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/clw_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/clw/NCC.NorESM1-ME/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/clw_Amon_NorESM1-ME_rcp85_r1i1p1.yaml |
| last updated | 2013-06-14 |
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>
clw (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: 647a6a89-f905-4fb8-9c2a-d69a8c77d4ba
product: output
experiment: RCP8.5
frequency: mon
creation_date: 2012-06-13T07:49:02Z
history: 2012-06-13T07:49:02Z 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: 2.7.1xarray.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 - clw(time, lev, lat, lon)float32dask.array<chunksize=(468, 26, 142, 144), 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
- original_name :
- CLDLIQ
- cell_methods :
- time: mean
- cell_measures :
- area: areacella
- history :
- 2012-06-13T07:49:01Z altered by CMOR: replaced missing value flag (1e+20) with standard missing value (1e+20). 2012-06-13T07:49:02Z altered by CMOR: Converted type from 'd' to 'f'. 2012-06-13T07:49:02Z 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 :
- 647a6a89-f905-4fb8-9c2a-d69a8c77d4ba
- product :
- output
- experiment :
- RCP8.5
- frequency :
- mon
- creation_date :
- 2012-06-13T07:49:02Z
- history :
- 2012-06-13T07:49:02Z 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