NorESM1-ME 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/cli_Amon_NorESM1-ME_rcp85_r1i1p1.yaml")
ds=cat.netcdf.read()
Metadata
title | NorESM1-ME model output prepared for CMIP5 RCP8.5 |
location | /shared/cmip5/data/rcp85/atmos/mon/Amon/cli/NCC.NorESM1-ME/r1i1p1 |
tags | gridded,global,model,monthly |
catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/cli_Amon_NorESM1-ME_rcp85_r1i1p1.yaml |
last updated | 2013-05-28 |
Dataset Contents
<xarray.Dataset> Dimensions: (bnds: 2, lat: 142, lev: 26, lon: 144, time: 1140) Coordinates: * lat (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 88.11 90.0 90.0 * time (time) float64 15.5 45.0 74.5 ... 2.036e+04 2.039e+04 2.042e+04 * lev (lev) float64 0.9926 0.9706 0.9296 ... 0.01397 0.007389 0.003545 * 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=(468, 2), meta=np.ndarray> lev_bnds (time, lev, bnds) float64 dask.array<chunksize=(468, 26, 2), meta=np.ndarray> p0 (time) float32 100000.0 100000.0 100000.0 ... 100000.0 100000.0 a (time, lev) float64 dask.array<chunksize=(468, 26), meta=np.ndarray> b (time, lev) float64 dask.array<chunksize=(468, 26), meta=np.ndarray> ps (time, lat, lon) float32 dask.array<chunksize=(468, 142, 144), meta=np.ndarray> a_bnds (time, lev, bnds) float64 dask.array<chunksize=(468, 26, 2), meta=np.ndarray> b_bnds (time, lev, bnds) float64 dask.array<chunksize=(468, 26, 2), meta=np.ndarray> lat_bnds (time, lat, bnds) float64 dask.array<chunksize=(468, 142, 2), meta=np.ndarray> lon_bnds (time, lon, bnds) float64 dask.array<chunksize=(468, 144, 2), meta=np.ndarray> cli (time, lev, lat, lon) float32 dask.array<chunksize=(468, 26, 142, 144), meta=np.ndarray> Attributes: institution: Norwegian Climate Centre institute_id: NCC experiment_id: rcp85 source: NorESM1-ME 2011 atmosphere: CAM-Oslo (CAM4-Oslo-... model_id: NorESM1-ME forcing: GHG, SA, Oz, Sl, BC, OC parent_experiment_id: historical parent_experiment_rip: r1i1p1 branch_time: 56940.0 contact: Please send any requests or bug reports to noresm... initialization_method: 1 physics_version: 1 tracking_id: 77230c79-59a1-41da-920a-d05b7d1fede7 product: output experiment: RCP8.5 frequency: mon creation_date: 2012-06-13T07:53:42Z history: 2012-06-13T07:53:42Z CMOR rewrote data to comply ... Conventions: CF-1.4 project_id: CMIP5 table_id: Table Amon (01 February 2012) 81f919710c21dca8a17... title: NorESM1-ME model output prepared for CMIP5 RCP8.5 parent_experiment: historical modeling_realm: atmos realization: 1 cmor_version: 2.7.1
xarray.Dataset
- bnds: 2
- lat: 142
- lev: 26
- lon: 144
- time: 1140
- lat(lat)float64-90.0 -88.11 -86.21 ... 90.0 90.0
- bounds :
- lat_bnds
- units :
- degrees_north
- axis :
- Y
- long_name :
- latitude
- standard_name :
- latitude
array([-90. , -88.105263, -86.210526, -84.315789, -82.421053, -80.526316, -78.631579, -76.736842, -74.842105, -72.947368, -71.052632, -69.157895, -67.263158, -65.368421, -63.473684, -61.578947, -59.684211, -57.789474, -55.894737, -54. , -52.105263, -50.210526, -48.315789, -46.421053, -44.526316, -42.631579, -40.736842, -38.842105, -36.947368, -35.052632, -33.157895, -31.263158, -31.263158, -29.368421, -27.473684, -27.473684, -25.578947, -23.684211, -21.789474, -21.789474, -19.894737, -19.894737, -18. , -18. , -16.105263, -14.210526, -14.210526, -12.315789, -12.315789, -10.421053, -10.421053, -8.526316, -8.526316, -6.631579, -6.631579, -4.736842, -4.736842, -2.842105, -2.842105, -0.947368, -0.947368, 0.947368, 0.947368, 2.842105, 2.842105, 4.736842, 4.736842, 6.631579, 6.631579, 8.526316, 8.526316, 10.421053, 10.421053, 12.315789, 14.210526, 14.210526, 16.105263, 16.105263, 18. , 18. , 19.894737, 19.894737, 21.789474, 23.684211, 23.684211, 25.578947, 25.578947, 27.473684, 27.473684, 29.368421, 29.368421, 31.263158, 33.157895, 35.052632, 35.052632, 36.947368, 36.947368, 38.842105, 40.736842, 42.631579, 44.526316, 44.526316, 46.421053, 46.421053, 48.315789, 48.315789, 50.210526, 50.210526, 52.105263, 52.105263, 54. , 54. , 55.894737, 55.894737, 57.789474, 59.684211, 61.578947, 63.473684, 63.473684, 65.368421, 65.368421, 67.263158, 67.263158, 69.157895, 69.157895, 71.052632, 71.052632, 72.947368, 72.947368, 74.842105, 76.736842, 78.631579, 80.526316, 82.421053, 84.315789, 84.315789, 86.210526, 86.210526, 88.105263, 88.105263, 90. , 90. ])
- time(time)float6415.5 45.0 ... 2.039e+04 2.042e+04
- bounds :
- time_bnds
