MRI-CGCM3 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/vo_Omon_MRI-CGCM3_piControl_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | MRI-CGCM3 model output prepared for CMIP5 pre-industrial control |
| location | /shared/cmip5/data/piControl/ocean/mon/Omon/vo/MRI.MRI-CGCM3/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/vo_Omon_MRI-CGCM3_piControl_r1i1p1.yaml |
| last updated | 2013-06-14 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, lev: 51, rlat: 368, rlon: 360, time: 6000, vertices: 4)
Coordinates:
* time (time) float64 15.5 45.0 74.5 ... 1.826e+05 1.826e+05
* lev (lev) float64 2.0 6.5 12.25 19.25 ... 5.4e+03 6e+03 6.325e+03
* rlat (rlat) float64 -78.25 -77.75 -77.25 ... 154.6 155.7 156.8
* rlon (rlon) float64 0.5 1.5 2.5 3.5 4.5 ... 356.5 357.5 358.5 359.5
lat (rlat, rlon) float32 dask.array<chunksize=(368, 360), meta=np.ndarray>
lon (rlat, rlon) float32 dask.array<chunksize=(368, 360), meta=np.ndarray>
Dimensions without coordinates: bnds, vertices
Data variables:
time_bnds (time, bnds) float64 dask.array<chunksize=(60, 2), meta=np.ndarray>
lev_bnds (time, lev, bnds) float64 dask.array<chunksize=(60, 51, 2), meta=np.ndarray>
lat_vertices (time, rlat, rlon, vertices) float32 dask.array<chunksize=(60, 368, 360, 4), meta=np.ndarray>
lon_vertices (time, rlat, rlon, vertices) float32 dask.array<chunksize=(60, 368, 360, 4), meta=np.ndarray>
vo (time, lev, rlat, rlon) float32 dask.array<chunksize=(60, 51, 368, 360), meta=np.ndarray>
Attributes:
institution: MRI (Meteorological Research Institute, Tsukuba, ...
institute_id: MRI
experiment_id: piControl
source: MRI-CGCM3 2011 atmosphere: GSMUV (gsmuv-101124, T...
model_id: MRI-CGCM3
forcing: N/A
parent_experiment_id: N/A
parent_experiment_rip: N/A
branch_time: 0.0
contact: Seiji Yukimoto (yukimoto@mri-jma.go.jp)
history: Output from /home/cmip5/oc/cgcm3_scup-101122/run-...
comment: The lowest layer is a bottom boundary layer (thic...
references: Model described by Yukimoto et al. (Technical Rep...
initialization_method: 1
physics_version: 1
tracking_id: d08866ed-3bc7-4ec7-a09c-9793e2ad9939
product: output
experiment: pre-industrial control
frequency: mon
creation_date: 2011-08-25T16:56:00Z
Conventions: CF-1.4
project_id: CMIP5
table_id: Table Omon (26 July 2011) 25bb94a0408beca44c0f5b6...
title: MRI-CGCM3 model output prepared for CMIP5 pre-ind...
parent_experiment: N/A
modeling_realm: ocean
realization: 1
cmor_version: 2.7.1xarray.Dataset
- bnds: 2
- lev: 51
- rlat: 368
- rlon: 360
- time: 6000
- vertices: 4
- time(time)float6415.5 45.0 ... 1.826e+05 1.826e+05
- bounds :
- time_bnds
- units :
- days since 1851-01-01
- calendar :
- standard
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([1.550000e+01, 4.500000e+01, 7.450000e+01, ..., 1.825445e+05, 1.825750e+05, 1.826055e+05]) - lev(lev)float642.0 6.5 12.25 ... 6e+03 6.325e+03
- bounds :
- lev_bnds
- units :
- m
- axis :
- Z
- positive :
- down
- long_name :
- ocean depth coordinate
- standard_name :
- depth
array([2.0000e+00, 6.5000e+00, 1.2250e+01, 1.9250e+01, 2.7500e+01, 3.7750e+01, 5.0500e+01, 6.5500e+01, 8.2250e+01, 1.0000e+02, 1.1825e+02, 1.3750e+02, 1.5775e+02, 1.7850e+02, 2.0000e+02, 2.2250e+02, 2.4600e+02, 2.7150e+02, 3.0000e+02, 3.3000e+02, 3.6250e+02, 4.0000e+02, 4.4000e+02, 4.8500e+02, 5.4000e+02, 6.0250e+02, 6.7000e+02, 7.4250e+02, 8.2000e+02, 9.0500e+02, 1.0000e+03, 1.1000e+03, 1.2125e+03, 1.3500e+03, 1.5000e+03, 1.6500e+03, 1.8125e+03, 2.0125e+03, 2.2500e+03, 2.5000e+03, 2.7500e+03, 3.0125e+03, 3.3000e+03, 3.6000e+03, 3.9000e+03, 4.2000e+03, 4.5000e+03, 4.8750e+03, 5.4000e+03, 6.0000e+03, 6.3250e+03]) - rlat(rlat)float64-78.25 -77.75 ... 155.7 156.8
- units :
- degrees
- axis :
- Y
- long_name :
- latitude in rotated pole grid
- standard_name :
- grid_latitude
array([-78.25 , -77.75 , -77.25 , ..., 154.5625, 155.6875, 156.8125])
