IPSL-CM5A-MR model output prepared for CMIP5 abrupt 4XCO2
Load in Python
from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/cli_Amon_IPSL-CM5A-MR_abrupt4xCO2_r1i1p1.yaml")
ds=cat.netcdf.read()
Metadata
| title | IPSL-CM5A-MR model output prepared for CMIP5 abrupt 4XCO2 |
| location | /shared/cmip5/data/abrupt4xCO2/atmos/mon/Amon/cli/IPSL.IPSL-CM5A-MR/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/cli_Amon_IPSL-CM5A-MR_abrupt4xCO2_r1i1p1.yaml |
| last updated | 2013-05-23 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, lat: 143, lev: 39, lon: 144, time: 1680)
Coordinates:
* time (time) float64 15.5 45.0 74.5 ... 5.102e+04 5.105e+04 5.108e+04
* lev (lev) float64 0.9958 0.9863 0.9736 ... 0.0001571 4.251e-05
* lat (lat) float64 -90.0 -88.73 -87.46 -86.2 ... 86.2 87.46 88.73 90.0
* lon (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5
Dimensions without coordinates: bnds
Data variables:
time_bnds (time, bnds) float64 dask.array<chunksize=(600, 2), meta=np.ndarray>
lev_bnds (time, lev, bnds) float64 dask.array<chunksize=(600, 39, 2), meta=np.ndarray>
ap (time, lev) float64 dask.array<chunksize=(600, 39), meta=np.ndarray>
b (time, lev) float64 dask.array<chunksize=(600, 39), meta=np.ndarray>
ps (time, lat, lon) float32 dask.array<chunksize=(600, 143, 144), meta=np.ndarray>
ap_bnds (time, lev, bnds) float64 dask.array<chunksize=(600, 39, 2), meta=np.ndarray>
b_bnds (time, lev, bnds) float64 dask.array<chunksize=(600, 39, 2), meta=np.ndarray>
lat_bnds (time, lat, bnds) float64 dask.array<chunksize=(600, 143, 2), meta=np.ndarray>
lon_bnds (time, lon, bnds) float64 dask.array<chunksize=(600, 144, 2), meta=np.ndarray>
cli (time, lev, lat, lon) float32 dask.array<chunksize=(600, 39, 143, 144), meta=np.ndarray>
Attributes:
institution: IPSL (Institut Pierre Simon Laplace, Paris, France)
institute_id: IPSL
experiment_id: abrupt4xCO2
source: IPSL-CM5A-MR (2010) : atmos : LMDZ4 (LMDZ4_v5, 14...
model_id: IPSL-CM5A-MR
forcing: GHG
parent_experiment_id: piControl
parent_experiment_rip: r1i1p1
branch_time: 1850.0
contact: ipsl-cmip5 _at_ ipsl.jussieu.fr Data manager : Se...
comment: This abrupt4xCO2 simulation was initiated from a ...
references: Model documentation and further reference availab...
initialization_method: 1
physics_version: 1
tracking_id: 769a5f23-5b36-42b5-8b8a-668081862d49
product: output
experiment: abrupt 4XCO2
frequency: mon
creation_date: 2012-01-16T00:17:53Z
history: 2012-01-16T00:17:53Z CMOR rewrote data to comply ...
Conventions: CF-1.4
project_id: CMIP5
table_id: Table Amon (31 January 2011) 53b766a395ac41696af4...
title: IPSL-CM5A-MR model output prepared for CMIP5 abru...
parent_experiment: pre-industrial control
modeling_realm: atmos
realization: 1
cmor_version: 2.7.1xarray.Dataset
- bnds: 2
- lat: 143
- lev: 39
- lon: 144
- time: 1680
- time(time)float6415.5 45.0 ... 5.105e+04 5.108e+04
- bounds :
- time_bnds
- units :
- days since 1850-01-01 00:00:00
- calendar :
- noleap
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([1.55000e+01, 4.50000e+01, 7.45000e+01, ..., 5.10235e+04, 5.10540e+04, 5.10845e+04]) - lev(lev)float640.9958 0.9863 ... 4.251e-05
- 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([9.957716e-01, 9.862627e-01, 9.736140e-01, 9.558820e-01, 9.313989e-01, 8.988125e-01, 8.571400e-01, 8.058494e-01, 7.449900e-01, 6.753821e-01, 5.988512e-01, 5.184424e-01, 4.384500e-01, 3.639867e-01, 2.998238e-01, 2.486269e-01, 2.096053e-01, 1.791188e-01, 1.532737e-01, 1.299950e-01, 1.088261e-01, 8.982668e-02, 7.305642e-02, 5.850303e-02, 4.608948e-02, 3.568636e-02, 2.712528e-02, 2.021213e-02, 1.473953e-02, 1.049771e-02, 7.283558e-03, 4.907410e-03, 3.197900e-03, 2.004757e-03, 1.199952e-03, 6.774612e-04, 3.520031e-04, 1.570627e-04, 4.250516e-05]) - lat(lat)float64-90.0 -88.73 -87.46 ... 88.73 90.0
