CESM1-BGC model output prepared for CMIP5 RCP8.5

Load in Python

from intake import open_catalog

cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/cli_Amon_CESM1-BGC_rcp85_r1i1p1.yaml")
ds=cat.netcdf.read()

Metadata

title	CESM1-BGC model output prepared for CMIP5 RCP8.5
location	/shared/cmip5/data/rcp85/atmos/mon/Amon/cli/NSF-DOE-NCAR.CESM1-BGC/r1i1p1
tags	gridded,global,model,monthly
catalog_dir	https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/cli_Amon_CESM1-BGC_rcp85_r1i1p1.yaml
last updated	2013-06-14

Dataset Contents

<xarray.Dataset>
Dimensions:    (bnds: 2, lat: 192, lev: 26, lon: 288, time: 1140)
Coordinates:
  * time       (time) float64 380.5 410.0 439.5 ... 3.499e+04 3.502e+04
  * lev        (lev) float64 0.9926 0.9706 0.9296 ... 0.01397 0.007389 0.003545
  * lat        (lat) float64 -90.0 -89.06 -88.12 -87.17 ... 88.12 89.06 90.0
  * lon        (lon) float64 0.0 1.25 2.5 3.75 5.0 ... 355.0 356.2 357.5 358.8
Dimensions without coordinates: bnds
Data variables:
    time_bnds  (time, bnds) float64 dask.array<chunksize=(528, 2), meta=np.ndarray>
    lev_bnds   (time, lev, bnds) float64 dask.array<chunksize=(528, 26, 2), meta=np.ndarray>
    p0         (time) float32 1000.0 1000.0 1000.0 ... 1000.0 1000.0 1000.0
    a          (time, lev) float64 dask.array<chunksize=(528, 26), meta=np.ndarray>
    b          (time, lev) float64 dask.array<chunksize=(528, 26), meta=np.ndarray>
    ps         (time, lat, lon) float32 dask.array<chunksize=(528, 192, 288), meta=np.ndarray>
    a_bnds     (time, lev, bnds) float64 dask.array<chunksize=(528, 26, 2), meta=np.ndarray>
    b_bnds     (time, lev, bnds) float64 dask.array<chunksize=(528, 26, 2), meta=np.ndarray>
    lat_bnds   (time, lat, bnds) float64 dask.array<chunksize=(528, 192, 2), meta=np.ndarray>
    lon_bnds   (time, lon, bnds) float64 dask.array<chunksize=(528, 288, 2), meta=np.ndarray>
    cli        (time, lev, lat, lon) float32 dask.array<chunksize=(528, 26, 192, 288), meta=np.ndarray>
Attributes:
    institution:                  NSF/DOE NCAR (National Center for Atmospher...
    institute_id:                 NSF-DOE-NCAR
    experiment_id:                rcp85
    source:                       CESM1-BGC
    model_id:                     CESM1-BGC
    forcing:                      Sl GHG SS Ds SA BC MD OC Oz AA
    parent_experiment_id:         piControl
    parent_experiment_rip:        r1i1p1
    branch_time:                  1.0
    contact:                      cesm_data@ucar.edu
    comment:                      CESM home page: http://www.cesm.ucar.edu
    references:                   TBD
 See also http://www.cesm.ucar.edu/pub...
    initialization_method:        1
    physics_version:              1
    tracking_id:                  b099dcaa-ebbe-4f8b-b1f1-42f9fb0bae5f
    acknowledgements:             The CESM project is supported by the Nation...
    cesm_casename:                b40.rcp8_5.1deg.bdrd.001
    cesm_repotag:                 unknown
    cesm_compset:                 unknown
    resolution:                   f09_g16 (0.9x1.25_gx1v6)
    forcing_note:                 Additional information on the external forc...
    processed_by:                 strandwg on silver.cgd.ucar.edu at 20120511...
    processing_code_information:  Last Changed Rev: 757 Last Changed Date: 20...
    product:                      output
    experiment:                   RCP8.5
    frequency:                    mon
    creation_date:                2012-05-11T16:57:00Z
    history:                      2012-05-11T16:57:00Z CMOR rewrote data to c...
    Conventions:                  CF-1.4
    project_id:                   CMIP5
    table_id:                     Table Amon (12 January 2012) 4996d487f7a657...
    title:                        CESM1-BGC model output prepared for CMIP5 R...
    parent_experiment:            pre-industrial control
    modeling_realm:               atmos
    realization:                  1
    cmor_version:                 2.8.1

