MPI-ESM-MR 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_MPI-ESM-MR_rcp85_r1i1p1.yaml")
ds=cat.netcdf.read()
Metadata
title | MPI-ESM-MR model output prepared for CMIP5 RCP8.5 |
location | /shared/cmip5/data/rcp85/atmos/mon/Amon/clw/MPI-M.MPI-ESM-MR/r1i1p1 |
tags | gridded,global,model,monthly |
catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/clw_Amon_MPI-ESM-MR_rcp85_r1i1p1.yaml |
last updated | 2013-06-14 |
Dataset Contents
<xarray.Dataset> Dimensions: (bnds: 2, lat: 96, lev: 95, lon: 192, time: 1140) Coordinates: * time (time) float64 5.699e+04 5.702e+04 ... 9.163e+04 9.166e+04 * lev (lev) float64 0.9961 0.9826 0.959 ... 2.31e-05 9.816e-06 * lat (lat) float64 -88.57 -86.72 -84.86 -83.0 ... 84.86 86.72 88.57 * lon (lon) float64 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1 Dimensions without coordinates: bnds Data variables: time_bnds (time, bnds) float64 dask.array<chunksize=(48, 2), meta=np.ndarray> lev_bnds (time, lev, bnds) float64 dask.array<chunksize=(48, 95, 2), meta=np.ndarray> ap (time, lev) float64 dask.array<chunksize=(48, 95), meta=np.ndarray> b (time, lev) float64 dask.array<chunksize=(48, 95), meta=np.ndarray> ps (time, lat, lon) float32 dask.array<chunksize=(48, 96, 192), meta=np.ndarray> ap_bnds (time, lev, bnds) float64 dask.array<chunksize=(48, 95, 2), meta=np.ndarray> b_bnds (time, lev, bnds) float64 dask.array<chunksize=(48, 95, 2), meta=np.ndarray> lat_bnds (time, lat, bnds) float64 dask.array<chunksize=(48, 96, 2), meta=np.ndarray> lon_bnds (time, lon, bnds) float64 dask.array<chunksize=(48, 192, 2), meta=np.ndarray> clw (time, lev, lat, lon) float32 dask.array<chunksize=(48, 95, 96, 192), meta=np.ndarray> Attributes: institution: Max Planck Institute for Meteorology institute_id: MPI-M experiment_id: rcp85 source: MPI-ESM-MR 2011; URL: http://svn.zmaw.de/svn/cosm... model_id: MPI-ESM-MR forcing: GHG,Oz,SD,Sl,Vl,LU parent_experiment_id: historical parent_experiment_rip: r1i1p1 branch_time: 56978.0 contact: cmip5-mpi-esm@dkrz.de history: Model raw output postprocessing with modelling en... references: ECHAM6: n/a; JSBACH: Raddatz et al., 2007. Will t... initialization_method: 1 physics_version: 1 tracking_id: 0cf7bfa2-ae34-4333-9603-a9dc265e82ae product: output experiment: RCP8.5 frequency: mon creation_date: 2011-11-14T17:28:28Z Conventions: CF-1.4 project_id: CMIP5 table_id: Table Amon (27 April 2011) a5a1c518f52ae340313ba0... title: MPI-ESM-MR model output prepared for CMIP5 RCP8.5 parent_experiment: historical modeling_realm: atmos realization: 1 cmor_version: 2.6.0
xarray.Dataset
- bnds: 2
- lat: 96
- lev: 95
- lon: 192
- time: 1140
- time(time)float645.699e+04 5.702e+04 ... 9.166e+04
- bounds :
- time_bnds
- units :
- days since 1850-1-1 00:00:00
- calendar :
- proleptic_gregorian
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([56993.5, 57023. , 57052.5, ..., 91599.5, 91630. , 91660.5])
- lev(lev)float640.9961 0.9826 ... 9.816e-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 = ap + b*ps
