CMCC-CM model output prepared for CMIP5 AMIP
Load in Python
from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/rsut_Amon_CMCC-CM_amip_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | CMCC-CM model output prepared for CMIP5 AMIP | 
| location | /shared/cmip5/data/amip/atmos/mon/Amon/rsut/CMCC.CMCC-CM/r1i1p1 | 
| tags | gridded,global,model,monthly | 
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/rsut_Amon_CMCC-CM_amip_r1i1p1.yaml | 
| last updated | 2013-08-29 | 
Dataset Contents
<xarray.Dataset>
Dimensions:    (bnds: 2, lat: 240, lon: 480, time: 360)
Coordinates:
  * time       (time) float64 15.5 45.0 74.5 ... 3.576e+03 3.607e+03 3.638e+03
  * 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=(120, 2), meta=np.ndarray>
    lat_bnds   (time, lat, bnds) float64 dask.array<chunksize=(120, 240, 2), meta=np.ndarray>
    lon_bnds   (time, lon, bnds) float64 dask.array<chunksize=(120, 480, 2), meta=np.ndarray>
    rsut       (time, lat, lon) float32 dask.array<chunksize=(120, 240, 480), meta=np.ndarray>
Attributes:
    institution:            CMCC - Centro Euro-Mediterraneo per i Cambiamenti
    institute_id:           CMCC
    experiment_id:          amip
    source:                 CMCC-CM
    model_id:               CMCC-CM
    forcing:                Nat,GHG,SA,TO,Sl
    parent_experiment_id:   historical
    parent_experiment_rip:  N/A
    branch_time:            37254.0
    contact:                Silvio Gualdi (gualdi@bo.ingv.it)
    history:                Model output postprocessed with CDO 2012-08-03T19...
    comment:                initial cond. taken at the end of year 1978 of an...
    references:             model described in the documentation at http://ww...
    initialization_method:  1
    physics_version:        1
    tracking_id:            c5644fb7-0f6d-42b5-b5cc-c0f3fa4dcebc
    product:                output
    experiment:             AMIP
    frequency:              mon
    creation_date:          2012-08-03T19:29:58Z
    Conventions:            CF-1.4
    project_id:             CMIP5
    table_id:               Table Amon (27 April 2011) a5a1c518f52ae340313ba0...
    title:                  CMCC-CM model output prepared for CMIP5 AMIP
    parent_experiment:      historical
    modeling_realm:         atmos
    realization:            1
    cmor_version:           2.7.1xarray.Dataset
- bnds: 2
- lat: 240
- lon: 480
- time: 360
 
- time(time)float6415.5 45.0 ... 3.607e+03 3.638e+03- bounds :
- time_bnds
- calendar :
- standard
- axis :
- T
- long_name :
- time
- standard_name :
- time
 array([ 15.5, 45. , 74.5, ..., 3576.5, 3607. , 3637.5]) 
- 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)float640.0 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]) 
 
- time_bnds(time, bnds)float64dask.array<chunksize=(120, 2), meta=np.ndarray>Array Chunk Bytes 5.76 kB 1.92 kB Shape (360, 2) (120, 2) Count 9 Tasks 3 Chunks Type float64 numpy.ndarray 
- lat_bnds(time, lat, bnds)float64dask.array<chunksize=(120, 240, 2), meta=np.ndarray>Array Chunk Bytes 1.38 MB 460.80 kB Shape (360, 240, 2) (120, 240, 2) Count 12 Tasks 3 Chunks Type float64 numpy.ndarray 
- lon_bnds(time, lon, bnds)float64dask.array<chunksize=(120, 480, 2), meta=np.ndarray>Array Chunk Bytes 2.76 MB 921.60 kB Shape (360, 480, 2) (120, 480, 2) Count 12 Tasks 3 Chunks Type float64 numpy.ndarray 
- rsut(time, lat, lon)float32dask.array<chunksize=(120, 240, 480), meta=np.ndarray>- standard_name :
- toa_outgoing_shortwave_flux
- long_name :
- TOA Outgoing Shortwave Radiation
- comment :
- at the top of the atmosphere
- units :
- W m-2
- original_name :
- srad0
- original_units :
- W/m^2
- history :
- 2012-08-03T19:29:58Z altered by CMOR: Converted units from 'W/m^2' to 'W m-2'. 2012-08-03T19:29:58Z altered by CMOR: Changed sign. 2012-08-03T19:29:58Z 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_amip_r0i0p0.nc areacella: areacella_fx_CMCC-CM_amip_r0i0p0.nc
 Array Chunk Bytes 165.89 MB 55.30 MB Shape (360, 240, 480) (120, 240, 480) Count 9 Tasks 3 Chunks Type float32 numpy.ndarray 
 
- institution :
- CMCC - Centro Euro-Mediterraneo per i Cambiamenti
- institute_id :
- CMCC
- experiment_id :
- amip
- source :
- CMCC-CM
- model_id :
- CMCC-CM
- forcing :
- Nat,GHG,SA,TO,Sl
- parent_experiment_id :
- historical
- parent_experiment_rip :
- N/A
- branch_time :
- 37254.0
- contact :
- Silvio Gualdi (gualdi@bo.ingv.it)
- history :
- Model output postprocessed with CDO 2012-08-03T19:29:58Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- comment :
- initial cond. taken at the end of year 1978 of an amip simulation that was started on year 1952 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 :
- c5644fb7-0f6d-42b5-b5cc-c0f3fa4dcebc
- product :
- output
- experiment :
- AMIP
- frequency :
- mon
- creation_date :
- 2012-08-03T19:29:58Z
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table Amon (27 April 2011) a5a1c518f52ae340313ba0aada03f862
- title :
- CMCC-CM model output prepared for CMIP5 AMIP
- parent_experiment :
- historical
- modeling_realm :
- atmos
- realization :
- 1
- cmor_version :
- 2.7.1
 
