IPSL-CM5A-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/tos_day_IPSL-CM5A-LR_rcp85_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | IPSL-CM5A-LR model output prepared for CMIP5 RCP8.5 |
| location | /shared/cmip5/data/rcp85/ocean/day/day/tos/IPSL.IPSL-CM5A-LR/r1i1p1 |
| tags | gridded,global,model,daily |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/tos_day_IPSL-CM5A-LR_rcp85_r1i1p1.yaml |
| last updated | 2013-05-31 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, i: 182, j: 149, time: 107675, vertices: 4)
Coordinates:
* time (time) float64 0.5 1.5 2.5 ... 1.077e+05 1.077e+05 1.077e+05
* j (j) int32 1 2 3 4 5 6 7 8 ... 142 143 144 145 146 147 148 149
* i (i) int32 1 2 3 4 5 6 7 8 ... 175 176 177 178 179 180 181 182
lat (j, i) float32 dask.array<chunksize=(149, 182), meta=np.ndarray>
lon (j, i) float32 dask.array<chunksize=(149, 182), meta=np.ndarray>
Dimensions without coordinates: bnds, vertices
Data variables:
time_bnds (time, bnds) float64 dask.array<chunksize=(73000, 2), meta=np.ndarray>
lat_vertices (time, j, i, vertices) float32 dask.array<chunksize=(73000, 149, 182, 4), meta=np.ndarray>
lon_vertices (time, j, i, vertices) float32 dask.array<chunksize=(73000, 149, 182, 4), meta=np.ndarray>
tos (time, j, i) float32 dask.array<chunksize=(73000, 149, 182), meta=np.ndarray>
Attributes:
institution: IPSL (Institut Pierre Simon Laplace, Paris, France)
institute_id: IPSL
experiment_id: rcp85
source: IPSL-CM5A-LR (2010) : atmos : LMDZ4 (LMDZ4_v5, 96...
model_id: IPSL-CM5A-LR
forcing: Nat,Ant,GHG,SA,Oz,LU,SS,Ds,BC,MD,OC,AA
parent_experiment_id: historical
parent_experiment_rip: r1i1p1
branch_time: 2005.0
contact: ipsl-cmip5 _at_ ipsl.jussieu.fr Data manager : Se...
comment: This 21th century simulation has been forced by p...
references: Model documentation and further reference availab...
initialization_method: 1
physics_version: 1
tracking_id: 7707440f-4b8b-4a0f-974c-a88815bd00ff
product: output
experiment: RCP8.5
frequency: day
creation_date: 2011-08-16T22:45:42Z
history: 2011-08-16T22:45:42Z CMOR rewrote data to comply ...
Conventions: CF-1.4
project_id: CMIP5
table_id: Table day (10 February 2011) 80e409bd73611e9d25d0...
title: IPSL-CM5A-LR model output prepared for CMIP5 RCP8.5
parent_experiment: historical
modeling_realm: ocean
realization: 1
cmor_version: 2.7.1xarray.Dataset
- bnds: 2
- i: 182
- j: 149
- time: 107675
- vertices: 4
- time(time)float640.5 1.5 2.5 ... 1.077e+05 1.077e+05
- bounds :
- time_bnds
- units :
- days since 2006-01-01 00:00:00
- calendar :
- noleap
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([5.000000e-01, 1.500000e+00, 2.500000e+00, ..., 1.076725e+05, 1.076735e+05, 1.076745e+05]) - j(j)int321 2 3 4 5 6 ... 145 146 147 148 149
- units :
- 1
- long_name :
- cell index along second dimension
array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149], dtype=int32) - i(i)int321 2 3 4 5 6 ... 178 179 180 181 182
- units :
- 1
- long_name :
- cell index along first dimension
array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182], dtype=int32) - lat(j, i)float32dask.array<chunksize=(149, 182), meta=np.ndarray>
- standard_name :
- latitude
- long_name :
- latitude coordinate
- units :
- degrees_north
- bounds :
- lat_vertices
