MRI-CGCM3 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/clw_Amon_MRI-CGCM3_abrupt4xCO2_r1i1p1.yaml")
ds=cat.netcdf.read()

Metadata

title	MRI-CGCM3 model output prepared for CMIP5 abrupt 4XCO2
location	/shared/cmip5/data/abrupt4xCO2/atmos/mon/Amon/clw/MRI.MRI-CGCM3/r1i1p1
tags	gridded,global,model,monthly
catalog_dir	https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/clw_Amon_MRI-CGCM3_abrupt4xCO2_r1i1p1.yaml
last updated	2013-06-14

Dataset Contents

<xarray.Dataset>
Dimensions:    (bnds: 2, lat: 160, lev: 35, lon: 320, time: 1800)
Coordinates:
  * time       (time) float64 15.5 45.0 74.5 ... 5.471e+04 5.474e+04 5.477e+04
  * lev        (lev) float64 0.995 0.9825 0.965 ... 0.02447 0.01782 0.01269
  * lat        (lat) float64 -89.14 -88.03 -86.91 -85.79 ... 86.91 88.03 89.14
  * lon        (lon) float64 0.0 1.125 2.25 3.375 ... 355.5 356.6 357.8 358.9
Dimensions without coordinates: bnds
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, 35, 2), meta=np.ndarray>
    p0         (time) float32 101325.0 101325.0 101325.0 ... 101325.0 101325.0
    a          (time, lev) float64 dask.array<chunksize=(120, 35), meta=np.ndarray>
    b          (time, lev) float64 dask.array<chunksize=(120, 35), meta=np.ndarray>
    ps         (time, lat, lon) float32 dask.array<chunksize=(120, 160, 320), meta=np.ndarray>
    a_bnds     (time, lev, bnds) float64 dask.array<chunksize=(120, 35, 2), meta=np.ndarray>
    b_bnds     (time, lev, bnds) float64 dask.array<chunksize=(120, 35, 2), meta=np.ndarray>
    lat_bnds   (time, lat, bnds) float64 dask.array<chunksize=(120, 160, 2), meta=np.ndarray>
    lon_bnds   (time, lon, bnds) float64 dask.array<chunksize=(120, 320, 2), meta=np.ndarray>
    clw        (time, lev, lat, lon) float32 dask.array<chunksize=(120, 35, 160, 320), meta=np.ndarray>
Attributes:
    institution:            MRI (Meteorological Research Institute, Tsukuba, ...
    institute_id:           MRI
    experiment_id:          abrupt4xCO2
    source:                 MRI-CGCM3 2011 atmosphere: GSMUV (gsmuv-101124, T...
    model_id:               MRI-CGCM3
    forcing:                GHG (CO2 only)
    parent_experiment_id:   piControl
    parent_experiment_rip:  r1i1p1
    branch_time:            14610.0
    contact:                Seiji Yukimoto (yukimoto@mri-jma.go.jp)
    history:                Output from /sharex2/cmip5/abrupt4xCO2/run-C_abru...
    references:             Model described by Yukimoto et al. (Technical Rep...
    initialization_method:  1
    physics_version:        1
    tracking_id:            fbf78dac-f59c-4a2d-94a4-8119665ec129
    product:                output
    experiment:             abrupt 4XCO2
    frequency:              mon
    creation_date:          2011-06-07T22:30:23Z
    Conventions:            CF-1.4
    project_id:             CMIP5
    table_id:               Table Amon (27 April 2011) a5a1c518f52ae340313ba0...
    title:                  MRI-CGCM3 model output prepared for CMIP5 abrupt ...
    parent_experiment:      pre-industrial control
    modeling_realm:         atmos
    realization:            1
    cmor_version:           2.6.0

xarray.Dataset

Dimensions:
- bnds: 2
- lat: 160
- lev: 35
- lon: 320
- time: 1800

Coordinates: (4)

time
(time)
float64
15.5 45.0 ... 5.474e+04 5.477e+04
bounds :
time_bnds
units :
days since 1851-01-01
calendar :
standard
axis :
T
long_name :
time
standard_name :
time
```
array([1.55000e+01, 4.50000e+01, 7.45000e+01, ..., 5.47105e+04, 5.47410e+04,
       5.47715e+04])
```

lev

(lev)

float64

0.995 0.9825 ... 0.01782 0.01269

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([0.994996, 0.98249 , 0.964983, 0.942465, 0.914922, 0.882353, 0.845271,
       0.804677, 0.761574, 0.716962, 0.671845, 0.626721, 0.582097, 0.538472,
       0.495847, 0.454224, 0.414116, 0.37602 , 0.339429, 0.303853, 0.269806,
       0.237784, 0.20779 , 0.179825, 0.15389 , 0.129985, 0.108109, 0.088385,
       0.070994, 0.056   , 0.043351, 0.032904, 0.024469, 0.017815, 0.01269 ])

