MPI-ESM-LR 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_MPI-ESM-LR_rcp85_r3i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | MPI-ESM-LR model output prepared for CMIP5 RCP8.5 |
| location | /shared/cmip5/data/rcp85/atmos/mon/Amon/cl/MPI-M.MPI-ESM-LR/r3i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/cl_Amon_MPI-ESM-LR_rcp85_r3i1p1.yaml |
| last updated | 2013-06-14 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, lat: 96, lev: 47, 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 ... 4.225e-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, 47, 2), meta=np.ndarray>
ap (time, lev) float64 dask.array<chunksize=(48, 47), meta=np.ndarray>
b (time, lev) float64 dask.array<chunksize=(48, 47), 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, 47, 2), meta=np.ndarray>
b_bnds (time, lev, bnds) float64 dask.array<chunksize=(48, 47, 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>
cl (time, lev, lat, lon) float32 dask.array<chunksize=(48, 47, 96, 192), meta=np.ndarray>
Attributes:
institution: Max Planck Institute for Meteorology
institute_id: MPI-M
experiment_id: rcp85
source: MPI-ESM-LR 2011; URL: http://svn.zmaw.de/svn/cosm...
model_id: MPI-ESM-LR
forcing: GHG Oz SD Sl Vl LU
parent_experiment_id: historical
parent_experiment_rip: r3i1p1
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: 6b07b702-6a3c-4230-a11d-e73a53b18ff0
product: output
experiment: RCP8.5
frequency: mon
creation_date: 2011-07-12T18:21:14Z
Conventions: CF-1.4
project_id: CMIP5
table_id: Table Amon (27 April 2011) a5a1c518f52ae340313ba0...
title: MPI-ESM-LR model output prepared for CMIP5 RCP8.5
parent_experiment: historical
modeling_realm: atmos
realization: 3
cmor_version: 2.5.9xarray.Dataset
- bnds: 2
- lat: 96
- lev: 47
- 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, 5.363946e-01, 4.934380e-01, 4.517182e-01, 4.114154e-01, 3.726136e-01, 3.354221e-01, 3.000480e-01, 2.666209e-01, 2.352179e-01, 2.059397e-01, 1.787885e-01, 1.537470e-01, 1.306586e-01, 1.092082e-01, 8.982902e-02, 7.309098e-02, 5.886336e-02, 4.689628e-02, 3.694117e-02, 2.875524e-02, 2.206205e-02, 1.662554e-02, 1.228782e-02, 8.893068e-03, 6.291450e-03, 4.342560e-03, 2.918469e-03, 1.903934e-03, 1.199425e-03, 7.259045e-04, 4.202813e-04, 2.284638e-04, 1.097754e-04, 4.224661e-05, 9.815866e-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, 47, 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 857.28 kB 99.26 kB Shape (1140, 47, 2) (132, 47, 2) Count 40 Tasks 10 Chunks Type float64 numpy.ndarray - ap(time, lev)float64dask.array<chunksize=(48, 47), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: ap(k)
- units :
- Pa
Array Chunk Bytes 428.64 kB 49.63 kB Shape (1140, 47) (132, 47) Count 40 Tasks 10 Chunks Type float64 numpy.ndarray - b(time, lev)float64dask.array<chunksize=(48, 47), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: b(k)
Array Chunk Bytes 428.64 kB 49.63 kB Shape (1140, 47) (132, 47) 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, 47, 2), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: ap(k+1/2)
- units :
- Pa
Array Chunk Bytes 857.28 kB 99.26 kB Shape (1140, 47, 2) (132, 47, 2) Count 40 Tasks 10 Chunks Type float64 numpy.ndarray - b_bnds(time, lev, bnds)float64dask.array<chunksize=(48, 47, 2), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: b(k+1/2)
Array Chunk Bytes 857.28 kB 99.26 kB Shape (1140, 47, 2) (132, 47, 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 - cl(time, lev, lat, lon)float32dask.array<chunksize=(48, 47, 96, 192), 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 :
- %
- cell_methods :
- time: mean
- cell_measures :
- area: areacella
- history :
- 2011-07-12T18:21:13Z altered by CMOR: replaced missing value flag (1e+22) with standard missing value (1e+20). 2011-07-12T18:21:14Z altered by CMOR: Inverted axis: lev.
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MPI-ESM-LR_rcp85_r0i0p0.nc areacella: areacella_fx_MPI-ESM-LR_rcp85_r0i0p0.nc
Array Chunk Bytes 3.95 GB 457.41 MB Shape (1140, 47, 96, 192) (132, 47, 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-LR 2011; URL: http://svn.zmaw.de/svn/cosmos/branches/releases/mpi-esm-cmip5/src/mod; atmosphere: ECHAM6 (REV: 4619), T63L47; land: JSBACH (REV: 4619); ocean: MPIOM (REV: 4619), GR15L40; sea ice: 4619; marine bgc: HAMOCC (REV: 4619);
- model_id :
- MPI-ESM-LR
- forcing :
- GHG Oz SD Sl Vl LU
- parent_experiment_id :
- historical
- parent_experiment_rip :
- r3i1p1
- 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: 3412 2011-07-12T18:21:14Z 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: http://www.mpimet.mpg.de/fileadmin/models/MPIOM/HAMOCC5.1_TECHNICAL_REPORT.pdf;
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- 6b07b702-6a3c-4230-a11d-e73a53b18ff0
- product :
- output
- experiment :
- RCP8.5
- frequency :
- mon
- creation_date :
- 2011-07-12T18:21:14Z
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table Amon (27 April 2011) a5a1c518f52ae340313ba0aada03f862
- title :
- MPI-ESM-LR model output prepared for CMIP5 RCP8.5
- parent_experiment :
- historical
- modeling_realm :
- atmos
- realization :
- 3
- cmor_version :
- 2.5.9