- bounds :
- lat_bnds
- units :
- degrees_north
- axis :
- Y
- long_name :
- latitude
- standard_name :
- latitude
array([-90. , -88.732391, -87.46479 , -86.197182, -84.929581, -83.661972, -82.394363, -81.126762, -79.859154, -78.591553, -77.323944, -76.056335, -74.788734, -73.521126, -72.253525, -70.985916, -69.718307, -68.450706, -67.183098, -65.915489, -64.647888, -63.380283, -62.112675, -60.84507 , -59.577465, -58.30986 , -57.042255, -55.774647, -54.507042, -53.239437, -51.971832, -50.704224, -49.436619, -48.169014, -46.901409, -45.633804, -44.366196, -43.098591, -41.830986, -40.563381, -39.295776, -38.028168, -36.760563, -35.492958, -34.225353, -32.957745, -31.690142, -30.422535, -29.15493 , -27.887323, -26.619719, -25.352112, -24.084507, -22.816902, -21.549295, -20.281691, -19.014084, -17.746479, -16.478872, -15.211267, -13.943662, -12.676056, -11.408451, -10.140845, -8.87324 , -7.605634, -6.338028, -5.070423, -3.802817, -2.535211, -1.267606, 0. , 1.267606, 2.535211, 3.802817, 5.070423, 6.338028, 7.605634, 8.87324 , 10.140845, 11.408451, 12.676056, 13.943662, 15.211267, 16.478872, 17.746479, 19.014084, 20.281691, 21.549295, 22.816902, 24.084507, 25.352112, 26.619719, 27.887323, 29.15493 , 30.422535, 31.690142, 32.957745, 34.225353, 35.492958, 36.760563, 38.028168, 39.295776, 40.563381, 41.830986, 43.098591, 44.366196, 45.633804, 46.901409, 48.169014, 49.436619, 50.704224, 51.971832, 53.239437, 54.507042, 55.774647, 57.042255, 58.30986 , 59.577465, 60.84507 , 62.112675, 63.380283, 64.647888, 65.915489, 67.183098, 68.450706, 69.718307, 70.985916, 72.253525, 73.521126, 74.788734, 76.056335, 77.323944, 78.591553, 79.859154, 81.126762, 82.394363, 83.661972, 84.929581, 86.197182, 87.46479 , 88.732391, 90. ]) - lon(lon)float640.0 2.5 5.0 ... 352.5 355.0 357.5
- bounds :
- lon_bnds
- units :
- degrees_east
- axis :
- X
- long_name :
- longitude
- standard_name :
- longitude
array([ 0. , 2.5, 5. , 7.5, 10. , 12.5, 15. , 17.5, 20. , 22.5, 25. , 27.5, 30. , 32.5, 35. , 37.5, 40. , 42.5, 45. , 47.5, 50. , 52.5, 55. , 57.5, 60. , 62.5, 65. , 67.5, 70. , 72.5, 75. , 77.5, 80. , 82.5, 85. , 87.5, 90. , 92.5, 95. , 97.5, 100. , 102.5, 105. , 107.5, 110. , 112.5, 115. , 117.5, 120. , 122.5, 125. , 127.5, 130. , 132.5, 135. , 137.5, 140. , 142.5, 145. , 147.5, 150. , 152.5, 155. , 157.5, 160. , 162.5, 165. , 167.5, 170. , 172.5, 175. , 177.5, 180. , 182.5, 185. , 187.5, 190. , 192.5, 195. , 197.5, 200. , 202.5, 205. , 207.5, 210. , 212.5, 215. , 217.5, 220. , 222.5, 225. , 227.5, 230. , 232.5, 235. , 237.5, 240. , 242.5, 245. , 247.5, 250. , 252.5, 255. , 257.5, 260. , 262.5, 265. , 267.5, 270. , 272.5, 275. , 277.5, 280. , 282.5, 285. , 287.5, 290. , 292.5, 295. , 297.5, 300. , 302.5, 305. , 307.5, 310. , 312.5, 315. , 317.5, 320. , 322.5, 325. , 327.5, 330. , 332.5, 335. , 337.5, 340. , 342.5, 345. , 347.5, 350. , 352.5, 355. , 357.5])
- time_bnds(time, bnds)float64dask.array<chunksize=(600, 2), meta=np.ndarray>
Array Chunk Bytes 26.88 kB 9.60 kB Shape (1680, 2) (600, 2) Count 9 Tasks 3 Chunks Type float64 numpy.ndarray - lev_bnds(time, lev, bnds)float64dask.array<chunksize=(600, 39, 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 1.05 MB 374.40 kB Shape (1680, 39, 2) (600, 39, 2) Count 12 Tasks 3 Chunks Type float64 numpy.ndarray - ap(time, lev)float64dask.array<chunksize=(600, 39), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: ap(k)
- units :
- Pa
Array Chunk Bytes 524.16 kB 187.20 kB Shape (1680, 39) (600, 39) Count 12 Tasks 3 Chunks Type float64 numpy.ndarray - b(time, lev)float64dask.array<chunksize=(600, 39), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: b(k)
