CMCC-CMS model output prepared for CMIP5 pre-industrial control
Load in Python
from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/wfo_Omon_CMCC-CMS_piControl_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | CMCC-CMS model output prepared for CMIP5 pre-industrial control |
| location | /shared/cmip5/data/piControl/ocean/mon/Omon/wfo/CMCC.CMCC-CMS/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/wfo_Omon_CMCC-CMS_piControl_r1i1p1.yaml |
| last updated | 2015-01-16 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, i: 182, j: 149, time: 6000, vertices: 4)
Coordinates:
* time (time) float64 15.5 45.5 75.5 ... 3.606e+03 3.636e+03
* 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=(120, 2), meta=np.ndarray>
lat_vertices (time, j, i, vertices) float32 dask.array<chunksize=(120, 149, 182, 4), meta=np.ndarray>
lon_vertices (time, j, i, vertices) float32 dask.array<chunksize=(120, 149, 182, 4), meta=np.ndarray>
wfo (time, j, i) float32 dask.array<chunksize=(120, 149, 182), meta=np.ndarray>
Attributes:
institution: CMCC - Centro Euro-Mediterraneo per i Cambiamenti...
institute_id: CMCC
experiment_id: piControl
source: CMCC-CMS
model_id: CMCC-CMS
forcing: Nat,GHG,Oz,Sl
parent_experiment_id: N/A
parent_experiment_rip: N/A
branch_time: 0.0
contact: Chiara Cagnazzo (chiara.cagnazzo@cmcc.it)
history: Model output postprocessed with Afterburner and C...
comment: Equilibrium reached after more than 1500-year spi...
references: model described in the documentation at http://ww...
initialization_method: 1
physics_version: 1
tracking_id: 9a1a5345-79fd-443f-8c75-82bb9269834e
product: output
experiment: pre-industrial control
frequency: mon
creation_date: 2012-01-20T05:28:10Z
Conventions: CF-1.4
project_id: CMIP5
table_id: Table Omon (27 April 2011) 340eddd4fd838d90fa9ffe...
title: CMCC-CMS model output prepared for CMIP5 pre-indu...
parent_experiment: N/A
modeling_realm: ocean
realization: 1
cmor_version: 2.7.1xarray.Dataset
- bnds: 2
- i: 182
- j: 149
- time: 6000
- vertices: 4
- time(time)float6415.5 45.5 ... 3.606e+03 3.636e+03
- bounds :
- time_bnds
- calendar :
- standard
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([ 15.5, 45.5, 75.5, ..., 3575.5, 3606. , 3636.5])
- 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 245 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 245 Tasks 1 Chunks Type float32 numpy.ndarray
- time_bnds(time, bnds)float64dask.array<chunksize=(120, 2), meta=np.ndarray>
Array Chunk Bytes 96.00 kB 1.92 kB Shape (6000, 2) (120, 2) Count 150 Tasks 50 Chunks Type float64 numpy.ndarray - lat_vertices(time, j, i, vertices)float32dask.array<chunksize=(120, 149, 182, 4), meta=np.ndarray>
- units :
- degrees_north
Array Chunk Bytes 2.60 GB 52.07 MB Shape (6000, 149, 182, 4) (120, 149, 182, 4) Count 200 Tasks 50 Chunks Type float32 numpy.ndarray - lon_vertices(time, j, i, vertices)float32dask.array<chunksize=(120, 149, 182, 4), meta=np.ndarray>
- units :
- degrees_east
Array Chunk Bytes 2.60 GB 52.07 MB Shape (6000, 149, 182, 4) (120, 149, 182, 4) Count 200 Tasks 50 Chunks Type float32 numpy.ndarray - wfo(time, j, i)float32dask.array<chunksize=(120, 149, 182), meta=np.ndarray>
- standard_name :
- water_flux_into_sea_water
- long_name :
- Water Flux into Sea Water
- comment :
- computed as the water flux into the ocean divided by the area of the ocean portion of the grid cell. This is the sum of the next two variables in this table.
- units :
- kg m-2 s-1
- original_name :
- sowaflup
- cell_methods :
- time: mean (interval: 1 month) area: mean where sea
- cell_measures :
- area: areacello
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_ocean_fx_CMCC-CMS_piControl_r0i0p0.nc areacello: areacello_fx_CMCC-CMS_piControl_r0i0p0.nc
Array Chunk Bytes 650.83 MB 13.02 MB Shape (6000, 149, 182) (120, 149, 182) Count 150 Tasks 50 Chunks Type float32 numpy.ndarray
- institution :
- CMCC - Centro Euro-Mediterraneo per i Cambiamenti Climatici, Bologna, Italy
- institute_id :
- CMCC
- experiment_id :
- piControl
- source :
- CMCC-CMS
- model_id :
- CMCC-CMS
- forcing :
- Nat,GHG,Oz,Sl
- parent_experiment_id :
- N/A
- parent_experiment_rip :
- N/A
- branch_time :
- 0.0
- contact :
- Chiara Cagnazzo (chiara.cagnazzo@cmcc.it)
- history :
- Model output postprocessed with Afterburner and CDO (https://code.zmaw.de/projects) 2012-01-20T05:28:10Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- comment :
- Equilibrium reached after more than 1500-year spin-up at pre-industrial GHG concentrations after which data were output with nominal date of January 3684
- references :
- model described in the documentation at http://www.cmcc.it/data-models/models
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- 9a1a5345-79fd-443f-8c75-82bb9269834e
- product :
- output
- experiment :
- pre-industrial control
- frequency :
- mon
- creation_date :
- 2012-01-20T05:28:10Z
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table Omon (27 April 2011) 340eddd4fd838d90fa9ffe1345ecbd73
- title :
- CMCC-CMS model output prepared for CMIP5 pre-industrial control
- parent_experiment :
- N/A
- modeling_realm :
- ocean
- realization :
- 1
- cmor_version :
- 2.7.1