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/thetao_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/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_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>
    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:                piControl
    source:                       CCSM4
    model_id:                     CCSM4
    forcing:                      Sl GHG Vl SS Ds SA BC MD OC Oz AA
    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:                  40090eca-a6c2-432c-94ee-e58bf72efe5a
    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 copper.cgd.ucar.edu at 20111129...
    processing_code_information:  Last Changed Rev: 472 Last Changed Date: 20...
    product:                      output
    experiment:                   pre-industrial control
    frequency:                    mon
    creation_date:                2011-11-29T21:51:13Z
    history:                      2011-11-29T21:51:13Z CMOR rewrote data to c...
    Conventions:                  CF-1.4
    project_id:                   CMIP5
    table_id:                     Table Omon (26 July 2011) 25bb94a0408beca44...
    title:                        CCSM4 model output prepared for CMIP5 pre-i...
    parent_experiment:            N/A
    modeling_realm:               ocean
    realization:                  1
    cmor_version:                 2.7.1

xarray.Dataset

Dimensions:
- bnds: 2
- i: 320
- j: 384
- lev: 60
- time: 6012
- vertices: 4

Coordinates: (6)

time
(time)
float64
2.92e+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)

float64

5.0 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)
int32
1 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)
int32
1 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)

float32

dask.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)

float32

dask.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

Data variables: (5)

time_bnds

(time, bnds)

float64

dask.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)

float64

dask.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)

float32

dask.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)

float32

dask.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

thetao

(time, lev, j, i)

float32

dask.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 :: 2011-11-29T21:51:13Z altered by CMOR: Converted units from 'degC' to 'K'. 2011-11-29T21:51:13Z 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_piControl_r0i0p0.nc areacello: areacello_fx_CCSM4_piControl_r0i0p0.nc volcello: volcello_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

Attributes: (35)
institution :
NCAR (National Center for Atmospheric Research) Boulder, CO, USA
institute_id :
NCAR
experiment_id :
piControl
source :
CCSM4
model_id :
CCSM4
forcing :
Sl GHG Vl SS Ds SA BC MD OC Oz AA
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 :
40090eca-a6c2-432c-94ee-e58bf72efe5a
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 copper.cgd.ucar.edu at 20111129 -145113.542
processing_code_information :
Last Changed Rev: 472 Last Changed Date: 2011-11-29 14:40:22 -0700 (Tue, 29 Nov 2011) Repository UUID: d2181dbe-5796-6825-dc7f-cbd98591f93d
product :
output
experiment :
pre-industrial control
frequency :
mon
creation_date :
2011-11-29T21:51:13Z
history :
2011-11-29T21:51:13Z 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 :
CCSM4 model output prepared for CMIP5 pre-industrial control
parent_experiment :
N/A
modeling_realm :
ocean
realization :
1
cmor_version :
2.7.1