- rlon(rlon)float640.5 1.5 2.5 ... 357.5 358.5 359.5
- units :
- degrees
- axis :
- X
- long_name :
- longitude in rotated pole grid
- standard_name :
- grid_longitude
array([ 0.5, 1.5, 2.5, ..., 357.5, 358.5, 359.5])
- lat(rlat, rlon)float32dask.array<chunksize=(368, 360), meta=np.ndarray>
- standard_name :
- latitude
- long_name :
- latitude coordinate
- units :
- degrees_north
- bounds :
- lat_vertices
Array Chunk Bytes 529.92 kB 529.92 kB Shape (368, 360) (368, 360) Count 495 Tasks 1 Chunks Type float32 numpy.ndarray - lon(rlat, rlon)float32dask.array<chunksize=(368, 360), meta=np.ndarray>
- standard_name :
- longitude
- long_name :
- longitude coordinate
- units :
- degrees_east
- bounds :
- lon_vertices
Array Chunk Bytes 529.92 kB 529.92 kB Shape (368, 360) (368, 360) Count 495 Tasks 1 Chunks Type float32 numpy.ndarray
- time_bnds(time, bnds)float64dask.array<chunksize=(60, 2), meta=np.ndarray>
Array Chunk Bytes 96.00 kB 960 B Shape (6000, 2) (60, 2) Count 300 Tasks 100 Chunks Type float64 numpy.ndarray - lev_bnds(time, lev, bnds)float64dask.array<chunksize=(60, 51, 2), meta=np.ndarray>
Array Chunk Bytes 4.90 MB 48.96 kB Shape (6000, 51, 2) (60, 51, 2) Count 400 Tasks 100 Chunks Type float64 numpy.ndarray - lat_vertices(time, rlat, rlon, vertices)float32dask.array<chunksize=(60, 368, 360, 4), meta=np.ndarray>
- units :
- degrees_north
Array Chunk Bytes 12.72 GB 127.18 MB Shape (6000, 368, 360, 4) (60, 368, 360, 4) Count 400 Tasks 100 Chunks Type float32 numpy.ndarray - lon_vertices(time, rlat, rlon, vertices)float32dask.array<chunksize=(60, 368, 360, 4), meta=np.ndarray>
- units :
- degrees_east
Array Chunk Bytes 12.72 GB 127.18 MB Shape (6000, 368, 360, 4) (60, 368, 360, 4) Count 400 Tasks 100 Chunks Type float32 numpy.ndarray - vo(time, lev, rlat, rlon)float32dask.array<chunksize=(60, 51, 368, 360), meta=np.ndarray>
- standard_name :
- sea_water_y_velocity
- long_name :
- Sea Water Y Velocity
- units :
- m s-1
- original_name :
- vo
- cell_methods :
- time: mean (interval: 20 minutes)
- history :
- 2011-08-25T16:55:59Z altered by CMOR: replaced missing value flag (-9.99e+33) with standard missing value (1e+20).
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_ocean_fx_MRI-CGCM3_piControl_r0i0p0.nc
Array Chunk Bytes 162.16 GB 1.62 GB Shape (6000, 51, 368, 360) (60, 51, 368, 360) Count 300 Tasks 100 Chunks Type float32 numpy.ndarray
- institution :
- MRI (Meteorological Research Institute, Tsukuba, Japan)
- institute_id :
- MRI
- experiment_id :
- piControl
- source :
- MRI-CGCM3 2011 atmosphere: GSMUV (gsmuv-101124, TL159L48); ocean: MRI.COM3 (MRICOM-3_0-20101116, 1x0.5L51); sea ice: MRI.COM3; land: HAL (HAL_cmip5_v0.31_01); aerosol: MASINGAR-mk2 (masingar_mk2-20101111, TL95L48)
- model_id :
- MRI-CGCM3
- forcing :
- N/A
- parent_experiment_id :
- N/A
- parent_experiment_rip :
- N/A
- branch_time :
- 0.0
- contact :
- Seiji Yukimoto (yukimoto@mri-jma.go.jp)
- history :
- Output from /home/cmip5/oc/cgcm3_scup-101122/run-C_piControl02/grads/cmip5_vo.ctl 2011-08-25T16:56:00Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- comment :
- The lowest layer is a bottom boundary layer (thickness: 50 m).
- references :
- Model described by Yukimoto et al. (Technical Report of the Meteorological Research Institute, 2011, 64, 83pp.)
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- d08866ed-3bc7-4ec7-a09c-9793e2ad9939
- product :
- output
- experiment :
- pre-industrial control
- frequency :
- mon
- creation_date :
- 2011-08-25T16:56:00Z
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table Omon (26 July 2011) 25bb94a0408beca44c0f5b601258a94e
- title :
- MRI-CGCM3 model output prepared for CMIP5 pre-industrial control
- parent_experiment :
- N/A
- modeling_realm :
- ocean
- realization :
- 1
- cmor_version :
- 2.7.1