CMCC-CESM 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/cl_Amon_CMCC-CESM_rcp85_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | CMCC-CESM model output prepared for CMIP5 RCP8.5 |
| location | /shared/cmip5/data/rcp85/atmos/mon/Amon/cl/CMCC.CMCC-CESM/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/cl_Amon_CMCC-CESM_rcp85_r1i1p1.yaml |
| last updated | 2013-06-14 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, lat: 48, lev: 39, lon: 96, time: 1152)
Coordinates:
* time (time) float64 15.5 45.5 75.5 ... 3.576e+03 3.606e+03 3.636e+03
* lev (lev) float64 0.9961 0.9826 0.9548 ... 3.543e-05 9.946e-06
* lat (lat) float64 -87.16 -83.48 -79.78 -76.07 ... 79.78 83.48 87.16
* lon (lon) float64 0.0 3.75 7.5 11.25 15.0 ... 345.0 348.8 352.5 356.2
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, 39, 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, 39), meta=np.ndarray>
b (time, lev) float64 dask.array<chunksize=(60, 39), meta=np.ndarray>
ps (time, lat, lon) float32 dask.array<chunksize=(60, 48, 96), meta=np.ndarray>
a_bnds (time, lev, bnds) float64 dask.array<chunksize=(60, 39, 2), meta=np.ndarray>
b_bnds (time, lev, bnds) float64 dask.array<chunksize=(60, 39, 2), meta=np.ndarray>
lat_bnds (time, lat, bnds) float64 dask.array<chunksize=(60, 48, 2), meta=np.ndarray>
lon_bnds (time, lon, bnds) float64 dask.array<chunksize=(60, 96, 2), meta=np.ndarray>
cl (time, lev, lat, lon) float32 dask.array<chunksize=(60, 39, 48, 96), meta=np.ndarray>
Attributes:
institution: CMCC - Centro Euro-Mediterraneo per i Cambiamenti...
institute_id: CMCC
experiment_id: rcp85
source: CMCC-CESM
model_id: CMCC-CESM
forcing: Nat,Ant,GHG,SA,Oz,Sl
parent_experiment_id: historical
parent_experiment_rip: r1i1p1
branch_time: 56978.0
contact: Marcello Vichi (marcello.vichi@cmcc.it)
history: Model output postprocessed with Afterburner and C...
comment: Equilibrium reached after more than 1500-year spi...
references: model described in the documentation at http://ww...
initialization_method: 1
physics_version: 1
tracking_id: b26673d2-4300-48b7-9fd2-e12bc21f52bb
product: output
experiment: RCP8.5
frequency: mon
creation_date: 2012-07-26T14:51:50Z
Conventions: CF-1.4
project_id: CMIP5
table_id: Table Amon (27 April 2011) a5a1c518f52ae340313ba0...
title: CMCC-CESM model output prepared for CMIP5 RCP8.5
parent_experiment: historical
modeling_realm: atmos
realization: 1
cmor_version: 2.7.1xarray.Dataset
- bnds: 2
- lat: 48
- lev: 39
- lon: 96
- time: 1152
- time(time)float6415.5 45.5 ... 3.606e+03 3.636e+03
- bounds :
- time_bnds
- calendar :
- standard
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([ 15.5, 45.5, 75.5, ..., 3575.5, 3606. , 3636.5])
- lev(lev)float640.9961 0.9826 ... 9.946e-06
- 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([9.961407e-01, 9.826334e-01, 9.547820e-01, 9.092581e-01, 8.464436e-01, 7.691647e-01, 6.816637e-01, 5.887858e-01, 4.965112e-01, 4.111473e-01, 3.369508e-01, 2.745220e-01, 2.222662e-01, 1.787704e-01, 1.427904e-01, 1.132339e-01, 8.914075e-02, 6.966111e-02, 5.403643e-02, 4.159872e-02, 3.177400e-02, 2.407468e-02, 1.809012e-02, 1.347742e-02, 9.952803e-03, 7.283551e-03, 5.280590e-03, 3.791768e-03, 2.695854e-03, 1.894518e-03, 1.310861e-03, 8.905416e-04, 5.934676e-04, 3.875889e-04, 2.457438e-04, 1.463488e-04, 7.804715e-05, 3.543221e-05, 9.945912e-06]) - lat(lat)float64-87.16 -83.48 ... 83.48 87.16
- bounds :
- lat_bnds
- units :
- degrees_north
- axis :
- Y
- long_name :
- latitude
- standard_name :
- latitude
array([-87.159095, -83.478937, -79.777046, -76.070244, -72.361581, -68.652017, -64.941949, -61.231573, -57.520994, -53.810274, -50.099453, -46.388558, -42.677606, -38.96661 , -35.25558 , -31.544523, -27.833444, -24.122348, -20.411238, -16.700118, -12.988989, -9.277853, -5.566714, -1.855571, 1.855571, 5.566714, 9.277853, 12.988989, 16.700118, 20.411238, 24.122348, 27.833444, 31.544523, 35.25558 , 38.96661 , 42.677606, 46.388558, 50.099453, 53.810274, 57.520994, 61.231573, 64.941949, 68.652017, 72.361581, 76.070244, 79.777046, 83.478937, 87.159095]) - lon(lon)float640.0 3.75 7.5 ... 348.8 352.5 356.2
- bounds :
- lon_bnds
- units :
- degrees_east
- axis :
- X
- long_name :
- longitude
- standard_name :
- longitude
array([ 0. , 3.75, 7.5 , 11.25, 15. , 18.75, 22.5 , 26.25, 30. , 33.75, 37.5 , 41.25, 45. , 48.75, 52.5 , 56.25, 60. , 63.75, 67.5 , 71.25, 75. , 78.75, 82.5 , 86.25, 90. , 93.75, 97.5 , 101.25, 105. , 108.75, 112.5 , 116.25, 120. , 123.75, 127.5 , 131.25, 135. , 138.75, 142.5 , 146.25, 150. , 153.75, 157.5 , 161.25, 165. , 168.75, 172.5 , 176.25, 180. , 183.75, 187.5 , 191.25, 195. , 198.75, 202.5 , 206.25, 210. , 213.75, 217.5 , 221.25, 225. , 228.75, 232.5 , 236.25, 240. , 243.75, 247.5 , 251.25, 255. , 258.75, 262.5 , 266.25, 270. , 273.75, 277.5 , 281.25, 285. , 288.75, 292.5 , 296.25, 300. , 303.75, 307.5 , 311.25, 315. , 318.75, 322.5 , 326.25, 330. , 333.75, 337.5 , 341.25, 345. , 348.75, 352.5 , 356.25])
