MIROC5 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/tauuo_Omon_MIROC5_piControl_r1i1p1.yaml")
ds=cat.netcdf.read()
Metadata
title | MIROC5 model output prepared for CMIP5 pre-industrial control |
location | /shared/cmip5/data/piControl/ocean/mon/Omon/tauuo/MIROC.MIROC5/r1i1p1 |
tags | gridded,global,model,monthly |
catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/tauuo_Omon_MIROC5_piControl_r1i1p1.yaml |
last updated | 2015-01-20 |
Dataset Contents
<xarray.Dataset> Dimensions: (bnds: 2, rlat: 224, rlon: 256, time: 8040, vertices: 4) Coordinates: * time (time) float64 15.5 45.0 74.5 ... 2.445e+05 2.445e+05 * rlat (rlat) float64 -86.16 -85.66 -85.16 ... 85.66 86.16 90.0 * rlon (rlon) float64 0.0 1.406 2.812 4.219 ... 355.8 357.2 358.6 lat (rlat, rlon) float32 dask.array<chunksize=(224, 256), meta=np.ndarray> lon (rlat, rlon) float32 dask.array<chunksize=(224, 256), meta=np.ndarray> Dimensions without coordinates: bnds, vertices Data variables: time_bnds (time, bnds) float64 dask.array<chunksize=(1200, 2), meta=np.ndarray> rlat_bnds (time, rlat, bnds) float64 dask.array<chunksize=(1200, 224, 2), meta=np.ndarray> rlon_bnds (time, rlon, bnds) float64 dask.array<chunksize=(1200, 256, 2), meta=np.ndarray> lat_vertices (time, rlat, rlon, vertices) float32 dask.array<chunksize=(1200, 224, 256, 4), meta=np.ndarray> lon_vertices (time, rlat, rlon, vertices) float32 dask.array<chunksize=(1200, 224, 256, 4), meta=np.ndarray> tauuo (time, rlat, rlon) float32 dask.array<chunksize=(1200, 224, 256), meta=np.ndarray> Attributes: institution: AORI (Atmosphere and Ocean Research Institute, Th... institute_id: MIROC experiment_id: piControl source: MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce... model_id: MIROC5 forcing: N/A parent_experiment_id: N/A parent_experiment_rip: N/A branch_time: 0.0 contact: Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seit... references: Watanabe et al., 2010: Improved climate simulatio... initialization_method: 1 physics_version: 1 tracking_id: f440bf19-7af1-481d-8c43-3ba195bb86b6 product: output experiment: pre-industrial control frequency: mon creation_date: 2011-09-15T07:20:57Z history: 2011-09-15T07:20:57Z CMOR rewrote data to comply ... Conventions: CF-1.4 project_id: CMIP5 table_id: Table Omon (26 July 2011) 25bb94a0408beca44c0f5b6... title: MIROC5 model output prepared for CMIP5 pre-indust... parent_experiment: N/A modeling_realm: ocean realization: 1 cmor_version: 2.7.1
xarray.Dataset
- bnds: 2
- rlat: 224
- rlon: 256
- time: 8040
- vertices: 4
- time(time)float6415.5 45.0 ... 2.445e+05 2.445e+05
- bounds :
- time_bnds
- units :
- days since 2000-1-1
- calendar :
- noleap
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([1.550000e+01, 4.500000e+01, 7.450000e+01, ..., 2.444735e+05, 2.445040e+05, 2.445345e+05])
- rlat(rlat)float64-86.16 -85.66 -85.16 ... 86.16 90.0
- bounds :
- rlat_bnds
- units :
- degrees
- axis :
- Y
- long_name :
- latitude in rotated pole grid
- standard_name :
- grid_latitude
array([-86.162558, -85.662558, -85.162558, ..., 85.662558, 86.162558, 90. ])
- rlon(rlon)float640.0 1.406 2.812 ... 357.2 358.6
- bounds :
- rlon_bnds
- units :
- degrees
- axis :
- X
- long_name :
- longitude in rotated pole grid
- standard_name :
- grid_longitude
array([ 0. , 1.40625, 2.8125 , ..., 355.78125, 357.1875 , 358.59375])
- lat(rlat, rlon)float32dask.array<chunksize=(224, 256), meta=np.ndarray>
- standard_name :
- latitude
- long_name :
- latitude coordinate
- units :
- degrees_north
- bounds :
- lat_vertices