lat

(lat)

float64

-89.14 -88.03 ... 88.03 89.14

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

array([-89.14152, -88.02943, -86.91077, -85.79063, -84.66992, -83.54895,
       -82.42782, -81.30659, -80.18531, -79.06398, -77.94262, -76.82124,
       -75.69984, -74.57843, -73.45701, -72.33558, -71.21414, -70.09269,
       -68.97124, -67.84978, -66.72833, -65.60686, -64.4854 , -63.36393,
       -62.24246, -61.12099, -59.99952, -58.87804, -57.75657, -56.63509,
       -55.51361, -54.39214, -53.27066, -52.14917, -51.02769, -49.90621,
       -48.78473, -47.66325, -46.54176, -45.42028, -44.29879, -43.17731,
       -42.05582, -40.93434, -39.81285, -38.69137, -37.56988, -36.44839,
       -35.32691, -34.20542, -33.08393, -31.96244, -30.84096, -29.71947,
       -28.59798, -27.47649, -26.355  , -25.23351, -24.11203, -22.99054,
       -21.86905, -20.74756, -19.62607, -18.50458, -17.38309, -16.2616 ,
       -15.14011, -14.01862, -12.89713, -11.77564, -10.65415,  -9.53266,
        -8.41117,  -7.28968,  -6.16819,  -5.0467 ,  -3.92521,  -2.80372,
        -1.68223,  -0.56074,   0.56074,   1.68223,   2.80372,   3.92521,
         5.0467 ,   6.16819,   7.28968,   8.41117,   9.53266,  10.65415,
        11.77564,  12.89713,  14.01862,  15.14011,  16.2616 ,  17.38309,
        18.50458,  19.62607,  20.74756,  21.86905,  22.99054,  24.11203,
        25.23351,  26.355  ,  27.47649,  28.59798,  29.71947,  30.84096,
        31.96244,  33.08393,  34.20542,  35.32691,  36.44839,  37.56988,
        38.69137,  39.81285,  40.93434,  42.05582,  43.17731,  44.29879,
        45.42028,  46.54176,  47.66325,  48.78473,  49.90621,  51.02769,
        52.14917,  53.27066,  54.39214,  55.51361,  56.63509,  57.75657,
        58.87804,  59.99952,  61.12099,  62.24246,  63.36393,  64.4854 ,
        65.60686,  66.72833,  67.84978,  68.97124,  70.09269,  71.21414,
        72.33558,  73.45701,  74.57843,  75.69984,  76.82124,  77.94262,
        79.06398,  80.18531,  81.30659,  82.42782,  83.54895,  84.66992,
        85.79063,  86.91077,  88.02943,  89.14152])

lon
(lon)
float64
0.0 1.125 2.25 ... 357.8 358.9
bounds :
lon_bnds
units :
degrees_east
axis :
X
long_name :
longitude
standard_name :
longitude
```
array([  0.   ,   1.125,   2.25 , ..., 356.625, 357.75 , 358.875])
```

Data variables: (11)

time_bnds

(time, bnds)

float64

dask.array<chunksize=(120, 2), meta=np.ndarray>

	Array	Chunk
Bytes	28.80 kB	1.92 kB
Shape	(1800, 2)	(120, 2)
Count	45 Tasks	15 Chunks
Type	float64	numpy.ndarray

lev_bnds

(time, lev, bnds)

float64

dask.array<chunksize=(120, 35, 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	1.01 MB	67.20 kB
Shape	(1800, 35, 2)	(120, 35, 2)
Count	60 Tasks	15 Chunks
Type	float64	numpy.ndarray

p0
(time)
float32
101325.0 101325.0 ... 101325.0
long_name :
vertical coordinate formula term: reference pressure
units :
Pa
```
array([101325., 101325., 101325., ..., 101325., 101325., 101325.],
      dtype=float32)
```

(time, lev)

float64

dask.array<chunksize=(120, 35), meta=np.ndarray>

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

	Array	Chunk
Bytes	504.00 kB	33.60 kB
Shape	(1800, 35)	(120, 35)
Count	60 Tasks	15 Chunks
Type	float64	numpy.ndarray

(time, lev)

float64

dask.array<chunksize=(120, 35), meta=np.ndarray>

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

	Array	Chunk
Bytes	504.00 kB	33.60 kB
Shape	(1800, 35)	(120, 35)
Count	60 Tasks	15 Chunks
Type	float64	numpy.ndarray