xarray.Dataset

Dimensions:
- bnds: 2
- lat: 192
- lev: 26
- lon: 288
- time: 1140

Coordinates: (4)

time
(time)
float64
380.5 410.0 ... 3.499e+04 3.502e+04
bounds :
time_bnds
units :
days since 2005-01-01 00:00:00
calendar :
noleap
axis :
T
long_name :
time
standard_name :
time
```
array([  380.5,   410. ,   439.5, ..., 34963.5, 34994. , 35024.5])
```

lev

(lev)

float64

0.9926 0.9706 ... 0.007389 0.003545

bounds :: lev_bnds
units :: 1
axis :: Z
positive :: down
long_name :: hybrid sigma pressure coordinate
standard_name :: atmosphere_hybrid_sigma_pressure_coordinate
formula :: p = a*p0 + b*ps
formula_terms :: p0: p0 a: a b: b ps: ps

array([0.992556, 0.970555, 0.929649, 0.867161, 0.787702, 0.696796, 0.600524,
       0.510455, 0.433895, 0.368818, 0.313501, 0.266481, 0.226513, 0.19254 ,
       0.163662, 0.139115, 0.11825 , 0.100515, 0.085439, 0.070059, 0.053115,
       0.03723 , 0.023945, 0.013967, 0.007389, 0.003545])

lat

(lat)

float64

-90.0 -89.06 -88.12 ... 89.06 90.0

bounds :: lat_bnds
units :: degrees_north
axis :: Y
long_name :: latitude
standard_name :: latitude

array([-90.      , -89.057594, -88.115181, -87.172775, -86.23037 , -85.287956,
       -84.345551, -83.403145, -82.460732, -81.518326, -80.575912, -79.633507,
       -78.691101, -77.748688, -76.806282, -75.863876, -74.921463, -73.979057,
       -73.036652, -72.094238, -71.151833, -70.209427, -69.267014, -68.324608,
       -67.382202, -66.439789, -65.497383, -64.554977, -63.612564, -62.670158,
       -61.727749, -60.785339, -59.842934, -58.900524, -57.958115, -57.015705,
       -56.073299, -55.13089 , -54.18848 , -53.246075, -52.303665, -51.361256,
       -50.41885 , -49.47644 , -48.534031, -47.591621, -46.649216, -45.706806,
       -44.764397, -43.821991, -42.879581, -41.937172, -40.994766, -40.052357,
       -39.109947, -38.167538, -37.225132, -36.282722, -35.340313, -34.397907,
       -33.455498, -32.513088, -31.570681, -30.628273, -29.685863, -28.743456,
       -27.801046, -26.858639, -25.916231, -24.973822, -24.031414, -23.089005,
       -22.146597, -21.204189, -20.26178 , -19.319372, -18.376963, -17.434555,
       -16.492147, -15.549738, -14.607329, -13.664922, -12.722513, -11.780105,
       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
        11.780105,  12.722513,  13.664922,  14.607329,  15.549738,  16.492147,
        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204189,  22.146597,
        23.089005,  24.031414,  24.973822,  25.916231,  26.858639,  27.801046,
        28.743456,  29.685863,  30.628273,  31.570681,  32.513088,  33.455498,
        34.397907,  35.340313,  36.282722,  37.225132,  38.167538,  39.109947,
        40.052357,  40.994766,  41.937172,  42.879581,  43.821991,  44.764397,
        45.706806,  46.649216,  47.591621,  48.534031,  49.47644 ,  50.41885 ,
        51.361256,  52.303665,  53.246075,  54.18848 ,  55.13089 ,  56.073299,
        57.015705,  57.958115,  58.900524,  59.842934,  60.785339,  61.727749,
        62.670158,  63.612564,  64.554977,  65.497383,  66.439789,  67.382202,
        68.324608,  69.267014,  70.209427,  71.151833,  72.094238,  73.036652,
        73.979057,  74.921463,  75.863876,  76.806282,  77.748688,  78.691101,
        79.633507,  80.575912,  81.518326,  82.460732,  83.403145,  84.345551,
        85.287956,  86.23037 ,  87.172775,  88.115181,  89.057594,  90.      ])