- formula_terms :
- ap: ap b: b ps: ps
array([9.961500e-01, 9.826500e-01, 9.589556e-01, 9.276460e-01, 8.908394e-01, 8.501503e-01, 8.068475e-01, 7.620137e-01, 7.164562e-01, 6.707188e-01, 6.252446e-01, 5.803910e-01, 5.366074e-01, 4.942692e-01, 4.537201e-01, 4.154341e-01, 3.797069e-01, 3.466272e-01, 3.161519e-01, 2.881811e-01, 2.625506e-01, 2.391084e-01, 2.177225e-01, 1.982337e-01, 1.804680e-01, 1.642867e-01, 1.495502e-01, 1.361203e-01, 1.238958e-01, 1.127819e-01, 1.026525e-01, 9.340927e-02, 8.499143e-02, 7.732509e-02, 7.033860e-02, 6.396105e-02, 5.814545e-02, 5.284837e-02, 4.802120e-02, 4.362085e-02, 3.960960e-02, 3.595304e-02, 3.261980e-02, 2.958129e-02, 2.681146e-02, 2.428654e-02, 2.198489e-02, 1.988675e-02, 1.797414e-02, 1.623065e-02, 1.464207e-02, 1.319605e-02, 1.188111e-02, 1.068652e-02, 9.602347e-03, 8.619337e-03, 7.728926e-03, 6.923179e-03, 6.194759e-03, 5.536888e-03, 4.943310e-03, 4.408264e-03, 3.926449e-03, 3.492988e-03, 3.103407e-03, 2.753606e-03, 2.439827e-03, 2.158631e-03, 1.906879e-03, 1.681707e-03, 1.480501e-03, 1.300885e-03, 1.140697e-03, 9.979719e-04, 8.709289e-04, 7.579535e-04, 6.575843e-04, 5.685002e-04, 4.895081e-04, 4.195318e-04, 3.577273e-04, 3.034278e-04, 2.559719e-04, 2.147130e-04, 1.790279e-04, 1.483228e-04, 1.220382e-04, 9.965253e-05, 8.068427e-05, 6.469293e-05, 5.127906e-05, 4.008352e-05, 3.078596e-05, 2.310285e-05, 9.815852e-06])
- lat(lat)float64-88.57 -86.72 ... 86.72 88.57
- bounds :
- lat_bnds
- units :
- degrees_north
- axis :
- Y
- long_name :
- latitude
- standard_name :
- latitude
array([-88.572166, -86.722534, -84.861969, -82.99894 , -81.134979, -79.270561, -77.405891, -75.541061, -73.676132, -71.811134, -69.946083, -68.080994, -66.215874, -64.350731, -62.485569, -60.620396, -58.755211, -56.890015, -55.024807, -53.159595, -51.294376, -49.429153, -47.563927, -45.698692, -43.833458, -41.96822 , -40.102978, -38.237736, -36.37249 , -34.507244, -32.641994, -30.776745, -28.911493, -27.04624 , -25.180986, -23.315731, -21.450476, -19.585218, -17.719961, -15.854704, -13.989446, -12.124187, -10.258928, -8.393669, -6.528409, -4.66315 , -2.79789 , -0.93263 , 0.93263 , 2.79789 , 4.66315 , 6.528409, 8.393669, 10.258928, 12.124187, 13.989446, 15.854704, 17.719961, 19.585218, 21.450476, 23.315731, 25.180986, 27.04624 , 28.911493, 30.776745, 32.641994, 34.507244, 36.37249 , 38.237736, 40.102978, 41.96822 , 43.833458, 45.698692, 47.563927, 49.429153, 51.294376, 53.159595, 55.024807, 56.890011, 58.755211, 60.620396, 62.485569, 64.350731, 66.215874, 68.080994, 69.946083, 71.811134, 73.676132, 75.541061, 77.405891, 79.270561, 81.134979, 82.99894 , 84.861969, 86.722534, 88.572166])
- lon(lon)float640.0 1.875 3.75 ... 356.2 358.1
- bounds :
- lon_bnds
- units :
- degrees_east
- axis :
- X
- long_name :
- longitude
- standard_name :
- longitude