(time, lat, lon)

float32

dask.array<chunksize=(120, 160, 320), 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	368.64 MB	24.58 MB
Shape	(1800, 160, 320)	(120, 160, 320)
Count	45 Tasks	15 Chunks
Type	float32	numpy.ndarray

a_bnds

(time, lev, bnds)

float64

dask.array<chunksize=(120, 35, 2), meta=np.ndarray>

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

	Array	Chunk
Bytes	1.01 MB	67.20 kB
Shape	(1800, 35, 2)	(120, 35, 2)
Count	60 Tasks	15 Chunks
Type	float64	numpy.ndarray

b_bnds

(time, lev, bnds)

float64

dask.array<chunksize=(120, 35, 2), meta=np.ndarray>

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

	Array	Chunk
Bytes	1.01 MB	67.20 kB
Shape	(1800, 35, 2)	(120, 35, 2)
Count	60 Tasks	15 Chunks
Type	float64	numpy.ndarray

lat_bnds

(time, lat, bnds)

float64

dask.array<chunksize=(120, 160, 2), meta=np.ndarray>

	Array	Chunk
Bytes	4.61 MB	307.20 kB
Shape	(1800, 160, 2)	(120, 160, 2)
Count	60 Tasks	15 Chunks
Type	float64	numpy.ndarray

lon_bnds

(time, lon, bnds)

float64

dask.array<chunksize=(120, 320, 2), meta=np.ndarray>

	Array	Chunk
Bytes	9.22 MB	614.40 kB
Shape	(1800, 320, 2)	(120, 320, 2)
Count	60 Tasks	15 Chunks
Type	float64	numpy.ndarray

clw

(time, lev, lat, lon)

float32

dask.array<chunksize=(120, 35, 160, 320), meta=np.ndarray>

standard_name :: mass_fraction_of_cloud_liquid_water_in_air
long_name :: Mass Fraction of Cloud Liquid Water
comment :: Includes both large-scale and convective cloud. Calculate as the mass of cloud liquid water in the grid cell divided by the mass of air (including the water in all phases) in the grid cells. Precipitating hydrometeors are included ONLY if the precipitating hydrometeors affect the calculation of radiative transfer in model.
units :: 1
original_name :: CWCWAT
cell_methods :: time: mean (interval: 30 minutes)
cell_measures :: area: areacella
history :: 2011-06-07T22:30:22Z altered by CMOR: replaced missing value flag (-9.99e+33) with standard missing value (1e+20).
associated_files :: baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MRI-CGCM3_abrupt4xCO2_r0i0p0.nc areacella: areacella_fx_MRI-CGCM3_abrupt4xCO2_r0i0p0.nc

	Array	Chunk
Bytes	12.90 GB	860.16 MB
Shape	(1800, 35, 160, 320)	(120, 35, 160, 320)
Count	45 Tasks	15 Chunks
Type	float32	numpy.ndarray

Attributes: (27)
institution :
MRI (Meteorological Research Institute, Tsukuba, Japan)
institute_id :
MRI
experiment_id :
abrupt4xCO2
source :
MRI-CGCM3 2011 atmosphere: GSMUV (gsmuv-101124, TL159L48); ocean: MRI.COM3 (MRICOM-3_0-20101116, 1x0.5L51); sea ice: MRI.COM3; land: HAL (HAL_cmip5_v0.31_01); aerosol: MASINGAR-mk2 (masingar_mk2-20101111, TL95L48)
model_id :
MRI-CGCM3
forcing :
GHG (CO2 only)
parent_experiment_id :
piControl
parent_experiment_rip :
r1i1p1
branch_time :
14610.0
contact :
Seiji Yukimoto (yukimoto@mri-jma.go.jp)
history :
Output from /sharex2/cmip5/abrupt4xCO2/run-C_abrupt4xCO2_01/grads/atm_eta_avr_mon.ctl 2011-06-07T22:30:23Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
references :
Model described by Yukimoto et al. (Technical Report of the Meteorological Research Institute, 2011, 64, 83pp.)
initialization_method :
1
physics_version :
1
tracking_id :
fbf78dac-f59c-4a2d-94a4-8119665ec129
product :
output
experiment :
abrupt 4XCO2
frequency :
mon
creation_date :
2011-06-07T22:30:23Z
Conventions :
CF-1.4
project_id :
CMIP5
table_id :
Table Amon (27 April 2011) a5a1c518f52ae340313ba0aada03f862
title :
MRI-CGCM3 model output prepared for CMIP5 abrupt 4XCO2
parent_experiment :
pre-industrial control
modeling_realm :
atmos
realization :
1
cmor_version :
2.6.0