lon
(lon)
float64
0.0 1.25 2.5 ... 356.2 357.5 358.8
bounds :
lon_bnds
units :
degrees_east
axis :
X
long_name :
longitude
standard_name :
longitude
```
array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])
```

Data variables: (11)

time_bnds

(time, bnds)

float64

dask.array<chunksize=(528, 2), meta=np.ndarray>

	Array	Chunk
Bytes	18.24 kB	9.79 kB
Shape	(1140, 2)	(612, 2)
Count	6 Tasks	2 Chunks
Type	float64	numpy.ndarray

lev_bnds

(time, lev, bnds)

float64

dask.array<chunksize=(528, 26, 2), meta=np.ndarray>

formula :: p = a*p0 + b*ps
standard_name :: atmosphere_hybrid_sigma_pressure_coordinate
units :: 1
formula_terms :: p0: p0 a: a_bnds b: b_bnds ps: ps

	Array	Chunk
Bytes	474.24 kB	254.59 kB
Shape	(1140, 26, 2)	(612, 26, 2)
Count	8 Tasks	2 Chunks
Type	float64	numpy.ndarray

p0
(time)
float32
1000.0 1000.0 ... 1000.0 1000.0
long_name :
vertical coordinate formula term: reference pressure
units :
Pa
```
array([1000., 1000., 1000., ..., 1000., 1000., 1000.], dtype=float32)
```

(time, lev)

float64

dask.array<chunksize=(528, 26), meta=np.ndarray>

long_name :: vertical coordinate formula term: a(k)

	Array	Chunk
Bytes	237.12 kB	127.30 kB
Shape	(1140, 26)	(612, 26)
Count	8 Tasks	2 Chunks
Type	float64	numpy.ndarray

(time, lev)

float64

dask.array<chunksize=(528, 26), meta=np.ndarray>

long_name :: vertical coordinate formula term: b(k)

	Array	Chunk
Bytes	237.12 kB	127.30 kB
Shape	(1140, 26)	(612, 26)
Count	8 Tasks	2 Chunks
Type	float64	numpy.ndarray

(time, lat, lon)

float32

dask.array<chunksize=(528, 192, 288), meta=np.ndarray>

standard_name :: surface_air_pressure
long_name :: Surface Air Pressure
comment :: not, in general, the same as mean sea-level pressure
units :: Pa
cell_methods :: time: mean
cell_measures :: area: areacella

	Array	Chunk
Bytes	252.15 MB	135.36 MB
Shape	(1140, 192, 288)	(612, 192, 288)
Count	6 Tasks	2 Chunks
Type	float32	numpy.ndarray

a_bnds

(time, lev, bnds)

float64

dask.array<chunksize=(528, 26, 2), meta=np.ndarray>

long_name :: vertical coordinate formula term: a(k+1/2)

	Array	Chunk
Bytes	474.24 kB	254.59 kB
Shape	(1140, 26, 2)	(612, 26, 2)
Count	8 Tasks	2 Chunks
Type	float64	numpy.ndarray

b_bnds

(time, lev, bnds)

float64

dask.array<chunksize=(528, 26, 2), meta=np.ndarray>

long_name :: vertical coordinate formula term: b(k+1/2)