Array Chunk Bytes 524.16 kB 187.20 kB Shape (1680, 39) (600, 39) Count 12 Tasks 3 Chunks Type float64 numpy.ndarray - ps(time, lat, lon)float32dask.array<chunksize=(600, 143, 144), 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 138.38 MB 49.42 MB Shape (1680, 143, 144) (600, 143, 144) Count 9 Tasks 3 Chunks Type float32 numpy.ndarray - ap_bnds(time, lev, bnds)float64dask.array<chunksize=(600, 39, 2), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: ap(k+1/2)
- units :
- Pa
Array Chunk Bytes 1.05 MB 374.40 kB Shape (1680, 39, 2) (600, 39, 2) Count 12 Tasks 3 Chunks Type float64 numpy.ndarray - b_bnds(time, lev, bnds)float64dask.array<chunksize=(600, 39, 2), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: b(k+1/2)
Array Chunk Bytes 1.05 MB 374.40 kB Shape (1680, 39, 2) (600, 39, 2) Count 12 Tasks 3 Chunks Type float64 numpy.ndarray - lat_bnds(time, lat, bnds)float64dask.array<chunksize=(600, 143, 2), meta=np.ndarray>
Array Chunk Bytes 3.84 MB 1.37 MB Shape (1680, 143, 2) (600, 143, 2) Count 12 Tasks 3 Chunks Type float64 numpy.ndarray - lon_bnds(time, lon, bnds)float64dask.array<chunksize=(600, 144, 2), meta=np.ndarray>
Array Chunk Bytes 3.87 MB 1.38 MB Shape (1680, 144, 2) (600, 144, 2) Count 12 Tasks 3 Chunks Type float64 numpy.ndarray - cli(time, lev, lat, lon)float32dask.array<chunksize=(600, 39, 143, 144), meta=np.ndarray>
- standard_name :
- mass_fraction_of_cloud_ice_in_air
- long_name :
- Mass Fraction of Cloud Ice
- comment :
- Includes both large-scale and convective cloud. This is calculated as the mass of cloud ice in the grid cell divided by the mass of air (including the water in all phases) in the grid cell. It includes precipitating hydrometeors ONLY if the precipitating hydrometeors affect the calculation of radiative transfer in model.
- units :
- 1
- original_name :
- iwcon
- original_units :
- kg/kg
- history :
- 2012-01-16T00:17:35Z altered by CMOR: Converted units from 'kg/kg' to '1'. 2012-01-16T00:17:35Z altered by CMOR: replaced missing value flag (9.96921e+36) with standard missing value (1e+20). 2012-01-16T00:17:53Z altered by CMOR: Inverted axis: lat.
- cell_methods :
- time: mean (interval: 30 minutes)
- cell_measures :
- area: areacella
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_IPSL-CM5A-MR_abrupt4xCO2_r0i0p0.nc areacella: areacella_fx_IPSL-CM5A-MR_abrupt4xCO2_r0i0p0.nc
Array Chunk Bytes 5.40 GB 1.93 GB Shape (1680, 39, 143, 144) (600, 39, 143, 144) Count 9 Tasks 3 Chunks Type float32 numpy.ndarray
- institution :
- IPSL (Institut Pierre Simon Laplace, Paris, France)
- institute_id :
- IPSL
- experiment_id :
- abrupt4xCO2
- source :
- IPSL-CM5A-MR (2010) : atmos : LMDZ4 (LMDZ4_v5, 144x143x39); ocean : ORCA2 (NEMOV2_3, 2x2L31); seaIce : LIM2 (NEMOV2_3); ocnBgchem : PISCES (NEMOV2_3); land : ORCHIDEE (orchidee_1_9_4_AR5)
- model_id :
- IPSL-CM5A-MR
- forcing :
- GHG
- parent_experiment_id :
- piControl
- parent_experiment_rip :
- r1i1p1
- branch_time :
- 1850.0
- contact :
- ipsl-cmip5 _at_ ipsl.jussieu.fr Data manager : Sebastien Denvil
- comment :
- This abrupt4xCO2 simulation was initiated from a preindustrial control simulation when equilibrium was reached.
- references :
- Model documentation and further reference available here : http://icmc.ipsl.fr
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- 769a5f23-5b36-42b5-8b8a-668081862d49
- product :
- output
- experiment :
- abrupt 4XCO2
- frequency :
- mon
- creation_date :
- 2012-01-16T00:17:53Z
- history :
- 2012-01-16T00:17:53Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table Amon (31 January 2011) 53b766a395ac41696af40aab76a49ae5
- title :
- IPSL-CM5A-MR model output prepared for CMIP5 abrupt 4XCO2
- parent_experiment :
- pre-industrial control
- modeling_realm :
- atmos
- realization :
- 1
- cmor_version :
- 2.7.1
