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/snw_LImon_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/landIce/mon/LImon/snw/NCC.NorESM1-ME/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/snw_LImon_NorESM1-ME_rcp85_r1i1p1.yaml |
| last updated | 2013-05-31 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, lat: 96, lon: 144, time: 1140)
Coordinates:
* time (time) float64 15.5 45.0 74.5 ... 2.036e+04 2.039e+04 2.042e+04
* lat (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 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=(468, 2), meta=np.ndarray>
lat_bnds (time, lat, bnds) float64 dask.array<chunksize=(468, 96, 2), meta=np.ndarray>
lon_bnds (time, lon, bnds) float64 dask.array<chunksize=(468, 144, 2), meta=np.ndarray>
snw (time, lat, lon) float32 dask.array<chunksize=(468, 96, 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: 345319c9-8de1-412c-a028-33a377579bae
product: output
experiment: RCP8.5
frequency: mon
creation_date: 2012-06-13T10:51:11Z
history: 2012-06-13T10:51:11Z CMOR rewrote data to comply ...
Conventions: CF-1.4
project_id: CMIP5
table_id: Table LImon (01 February 2012) 98ea837246c3dd3cc4...
title: NorESM1-ME model output prepared for CMIP5 RCP8.5
parent_experiment: historical
modeling_realm: landIce land
realization: 1
cmor_version: 2.7.1xarray.Dataset
- bnds: 2
- lat: 96
- lon: 144
- time: 1140
- 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]) - lat(lat)float64-90.0 -88.11 -86.21 ... 88.11 90.0
- bounds :
- lat_bnds
- units :
- degrees_north
- axis :
- Y
- long_name :
- latitude
- standard_name :
- latitude
array([-90. , -88.105263, -86.210526, -84.315788, -82.421051, -80.526314, -78.631577, -76.736839, -74.842102, -72.947365, -71.052635, -69.157898, -67.263161, -65.368423, -63.473682, -61.578949, -59.684212, -57.789474, -55.894737, -54. , -52.105263, -50.210526, -48.315788, -46.421051, -44.526318, -42.63158 , -40.736843, -38.842106, -36.947369, -35.052631, -33.157894, -31.263159, -29.368422, -27.473684, -25.578947, -23.68421 , -21.789474, -19.894737, -18. , -16.105263, -14.210526, -12.315789, -10.421053, -8.526316, -6.631579, -4.736842, -2.842105, -0.947368, 0.947368, 2.842105, 4.736842, 6.631579, 8.526316, 10.421053, 12.315789, 14.210526, 16.105263, 18. , 19.894737, 21.789474, 23.68421 , 25.578947, 27.473684, 29.368422, 31.263159, 33.157894, 35.052631, 36.947369, 38.842106, 40.736843, 42.63158 , 44.526318, 46.421051, 48.315788, 50.210526, 52.105263, 54. , 55.894737, 57.789474, 59.684212, 61.578949, 63.473682, 65.368423, 67.263161, 69.157898, 71.052635, 72.947365, 74.842102, 76.736839, 78.631577, 80.526314, 82.421051, 84.315788, 86.210526, 88.105263, 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=(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 - lat_bnds(time, lat, bnds)float64dask.array<chunksize=(468, 96, 2), meta=np.ndarray>
Array Chunk Bytes 1.75 MB 1.03 MB Shape (1140, 96, 2) (672, 96, 2) Count 8 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 - snw(time, lat, lon)float32dask.array<chunksize=(468, 96, 144), meta=np.ndarray>
- standard_name :
- surface_snow_amount
- long_name :
- Surface Snow Amount
- comment :
- Computed as the mass of surface snow on the land portion of the grid cell divided by the land area in the grid cell; reported as 0.0 where the land fraction is 0; excluded is snow on vegetation canopy or on sea ice.
- units :
- kg m-2
- original_name :
- SNOWICE+SNOWLIQ
- original_units :
- kg/m2
- history :
- 2012-06-13T10:51:10Z altered by CMOR: Converted units from 'kg/m2' to 'kg m-2'. 2012-06-13T10:51:10Z altered by CMOR: replaced missing value flag (1e+20) with standard missing value (1e+20). 2012-06-13T10:51:11Z altered by CMOR: Converted type from 'd' to 'f'.
- cell_methods :
- time: mean area: mean where land
- cell_measures :
- area: areacella
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_landIce_fx_NorESM1-ME_rcp85_r0i0p0.nc areacella: areacella_fx_NorESM1-ME_rcp85_r0i0p0.nc
Array Chunk Bytes 63.04 MB 37.16 MB Shape (1140, 96, 144) (672, 96, 144) Count 6 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 :
- 345319c9-8de1-412c-a028-33a377579bae
- product :
- output
- experiment :
- RCP8.5
- frequency :
- mon
- creation_date :
- 2012-06-13T10:51:11Z
- history :
- 2012-06-13T10:51:11Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table LImon (01 February 2012) 98ea837246c3dd3cc4918dee0ba63da5
- title :
- NorESM1-ME model output prepared for CMIP5 RCP8.5
- parent_experiment :
- historical
- modeling_realm :
- landIce land
- realization :
- 1
- cmor_version :
- 2.7.1