Array Chunk Bytes 108.47 kB 108.47 kB Shape (149, 182) (149, 182) Count 5 Tasks 1 Chunks Type float32 numpy.ndarray - lon(j, i)float32dask.array<chunksize=(149, 182), meta=np.ndarray>
- standard_name :
- longitude
- long_name :
- longitude coordinate
- units :
- degrees_east
- bounds :
- lon_vertices
Array Chunk Bytes 108.47 kB 108.47 kB Shape (149, 182) (149, 182) Count 5 Tasks 1 Chunks Type float32 numpy.ndarray
- time_bnds(time, bnds)float64dask.array<chunksize=(73000, 2), meta=np.ndarray>
Array Chunk Bytes 1.72 MB 1.17 MB Shape (107675, 2) (73000, 2) Count 6 Tasks 2 Chunks Type float64 numpy.ndarray - lat_vertices(time, j, i, vertices)float32dask.array<chunksize=(73000, 149, 182, 4), meta=np.ndarray>
- units :
- degrees_north
Array Chunk Bytes 46.72 GB 31.67 GB Shape (107675, 149, 182, 4) (73000, 149, 182, 4) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray - lon_vertices(time, j, i, vertices)float32dask.array<chunksize=(73000, 149, 182, 4), meta=np.ndarray>
- units :
- degrees_east
Array Chunk Bytes 46.72 GB 31.67 GB Shape (107675, 149, 182, 4) (73000, 149, 182, 4) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray - tos(time, j, i)float32dask.array<chunksize=(73000, 149, 182), meta=np.ndarray>
- standard_name :
- surface_temperature
- long_name :
- Sea Surface Temperature
- comment :
- temperature of liquid ocean.
- units :
- K
- original_name :
- sosstsst
- original_units :
- degC
- history :
- 2011-08-16T22:44:51Z altered by CMOR: Converted units from 'degC' to 'K'. 2011-08-16T22:44:51Z altered by CMOR: replaced missing value flag (9.96921e+36) with standard missing value (1e+20).
- cell_methods :
- time: mean (interval: 30 minutes)
- cell_measures :
- area: areacello
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_ocean_fx_IPSL-CM5A-LR_rcp85_r0i0p0.nc areacello: areacello_fx_IPSL-CM5A-LR_rcp85_r0i0p0.nc
Array Chunk Bytes 11.68 GB 7.92 GB Shape (107675, 149, 182) (73000, 149, 182) Count 6 Tasks 2 Chunks Type float32 numpy.ndarray
- institution :
- IPSL (Institut Pierre Simon Laplace, Paris, France)
- institute_id :
- IPSL
- experiment_id :
- rcp85
- source :
- IPSL-CM5A-LR (2010) : atmos : LMDZ4 (LMDZ4_v5, 96x95x39); ocean : ORCA2 (NEMOV2_3, 2x2L31); seaIce : LIM2 (NEMOV2_3); ocnBgchem : PISCES (NEMOV2_3); land : ORCHIDEE (orchidee_1_9_4_AR5)
- model_id :
- IPSL-CM5A-LR
- forcing :
- Nat,Ant,GHG,SA,Oz,LU,SS,Ds,BC,MD,OC,AA
- parent_experiment_id :
- historical
- parent_experiment_rip :
- r1i1p1
- branch_time :
- 2005.0
- contact :
- ipsl-cmip5 _at_ ipsl.jussieu.fr Data manager : Sebastien Denvil
- comment :
- This 21th century simulation has been forced by prescribed concentration following the rcp 8.5 scenario.
- references :
- Model documentation and further reference available here : http://icmc.ipsl.fr
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- 7707440f-4b8b-4a0f-974c-a88815bd00ff
- product :
- output
- experiment :
- RCP8.5
- frequency :
- day
- creation_date :
- 2011-08-16T22:45:42Z
- history :
- 2011-08-16T22:45:42Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table day (10 February 2011) 80e409bd73611e9d25d049ad2059c310
- title :
- IPSL-CM5A-LR model output prepared for CMIP5 RCP8.5
- parent_experiment :
- historical
- modeling_realm :
- ocean
- realization :
- 1
- cmor_version :
- 2.7.1