- calendar :
- noleap
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([1.55000e+01, 4.50000e+01, 7.45000e+01, ..., 2.03635e+04, 2.03940e+04, 2.04245e+04])
- lev(lev)float640.9926 0.9706 ... 0.007389 0.003545
- 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([0.992556, 0.970555, 0.929649, 0.867161, 0.787702, 0.696796, 0.600524, 0.510455, 0.433895, 0.368818, 0.313501, 0.266481, 0.226513, 0.19254 , 0.163662, 0.139115, 0.11825 , 0.100515, 0.085439, 0.070059, 0.053115, 0.03723 , 0.023945, 0.013967, 0.007389, 0.003545])
- 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=(468, 2), meta=np.ndarray>
Array Chunk Bytes 18.24 kB 10.75 kB Shape (1140, 2) (672, 2) Count 6 Tasks 2 Chunks Type float64 numpy.ndarray - lev_bnds(time, lev, bnds)float64dask.array<chunksize=(468, 26, 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 474.24 kB 279.55 kB Shape (1140, 26, 2) (672, 26, 2) Count 8 Tasks 2 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=(468, 26), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: a(k)
Array Chunk Bytes 237.12 kB 139.78 kB Shape (1140, 26) (672, 26) Count 8 Tasks 2 Chunks Type float64 numpy.ndarray - b(time, lev)float64dask.array<chunksize=(468, 26), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: b(k)
Array Chunk Bytes 237.12 kB 139.78 kB Shape (1140, 26) (672, 26) Count 8 Tasks 2 Chunks Type float64 numpy.ndarray - ps(time, lat, lon)float32dask.array<chunksize=(468, 142, 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 93.24 MB 54.96 MB Shape (1140, 142, 144) (672, 142, 144) Count 26 Tasks 2 Chunks Type float32 numpy.ndarray - a_bnds(time, lev, bnds)float64dask.array<chunksize=(468, 26, 2), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: a(k+1/2)
Array Chunk Bytes 474.24 kB 279.55 kB Shape (1140, 26, 2) (672, 26, 2) Count 8 Tasks 2 Chunks Type float64 numpy.ndarray - b_bnds(time, lev, bnds)float64dask.array<chunksize=(468, 26, 2), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: b(k+1/2)
Array Chunk Bytes 474.24 kB 279.55 kB Shape (1140, 26, 2) (672, 26, 2) Count 8 Tasks 2 Chunks Type float64 numpy.ndarray - lat_bnds(time, lat, bnds)float64dask.array<chunksize=(468, 142, 2), meta=np.ndarray>
Array Chunk Bytes 2.59 MB 1.53 MB Shape (1140, 142, 2) (672, 142, 2) Count 22 Tasks 2 Chunks Type float64 numpy.ndarray - lon_bnds(time, lon, bnds)float64dask.array<chunksize=(468, 144, 2), meta=np.ndarray>
Array Chunk Bytes 2.63 MB 1.55 MB Shape (1140, 144, 2) (672, 144, 2) Count 8 Tasks 2 Chunks Type float64 numpy.ndarray - cli(time, lev, lat, lon)float32dask.array<chunksize=(468, 26, 142, 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 :
- CLDICE
- cell_methods :
- time: mean
- cell_measures :
- area: areacella
- history :
- 2012-06-13T07:53:41Z altered by CMOR: replaced missing value flag (1e+20) with standard missing value (1e+20). 2012-06-13T07:53:42Z altered by CMOR: Converted type from 'd' to 'f'. 2012-06-13T07:53:42Z altered by CMOR: Inverted axis: lev.
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_NorESM1-ME_rcp85_r0i0p0.nc areacella: areacella_fx_NorESM1-ME_rcp85_r0i0p0.nc
Array Chunk Bytes 2.42 GB 1.43 GB Shape (1140, 26, 142, 144) (672, 26, 142, 144) Count 30 Tasks 2 Chunks Type float32 numpy.ndarray
- institution :
- Norwegian Climate Centre
- institute_id :
- NCC
- experiment_id :
- rcp85
- source :
- NorESM1-ME 2011 atmosphere: CAM-Oslo (CAM4-Oslo-noresm-ver1_cmip5-r139, f19L26); ocean: MICOM (MICOM-noresm-ver1_cmip5-r139, gx1v6L53); ocean biogeochemistry: HAMOCC (HAMOCC-noresm-ver1_cmip5-r139, gx1v6L53); sea ice: CICE (CICE4-noresm-ver1_cmip5-r139); land: CLM (CLM4-noresm-ver1_cmip5-r139)
- model_id :
- NorESM1-ME
- forcing :
- GHG, SA, Oz, Sl, BC, OC
- parent_experiment_id :
- historical
- parent_experiment_rip :
- r1i1p1
- branch_time :
- 56940.0
- contact :
- Please send any requests or bug reports to noresm-ncc@met.no.
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- 77230c79-59a1-41da-920a-d05b7d1fede7
- product :
- output
- experiment :
- RCP8.5
- frequency :
- mon
- creation_date :
- 2012-06-13T07:53:42Z
- history :
- 2012-06-13T07:53:42Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table Amon (01 February 2012) 81f919710c21dca8a1753166d5bac090
- title :
- NorESM1-ME model output prepared for CMIP5 RCP8.5
- parent_experiment :
- historical
- modeling_realm :
- atmos
- realization :
- 1
- cmor_version :
- 2.7.1