CMCC-CM 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/clw_Amon_CMCC-CM_rcp85_r1i1p1.yaml")
ds=cat.netcdf.read()

Metadata

title	CMCC-CM model output prepared for CMIP5 RCP8.5
location	/shared/cmip5/data/rcp85/atmos/mon/Amon/clw/CMCC.CMCC-CM/r1i1p1
tags	gridded,global,model,monthly
catalog_dir	https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/clw_Amon_CMCC-CM_rcp85_r1i1p1.yaml
last updated	2013-06-14

Dataset Contents

<xarray.Dataset>
Dimensions:    (bnds: 2, lat: 240, lev: 31, lon: 480, time: 1140)
Coordinates:
  * time       (time) float64 15.5 45.0 74.5 ... 3.576e+03 3.606e+03 3.636e+03
  * lev        (lev) float64 0.9961 0.9826 0.959 0.9277 ... 0.07 0.05 0.03 0.01
  * lat        (lat) float64 -89.43 -88.68 -87.94 -87.19 ... 87.94 88.68 89.43
  * lon        (lon) float64 0.0 0.75 1.5 2.25 3.0 ... 357.0 357.8 358.5 359.2
Dimensions without coordinates: bnds
Data variables:
    time_bnds  (time, bnds) float64 dask.array<chunksize=(60, 2), meta=np.ndarray>
    lev_bnds   (time, lev, bnds) float64 dask.array<chunksize=(60, 31, 2), meta=np.ndarray>
    p0         (time) float32 100000.0 100000.0 100000.0 ... 100000.0 100000.0
    a          (time, lev) float64 dask.array<chunksize=(60, 31), meta=np.ndarray>
    b          (time, lev) float64 dask.array<chunksize=(60, 31), meta=np.ndarray>
    ps         (time, lat, lon) float32 dask.array<chunksize=(60, 240, 480), meta=np.ndarray>
    a_bnds     (time, lev, bnds) float64 dask.array<chunksize=(60, 31, 2), meta=np.ndarray>
    b_bnds     (time, lev, bnds) float64 dask.array<chunksize=(60, 31, 2), meta=np.ndarray>
    lat_bnds   (time, lat, bnds) float64 dask.array<chunksize=(60, 240, 2), meta=np.ndarray>
    lon_bnds   (time, lon, bnds) float64 dask.array<chunksize=(60, 480, 2), meta=np.ndarray>
    clw        (time, lev, lat, lon) float32 dask.array<chunksize=(60, 31, 240, 480), meta=np.ndarray>
Attributes:
    institution:            CMCC - Centro Euro-Mediterraneo per i Cambiamenti
    institute_id:           CMCC
    experiment_id:          rcp85
    source:                 CMCC-CM
    model_id:               CMCC-CM
    forcing:                Nat,GHG,SA,TO,Sl
    parent_experiment_id:   historical
    parent_experiment_rip:  N/A
    branch_time:            56978.0
    contact:                Silvio Gualdi (gualdi@bo.ingv.it)
    history:                Model output postprocessed with CDO 2012-02-15T12...
    comment:                RCP8.5 simulation starting at the end of the hist...
    references:             model described in the documentation at http://ww...
    initialization_method:  1
    physics_version:        1
    tracking_id:            bbe59caf-311d-4008-b40f-5d0c169da36b
    product:                output
    experiment:             RCP8.5
    frequency:              mon
    creation_date:          2012-02-15T12:36:27Z
    Conventions:            CF-1.4
    project_id:             CMIP5
    table_id:               Table Amon (27 April 2011) a5a1c518f52ae340313ba0...
    title:                  CMCC-CM model output prepared for CMIP5 RCP8.5
    parent_experiment:      historical
    modeling_realm:         atmos
    realization:            1
    cmor_version:           2.7.1