array([ 0. , 1.875, 3.75 , 5.625, 7.5 , 9.375, 11.25 , 13.125, 15. , 16.875, 18.75 , 20.625, 22.5 , 24.375, 26.25 , 28.125, 30. , 31.875, 33.75 , 35.625, 37.5 , 39.375, 41.25 , 43.125, 45. , 46.875, 48.75 , 50.625, 52.5 , 54.375, 56.25 , 58.125, 60. , 61.875, 63.75 , 65.625, 67.5 , 69.375, 71.25 , 73.125, 75. , 76.875, 78.75 , 80.625, 82.5 , 84.375, 86.25 , 88.125, 90. , 91.875, 93.75 , 95.625, 97.5 , 99.375, 101.25 , 103.125, 105. , 106.875, 108.75 , 110.625, 112.5 , 114.375, 116.25 , 118.125, 120. , 121.875, 123.75 , 125.625, 127.5 , 129.375, 131.25 , 133.125, 135. , 136.875, 138.75 , 140.625, 142.5 , 144.375, 146.25 , 148.125, 150. , 151.875, 153.75 , 155.625, 157.5 , 159.375, 161.25 , 163.125, 165. , 166.875, 168.75 , 170.625, 172.5 , 174.375, 176.25 , 178.125, 180. , 181.875, 183.75 , 185.625, 187.5 , 189.375, 191.25 , 193.125, 195. , 196.875, 198.75 , 200.625, 202.5 , 204.375, 206.25 , 208.125, 210. , 211.875, 213.75 , 215.625, 217.5 , 219.375, 221.25 , 223.125, 225. , 226.875, 228.75 , 230.625, 232.5 , 234.375, 236.25 , 238.125, 240. , 241.875, 243.75 , 245.625, 247.5 , 249.375, 251.25 , 253.125, 255. , 256.875, 258.75 , 260.625, 262.5 , 264.375, 266.25 , 268.125, 270. , 271.875, 273.75 , 275.625, 277.5 , 279.375, 281.25 , 283.125, 285. , 286.875, 288.75 , 290.625, 292.5 , 294.375, 296.25 , 298.125, 300. , 301.875, 303.75 , 305.625, 307.5 , 309.375, 311.25 , 313.125, 315. , 316.875, 318.75 , 320.625, 322.5 , 324.375, 326.25 , 328.125, 330. , 331.875, 333.75 , 335.625, 337.5 , 339.375, 341.25 , 343.125, 345. , 346.875, 348.75 , 350.625, 352.5 , 354.375, 356.25 , 358.125])
- time_bnds(time, bnds)float64dask.array<chunksize=(48, 2), meta=np.ndarray>
Array Chunk Bytes 18.24 kB 2.11 kB Shape (1140, 2) (132, 2) Count 30 Tasks 10 Chunks Type float64 numpy.ndarray - lev_bnds(time, lev, bnds)float64dask.array<chunksize=(48, 95, 2), meta=np.ndarray>
- formula :
- p = ap + b*ps
- standard_name :
- atmosphere_hybrid_sigma_pressure_coordinate
- units :
- 1
- formula_terms :
- ap: ap_bnds b: b_bnds ps: ps
Array Chunk Bytes 1.73 MB 200.64 kB Shape (1140, 95, 2) (132, 95, 2) Count 40 Tasks 10 Chunks Type float64 numpy.ndarray - ap(time, lev)float64dask.array<chunksize=(48, 95), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: ap(k)
- units :
- Pa
Array Chunk Bytes 866.40 kB 100.32 kB Shape (1140, 95) (132, 95) Count 40 Tasks 10 Chunks Type float64 numpy.ndarray - b(time, lev)float64dask.array<chunksize=(48, 95), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: b(k)
Array Chunk Bytes 866.40 kB 100.32 kB Shape (1140, 95) (132, 95) Count 40 Tasks 10 Chunks Type float64 numpy.ndarray - ps(time, lat, lon)float32dask.array<chunksize=(48, 96, 192), 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 84.05 MB 9.73 MB Shape (1140, 96, 192) (132, 96, 192) Count 30 Tasks 10 Chunks Type float32 numpy.ndarray - ap_bnds(time, lev, bnds)float64dask.array<chunksize=(48, 95, 2), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: ap(k+1/2)
- units :
- Pa
