CCSM4 model output prepared for CMIP5 historical

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_historical_r1i1p1.yaml")
ds=cat.netcdf.read()

Metadata

title	CCSM4 model output prepared for CMIP5 historical
location	/shared/cmip5/data/historical/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_historical_r1i1p1.yaml
last updated	2019-06-07

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:                historical
    source:                       CCSM4
    model_id:                     CCSM4
    forcing:                      Sl GHG Vl SS Ds SD BC MD OC Oz AA LU
    parent_experiment_id:         piControl
    parent_experiment_rip:        r1i1p1
    branch_time:                  937.0
    contact:                      cesm_data@ucar.edu
    references:                   Gent P. R., et.al. 2011: The Community Clim...
    initialization_method:        1
    physics_version:              1
    tracking_id:                  e8f29806-e081-472a-97c0-15bf8d4cf5da
    acknowledgements:             The CESM project is supported by the Nation...
    cesm_casename:                b40.20th.track1.1deg.008
    cesm_repotag:                 ccsm4_0_beta43
    cesm_compset:                 B20TRCN
    resolution:                   f09_g16 (0.9x1.25_gx1v6)
    forcing_note:                 Additional information on the external forc...
    processed_by:                 strandwg on silver.cgd.ucar.edu at 20120205...
    processing_code_information:  Last Changed Rev: 526 Last Changed Date: 20...
    product:                      output
    experiment:                   historical
    frequency:                    mon
    creation_date:                2012-02-06T00:12:02Z
    history:                      2012-02-06T00:12:02Z CMOR rewrote data to c...
    Conventions:                  CF-1.4
    project_id:                   CMIP5
    table_id:                     Table Omon (12 January 2012) 55314d66bb61ec...
    title:                        CCSM4 model output prepared for CMIP5 histo...
    parent_experiment:            pre-industrial control
    modeling_realm:               ocean
    realization:                  1
    cmor_version:                 2.7.1

xarray.Dataset

Dimensions:
- bnds: 2
- i: 320
- j: 384
- lev: 60
- time: 1872
- vertices: 4

Coordinates: (6)

time
(time)
float64
6.753e+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)

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	75 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	75 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	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)

float64

dask.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)

float32

dask.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)

float32

dask.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)

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 :: 2012-02-06T00:12:02Z altered by CMOR: Converted units from 'degC' to 'K'. 2012-02-06T00:12:02Z 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_historical_r0i0p0.nc areacello: areacello_fx_CCSM4_historical_r0i0p0.nc volcello: volcello_fx_CCSM4_historical_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

Attributes: (35)
institution :
NCAR (National Center for Atmospheric Research) Boulder, CO, USA
institute_id :
NCAR
experiment_id :
historical
source :
CCSM4
model_id :
CCSM4
forcing :
Sl GHG Vl SS Ds SD BC MD OC Oz AA LU
parent_experiment_id :
piControl
parent_experiment_rip :
r1i1p1
branch_time :
937.0
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 :
e8f29806-e081-472a-97c0-15bf8d4cf5da
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 :
b40.20th.track1.1deg.008
cesm_repotag :
ccsm4_0_beta43
cesm_compset :
B20TRCN
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 20120205 -171202.177
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 :
historical
frequency :
mon
creation_date :
2012-02-06T00:12:02Z
history :
2012-02-06T00:12:02Z 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) 55314d66bb61ec8ded75f3d277593161
title :
CCSM4 model output prepared for CMIP5 historical
parent_experiment :
pre-industrial control
modeling_realm :
ocean
realization :
1
cmor_version :
2.7.1