	Array	Chunk
Bytes	474.24 kB	254.59 kB
Shape	(1140, 26, 2)	(612, 26, 2)
Count	8 Tasks	2 Chunks
Type	float64	numpy.ndarray

lat_bnds

(time, lat, bnds)

float64

dask.array<chunksize=(528, 192, 2), meta=np.ndarray>

	Array	Chunk
Bytes	3.50 MB	1.88 MB
Shape	(1140, 192, 2)	(612, 192, 2)
Count	8 Tasks	2 Chunks
Type	float64	numpy.ndarray

lon_bnds

(time, lon, bnds)

float64

dask.array<chunksize=(528, 288, 2), meta=np.ndarray>

	Array	Chunk
Bytes	5.25 MB	2.82 MB
Shape	(1140, 288, 2)	(612, 288, 2)
Count	8 Tasks	2 Chunks
Type	float64	numpy.ndarray

cli

(time, lev, lat, lon)

float32

dask.array<chunksize=(528, 26, 192, 288), meta=np.ndarray>

standard_name :: mass_fraction_of_cloud_ice_in_air
long_name :: Mass Fraction of Cloud Ice
comment :: CLDICE on model levels, no change, CMIP5_table_comment: Includes both large-scale and convective cloud. This is calculated as the mass of cloud ice in the grid cell divided by the mass of air (including the water in all phases) in the grid cell. It includes precipitating hydrometeors ONLY if the precipitating hydrometeors affect the calculation of radiative transfer in model.
units :: 1
original_name :: CLDICE,PS
original_units :: kg/kg
history :: 2012-05-11T16:56:48Z altered by CMOR: Converted units from 'kg/kg' to '1'. 2012-05-11T16:56:48Z altered by CMOR: replaced missing value flag (-1e+32) with standard missing value (1e+20). 2012-05-11T16:57:00Z altered by CMOR: Inverted axis: lev.
cell_methods :: time: mean (interval: 30 days)
cell_measures :: area: areacella
associated_files :: baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_CESM1-BGC_rcp85_r0i0p0.nc areacella: areacella_fx_CESM1-BGC_rcp85_r0i0p0.nc

	Array	Chunk
Bytes	6.56 GB	3.52 GB
Shape	(1140, 26, 192, 288)	(612, 26, 192, 288)
Count	6 Tasks	2 Chunks
Type	float32	numpy.ndarray

Attributes: (36)
institution :
NSF/DOE NCAR (National Center for Atmospheric Research) Boulder, CO, USA
institute_id :
NSF-DOE-NCAR
experiment_id :
rcp85
source :
CESM1-BGC
model_id :
CESM1-BGC
forcing :
Sl GHG SS Ds SA BC MD OC Oz AA
parent_experiment_id :
piControl
parent_experiment_rip :
r1i1p1
branch_time :
1.0
contact :
cesm_data@ucar.edu
comment :
CESM home page: http://www.cesm.ucar.edu
references :
TBD See also http://www.cesm.ucar.edu/publications
initialization_method :
1
physics_version :
1
tracking_id :
b099dcaa-ebbe-4f8b-b1f1-42f9fb0bae5f
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.rcp8_5.1deg.bdrd.001
cesm_repotag :
unknown
cesm_compset :
unknown
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 20120511 -105648.490
processing_code_information :
Last Changed Rev: 757 Last Changed Date: 2012-05-09 13:01:12 -0600 (Wed, 09 May 2012) Repository UUID: d2181dbe-5796-6825-dc7f-cbd98591f93d
product :
output
experiment :
RCP8.5
frequency :
mon
creation_date :
2012-05-11T16:57:00Z
history :
2012-05-11T16:57:00Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
Conventions :
CF-1.4
project_id :
CMIP5
table_id :
Table Amon (12 January 2012) 4996d487f7a65749098d9cc0dccb4f8d
title :
CESM1-BGC model output prepared for CMIP5 RCP8.5
parent_experiment :
pre-industrial control
modeling_realm :
atmos
realization :
1
cmor_version :
2.8.1