xarray.Dataset

Dimensions:
- bnds: 2
- lat: 240
- lev: 31
- lon: 480
- time: 1140
Coordinates: (4)
- time
  (time)
  float64
  15.5 45.0 ... 3.606e+03 3.636e+03
  bounds :
  time_bnds
  calendar :
  standard
  axis :
  T
  long_name :
  time
  standard_name :
  time
```
array([  15.5,   45. ,   74.5, ..., 3575.5, 3606. , 3636.5])
```
- lev
  (lev)
  float64
  0.9961 0.9826 0.959 ... 0.03 0.01
  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([0.996141, 0.982633, 0.95896 , 0.927683, 0.890885, 0.850232, 0.80704 ,
       0.762332, 0.716891, 0.671308, 0.626022, 0.58136 , 0.537568, 0.494837,
       0.453323, 0.413166, 0.3745  , 0.337457, 0.302169, 0.268762, 0.237349,
       0.20801 , 0.180775, 0.155595, 0.132317, 0.110639, 0.090076, 0.07    ,
       0.05    , 0.03    , 0.01    ])
```
- lat
  (lat)
  float64
  -89.43 -88.68 ... 88.68 89.43
  bounds :
  lat_bnds
  units :
  degrees_north
  axis :
  Y
  long_name :
  latitude
  standard_name :
  latitude
```
array([-89.427084, -88.684919, -87.938371, ...,  87.938371,  88.684919,
        89.427084])
```
- lon
  (lon)
  float64
  0.0 0.75 1.5 ... 357.8 358.5 359.2
  bounds :
  lon_bnds
  units :
  degrees_east
  axis :
  X
  long_name :
  longitude
  standard_name :
  longitude
```
array([  0.  ,   0.75,   1.5 , ..., 357.75, 358.5 , 359.25])
```

Data variables: (11)

time_bnds

(time, bnds)

float64

dask.array<chunksize=(60, 2), meta=np.ndarray>

	Array	Chunk
Bytes	18.24 kB	1.92 kB
Shape	(1140, 2)	(120, 2)
Count	30 Tasks	10 Chunks
Type	float64	numpy.ndarray

lev_bnds

(time, lev, bnds)

float64

dask.array<chunksize=(60, 31, 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	565.44 kB	59.52 kB
Shape	(1140, 31, 2)	(120, 31, 2)
Count	40 Tasks	10 Chunks
Type	float64	numpy.ndarray

p0
(time)
float32
100000.0 100000.0 ... 100000.0
long_name :
vertical coordinate formula term: reference pressure
units :
Pa
```
array([100000., 100000., 100000., ..., 100000., 100000., 100000.],
      dtype=float32)
```

(time, lev)

float64

dask.array<chunksize=(60, 31), meta=np.ndarray>

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

	Array	Chunk
Bytes	282.72 kB	29.76 kB
Shape	(1140, 31)	(120, 31)
Count	40 Tasks	10 Chunks
Type	float64	numpy.ndarray

(time, lev)

float64

dask.array<chunksize=(60, 31), meta=np.ndarray>

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

	Array	Chunk
Bytes	282.72 kB	29.76 kB
Shape	(1140, 31)	(120, 31)
Count	40 Tasks	10 Chunks
Type	float64	numpy.ndarray

(time, lat, lon)

float32

dask.array<chunksize=(60, 240, 480), 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	525.31 MB	55.30 MB
Shape	(1140, 240, 480)	(120, 240, 480)
Count	30 Tasks	10 Chunks
Type	float32	numpy.ndarray

a_bnds

(time, lev, bnds)

float64

dask.array<chunksize=(60, 31, 2), meta=np.ndarray>

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

	Array	Chunk
Bytes	565.44 kB	59.52 kB
Shape	(1140, 31, 2)	(120, 31, 2)
Count	40 Tasks	10 Chunks
Type	float64	numpy.ndarray

b_bnds

(time, lev, bnds)

float64

dask.array<chunksize=(60, 31, 2), meta=np.ndarray>

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

	Array	Chunk
Bytes	565.44 kB	59.52 kB
Shape	(1140, 31, 2)	(120, 31, 2)
Count	40 Tasks	10 Chunks
Type	float64	numpy.ndarray

lat_bnds

(time, lat, bnds)

float64

dask.array<chunksize=(60, 240, 2), meta=np.ndarray>

	Array	Chunk
Bytes	4.38 MB	460.80 kB
Shape	(1140, 240, 2)	(120, 240, 2)
Count	40 Tasks	10 Chunks
Type	float64	numpy.ndarray

lon_bnds

(time, lon, bnds)

float64

dask.array<chunksize=(60, 480, 2), meta=np.ndarray>

	Array	Chunk
Bytes	8.76 MB	921.60 kB
Shape	(1140, 480, 2)	(120, 480, 2)
Count	40 Tasks	10 Chunks
Type	float64	numpy.ndarray

clw

(time, lev, lat, lon)

float32

dask.array<chunksize=(60, 31, 240, 480), 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 :: xl
original_units :: kg/kg
history :: 2012-02-15T12:36:27Z altered by CMOR: Converted units from 'kg/kg' to '1'. 2012-02-15T12:36:27Z altered by CMOR: Inverted axis: lev. 2012-02-15T12:36:27Z altered by CMOR: Inverted axis: lat.
cell_methods :: time: mean (interval: 1 month)
cell_measures :: area: areacella
associated_files :: baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_CMCC-CM_rcp85_r0i0p0.nc areacella: areacella_fx_CMCC-CM_rcp85_r0i0p0.nc

	Array	Chunk
Bytes	16.28 GB	1.71 GB
Shape	(1140, 31, 240, 480)	(120, 31, 240, 480)
Count	30 Tasks	10 Chunks
Type	float32	numpy.ndarray

Attributes: (28)
institution :
CMCC - Centro Euro-Mediterraneo per i Cambiamenti
institute_id :
CMCC
experiment_id :
rcp85
source :
CMCC-CM
model_id :
CMCC-CM
forcing :
Nat,GHG,SA,TO,Sl
parent_experiment_id :
historical
parent_experiment_rip :
N/A
branch_time :
56978.0
contact :
Silvio Gualdi (gualdi@bo.ingv.it)
history :
Model output postprocessed with CDO 2012-02-15T12:36:27Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
comment :
RCP8.5 simulation starting at the end of the historical run
references :
model described in the documentation at http://www.cmcc.it/data-models/models
initialization_method :
1
physics_version :
1
tracking_id :
bbe59caf-311d-4008-b40f-5d0c169da36b
product :
output
experiment :
RCP8.5
frequency :
mon
creation_date :
2012-02-15T12:36:27Z
Conventions :
CF-1.4
project_id :
CMIP5
table_id :
Table Amon (27 April 2011) a5a1c518f52ae340313ba0aada03f862
title :
CMCC-CM model output prepared for CMIP5 RCP8.5
parent_experiment :
historical
modeling_realm :
atmos
realization :
1
cmor_version :
2.7.1