Array Chunk Bytes 229.38 kB 229.38 kB Shape (224, 256) (224, 256) Count 30 Tasks 1 Chunks Type float32 numpy.ndarray - lon(rlat, rlon)float32dask.array<chunksize=(224, 256), meta=np.ndarray>
- standard_name :
- longitude
- long_name :
- longitude coordinate
- units :
- degrees_east
- bounds :
- lon_vertices
Array Chunk Bytes 229.38 kB 229.38 kB Shape (224, 256) (224, 256) Count 30 Tasks 1 Chunks Type float32 numpy.ndarray
- time_bnds(time, bnds)float64dask.array<chunksize=(1200, 2), meta=np.ndarray>
Array Chunk Bytes 128.64 kB 19.20 kB Shape (8040, 2) (1200, 2) Count 21 Tasks 7 Chunks Type float64 numpy.ndarray - rlat_bnds(time, rlat, bnds)float64dask.array<chunksize=(1200, 224, 2), meta=np.ndarray>
Array Chunk Bytes 28.82 MB 4.30 MB Shape (8040, 224, 2) (1200, 224, 2) Count 28 Tasks 7 Chunks Type float64 numpy.ndarray - rlon_bnds(time, rlon, bnds)float64dask.array<chunksize=(1200, 256, 2), meta=np.ndarray>
Array Chunk Bytes 32.93 MB 4.92 MB Shape (8040, 256, 2) (1200, 256, 2) Count 28 Tasks 7 Chunks Type float64 numpy.ndarray - lat_vertices(time, rlat, rlon, vertices)float32dask.array<chunksize=(1200, 224, 256, 4), meta=np.ndarray>
- units :
- degrees_north
Array Chunk Bytes 7.38 GB 1.10 GB Shape (8040, 224, 256, 4) (1200, 224, 256, 4) Count 28 Tasks 7 Chunks Type float32 numpy.ndarray - lon_vertices(time, rlat, rlon, vertices)float32dask.array<chunksize=(1200, 224, 256, 4), meta=np.ndarray>
- units :
- degrees_east
Array Chunk Bytes 7.38 GB 1.10 GB Shape (8040, 224, 256, 4) (1200, 224, 256, 4) Count 28 Tasks 7 Chunks Type float32 numpy.ndarray - tauuo(time, rlat, rlon)float32dask.array<chunksize=(1200, 224, 256), meta=np.ndarray>
- standard_name :
- surface_downward_x_stress
- long_name :
- Surface Downward X Stress
- comment :
- This is the stress on the liquid ocean from overlying atmosphere, sea ice, ice shelf, etc.
- units :
- N m-2
- original_name :
- OTAUX
- cell_methods :
- time: mean area: mean where sea
- history :
- 2011-09-15T07:20:57Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20).
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_ocean_fx_MIROC5_piControl_r0i0p0.nc
Array Chunk Bytes 1.84 GB 275.25 MB Shape (8040, 224, 256) (1200, 224, 256) Count 21 Tasks 7 Chunks Type float32 numpy.ndarray
- institution :
- AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan), NIES (National Institute for Environmental Studies, Ibaraki, Japan), JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan)
- institute_id :
- MIROC
- experiment_id :
- piControl
- source :
- MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); ocean: COCO (COCO4.5, 256x224 L50); sea ice: COCO (COCO4.5); land: MATSIRO (MATSIRO, L6); aerosols: SPRINTARS (SPRINTARS 5.00, T85L40)
- model_id :
- MIROC5
- forcing :
- N/A
- parent_experiment_id :
- N/A
- parent_experiment_rip :
- N/A
- branch_time :
- 0.0
- contact :
- Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seita Emori (emori@nies.go.jp), Masayoshi Ishii (ism@jamstec.go.jp), Masahide Kimoto (kimoto@aori.u-tokyo.ac.jp)
- references :
- Watanabe et al., 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312-6335
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- f440bf19-7af1-481d-8c43-3ba195bb86b6
- product :
- output
- experiment :
- pre-industrial control
- frequency :
- mon
- creation_date :
- 2011-09-15T07:20:57Z
- history :
- 2011-09-15T07:20:57Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table Omon (26 July 2011) 25bb94a0408beca44c0f5b601258a94e
- title :
- MIROC5 model output prepared for CMIP5 pre-industrial control
- parent_experiment :
- N/A
- modeling_realm :
- ocean
- realization :
- 1
- cmor_version :
- 2.7.1