2/ocean/mon/Omon/thetao/NCAR.CCSM4/r1i1p1 |
tags | gridded,global,model,monthly |
catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/thetao_Omon_CCSM4_1pctCO2_r1i1p1.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 6.753e+05 6.753e+05 ... 7.321e+05 7.322e+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> thetao (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: 1pctCO2 source: CCSM4 model_id: CCSM4 forcing: GHG (CO2 only) 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: a1127f70-dd39-4d34-91eb-ed1812f27bab acknowledgements: The CESM project is supported by the Nation... cesm_casename: b40.1850_ramp.track1.1deg.001 cesm_repotag: ccsm4_0_beta31 cesm_compset: B1850TR1CNRM resolution: f09_g16 (0.9x1.25_gx1v6) forcing_note: Additional information on the external forc... processed_by: strandwg on mirage4 at 20120527 -182201.270 processing_code_information: Last Changed Rev: 800 Last Changed Date: 20... product: output experiment: 1 percent per year CO2 frequency: mon creation_date: 2012-05-28T00:22:05Z history: 2012-05-28T00:22:05Z 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 1 per... parent_experiment: pre-industrial control modeling_realm: ocean realization: 1 cmor_version: 2.8.1
xarray.Dataset
- bnds: 2
- i: 320
- j: 384
- lev: 60
- time: 1872
- vertices: 4
- time(time)float646.753e+05 6.753e+05 ... 7.322e+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, ..., 732113.5, 732144. , 732174.5])
- 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 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=(120, 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=(120, 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=(120, 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 - thetao(time, lev, j, i)float32dask.array<chunksize=(120, 60, 384, 320), meta=np.ndarray>
- standard_name :
- sea_water_potential_temperature
- long_name :
- Sea Water Potential Temperature
- units :
- K
- original_name :
- TEMP
- comment :
- TEMP no change, units from C to K
- original_units :
- degC
- history :
- 2012-05-28T00:22:01Z altered by CMOR: Converted units from 'degC' to 'K'. 2012-05-28T00:22:01Z altered by CMOR: replaced missing value flag (9.96921e+36) 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_1pctCO2_r0i0p0.nc areacello: areacello_fx_CCSM4_1pctCO2_r0i0p0.nc volcello: volcello_fx_CCSM4_1pctCO2_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 :
- 1pctCO2
- source :
- CCSM4
- model_id :
- CCSM4
- forcing :
- GHG (CO2 only)
- 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 :
- a1127f70-dd39-4d34-91eb-ed1812f27bab
- 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_ramp.track1.1deg.001
- cesm_repotag :
- ccsm4_0_beta31
- cesm_compset :
- B1850TR1CNRM
- 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 20120527 -182201.270
- processing_code_information :
- Last Changed Rev: 800 Last Changed Date: 2012-05-27 01:04:34 -0600 (Sun, 27 May 2012) Repository UUID: d2181dbe-5796-6825-dc7f-cbd98591f93d
- product :
- output
- experiment :
- 1 percent per year CO2
- frequency :
- mon
- creation_date :
- 2012-05-28T00:22:05Z
- history :
- 2012-05-28T00:22:05Z 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 1 percent per year CO2
- parent_experiment :
- pre-industrial control
- modeling_realm :
- ocean
- realization :
- 1
- cmor_version :
- 2.8.1