- time_bnds(time, bnds)float64dask.array<chunksize=(60, 2), meta=np.ndarray>
Array Chunk Bytes 18.43 kB 1.92 kB Shape (1152, 2) (120, 2) Count 33 Tasks 11 Chunks Type float64 numpy.ndarray - lev_bnds(time, lev, bnds)float64dask.array<chunksize=(60, 39, 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 718.85 kB 74.88 kB Shape (1152, 39, 2) (120, 39, 2) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - p0(time)float32100000.0 100000.0 ... 100000.0
- long_name :
- vertical coordinate formula term: reference pressure
- units :
- Pa
array([100000., 100000., 100000., ..., 100000., 100000., 100000.], dtype=float32) - a(time, lev)float64dask.array<chunksize=(60, 39), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: a(k)
Array Chunk Bytes 359.42 kB 37.44 kB Shape (1152, 39) (120, 39) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - b(time, lev)float64dask.array<chunksize=(60, 39), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: b(k)
Array Chunk Bytes 359.42 kB 37.44 kB Shape (1152, 39) (120, 39) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - ps(time, lat, lon)float32dask.array<chunksize=(60, 48, 96), 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 21.23 MB 2.21 MB Shape (1152, 48, 96) (120, 48, 96) Count 33 Tasks 11 Chunks Type float32 numpy.ndarray - a_bnds(time, lev, bnds)float64dask.array<chunksize=(60, 39, 2), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: a(k+1/2)
Array Chunk Bytes 718.85 kB 74.88 kB Shape (1152, 39, 2) (120, 39, 2) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - b_bnds(time, lev, bnds)float64dask.array<chunksize=(60, 39, 2), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: b(k+1/2)
Array Chunk Bytes 718.85 kB 74.88 kB Shape (1152, 39, 2) (120, 39, 2) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - lat_bnds(time, lat, bnds)float64dask.array<chunksize=(60, 48, 2), meta=np.ndarray>
Array Chunk Bytes 884.74 kB 92.16 kB Shape (1152, 48, 2) (120, 48, 2) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - lon_bnds(time, lon, bnds)float64dask.array<chunksize=(60, 96, 2), meta=np.ndarray>
Array Chunk Bytes 1.77 MB 184.32 kB Shape (1152, 96, 2) (120, 96, 2) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - cl(time, lev, lat, lon)float32dask.array<chunksize=(60, 39, 48, 96), meta=np.ndarray>
- standard_name :
- cloud_area_fraction_in_atmosphere_layer
- long_name :
- Cloud Area Fraction
- comment :
- Includes both large-scale and convective cloud.
- units :
- %
- original_name :
- aclcac
- original_units :
- percent
- history :
- 2012-07-26T14:51:49Z altered by CMOR: Converted units from 'percent' to '%'. 2012-07-26T14:51:50Z altered by CMOR: Inverted axis: lev. 2012-07-26T14:51:50Z 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-CESM_rcp85_r0i0p0.nc areacella: areacella_fx_CMCC-CESM_rcp85_r0i0p0.nc
Array Chunk Bytes 828.11 MB 86.26 MB Shape (1152, 39, 48, 96) (120, 39, 48, 96) Count 33 Tasks 11 Chunks Type float32 numpy.ndarray
- institution :
- CMCC - Centro Euro-Mediterraneo per i Cambiamenti Climatici, Bologna, Italy
- institute_id :
- CMCC
- experiment_id :
- rcp85
- source :
- CMCC-CESM
- model_id :
- CMCC-CESM
- forcing :
- Nat,Ant,GHG,SA,Oz,Sl
- parent_experiment_id :
- historical
- parent_experiment_rip :
- r1i1p1
- branch_time :
- 56978.0
- contact :
- Marcello Vichi (marcello.vichi@cmcc.it)
- history :
- Model output postprocessed with Afterburner and CDO (https://code.zmaw.de/projects) 2012-07-26T14:51:50Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- comment :
- Equilibrium reached after more than 1500-year spin-up of the physics, 200-year spin-up of carbon content and 276 year at pre-industrial GHG concentrations after which data were output with nominal date of January 1850.
- references :
- model described in the documentation at http://www.cmcc.it/data-models/models
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- b26673d2-4300-48b7-9fd2-e12bc21f52bb
- product :
- output
- experiment :
- RCP8.5
- frequency :
- mon
- creation_date :
- 2012-07-26T14:51:50Z
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table Amon (27 April 2011) a5a1c518f52ae340313ba0aada03f862
- title :
- CMCC-CESM model output prepared for CMIP5 RCP8.5
- parent_experiment :
- historical
- modeling_realm :
- atmos
- realization :
- 1
- cmor_version :
- 2.7.1