Array Chunk Bytes 1.73 MB 200.64 kB Shape (1140, 95, 2) (132, 95, 2) Count 40 Tasks 10 Chunks Type float64 numpy.ndarray - b_bnds(time, lev, bnds)float64dask.array<chunksize=(48, 95, 2), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: b(k+1/2)
Array Chunk Bytes 1.73 MB 200.64 kB Shape (1140, 95, 2) (132, 95, 2) Count 40 Tasks 10 Chunks Type float64 numpy.ndarray - lat_bnds(time, lat, bnds)float64dask.array<chunksize=(48, 96, 2), meta=np.ndarray>
Array Chunk Bytes 1.75 MB 202.75 kB Shape (1140, 96, 2) (132, 96, 2) Count 40 Tasks 10 Chunks Type float64 numpy.ndarray - lon_bnds(time, lon, bnds)float64dask.array<chunksize=(48, 192, 2), meta=np.ndarray>
Array Chunk Bytes 3.50 MB 405.50 kB Shape (1140, 192, 2) (132, 192, 2) Count 40 Tasks 10 Chunks Type float64 numpy.ndarray - clw(time, lev, lat, lon)float32dask.array<chunksize=(48, 95, 96, 192), 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
- cell_methods :
- time: mean
- cell_measures :
- area: areacella
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MPI-ESM-MR_rcp85_r0i0p0.nc areacella: areacella_fx_MPI-ESM-MR_rcp85_r0i0p0.nc
- history :
- 2011-11-14T17:28:28Z altered by CMOR: Inverted axis: lev.
Array Chunk Bytes 7.98 GB 924.55 MB Shape (1140, 95, 96, 192) (132, 95, 96, 192) Count 30 Tasks 10 Chunks Type float32 numpy.ndarray
- institution :
- Max Planck Institute for Meteorology
- institute_id :
- MPI-M
- experiment_id :
- rcp85
- source :
- MPI-ESM-MR 2011; URL: http://svn.zmaw.de/svn/cosmos/branches/releases/mpi-esm-cmip5/src/mod; atmosphere: ECHAM6 (REV: 4936), T63L47; land: JSBACH (REV: 4936); ocean: MPIOM (REV: 4936), GR15L40; sea ice: 4936; marine bgc: HAMOCC (REV: 4936);
- model_id :
- MPI-ESM-MR
- forcing :
- GHG,Oz,SD,Sl,Vl,LU
- parent_experiment_id :
- historical
- parent_experiment_rip :
- r1i1p1
- branch_time :
- 56978.0
- contact :
- cmip5-mpi-esm@dkrz.de
- history :
- Model raw output postprocessing with modelling environment (IMDI) at DKRZ: URL: http://svn-mad.zmaw.de/svn/mad/Model/IMDI/trunk, REV: 3998 2011-11-14T17:28:11Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- references :
- ECHAM6: n/a; JSBACH: Raddatz et al., 2007. Will the tropical land biosphere dominate the climate-carbon cycle feedback during the twenty first century? Climate Dynamics, 29, 565-574, doi 10.1007/s00382-007-0247-8; MPIOM: Marsland et al., 2003. The Max-Planck-Institute global ocean/sea ice model with orthogonal curvilinear coordinates. Ocean Modelling, 5, 91-127; HAMOCC: Technical Documentation, http://www.mpimet.mpg.de/fileadmin/models/MPIOM/HAMOCC5.1_TECHNICAL_REPORT.pdf;
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- 0cf7bfa2-ae34-4333-9603-a9dc265e82ae
- product :
- output
- experiment :
- RCP8.5
- frequency :
- mon
- creation_date :
- 2011-11-14T17:28:28Z
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table Amon (27 April 2011) a5a1c518f52ae340313ba0aada03f862
- title :
- MPI-ESM-MR model output prepared for CMIP5 RCP8.5
- parent_experiment :
- historical
- modeling_realm :
- atmos
- realization :
- 1
- cmor_version :
- 2.6.0