MIROC5 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_MIROC5_rcp85_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | MIROC5 model output prepared for CMIP5 RCP8.5 |
| location | /shared/cmip5/data/rcp85/ocean/day/day/tos/MIROC.MIROC5/r1i1p1 |
| tags | gridded,global,model,daily |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/tos_day_MIROC5_rcp85_r1i1p1.yaml |
| last updated | 2013-06-14 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, rlat: 224, rlon: 256, time: 34675, vertices: 4)
Coordinates:
* time (time) float64 5.694e+04 5.694e+04 ... 9.161e+04 9.161e+04
* rlat (rlat) float64 -88.08 -85.91 -85.41 ... 85.41 85.91 88.08
* rlon (rlon) float64 -0.7031 0.7031 2.109 ... 355.1 356.5 357.9
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=(1460, 2), meta=np.ndarray>
rlat_bnds (time, rlat, bnds) float64 dask.array<chunksize=(1460, 224, 2), meta=np.ndarray>
rlon_bnds (time, rlon, bnds) float64 dask.array<chunksize=(1460, 256, 2), meta=np.ndarray>
lat_vertices (time, rlat, rlon, vertices) float32 dask.array<chunksize=(1460, 224, 256, 4), meta=np.ndarray>
lon_vertices (time, rlat, rlon, vertices) float32 dask.array<chunksize=(1460, 224, 256, 4), meta=np.ndarray>
tos (time, rlat, rlon) float32 dask.array<chunksize=(1460, 224, 256), meta=np.ndarray>
Attributes:
institution: AORI (Atmosphere and Ocean Research Institute, Th...
institute_id: MIROC
experiment_id: rcp85
source: MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...
model_id: MIROC5
forcing: GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG ...
parent_experiment_id: historical
parent_experiment_rip: r1i1p1
branch_time: 56940.0
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: e2fd371f-d228-48bd-85d3-52fb8a4d963c
product: output
experiment: RCP8.5
frequency: day
creation_date: 2011-09-27T00:54:50Z
history: 2011-09-27T00:54:50Z CMOR rewrote data to comply ...
Conventions: CF-1.4
project_id: CMIP5
table_id: Table day (27 April 2011) 86d1558d99b6ed1e7a886ab...
title: MIROC5 model output prepared for CMIP5 RCP8.5
parent_experiment: historical
modeling_realm: ocean
realization: 1
cmor_version: 2.7.1xarray.Dataset
- bnds: 2
- rlat: 224
- rlon: 256
- time: 34675
- vertices: 4
- time(time)float645.694e+04 5.694e+04 ... 9.161e+04
- bounds :
- time_bnds
- units :
- days since 1850-1-1
- calendar :
- noleap
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([56940.5, 56941.5, 56942.5, ..., 91612.5, 91613.5, 91614.5])
- rlat(rlat)float64-88.08 -85.91 ... 85.91 88.08
- bounds :
- rlat_bnds
- units :
- degrees
- axis :
- Y
- long_name :
- latitude in rotated pole grid
- standard_name :
- grid_latitude
array([-88.081279, -85.912558, -85.412558, ..., 85.412558, 85.912558, 88.081279]) - rlon(rlon)float64-0.7031 0.7031 ... 356.5 357.9
- bounds :
- rlon_bnds
- units :
- degrees
- axis :
- X
- long_name :
- longitude in rotated pole grid
- standard_name :
- grid_longitude
array([ -0.703125, 0.703125, 2.109375, ..., 355.078125, 356.484375, 357.890625]) - 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 50 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 50 Tasks 1 Chunks Type float32 numpy.ndarray
- time_bnds(time, bnds)float64dask.array<chunksize=(1460, 2), meta=np.ndarray>
Array Chunk Bytes 554.80 kB 58.40 kB Shape (34675, 2) (3650, 2) Count 33 Tasks 11 Chunks Type float64 numpy.ndarray - rlat_bnds(time, rlat, bnds)float64dask.array<chunksize=(1460, 224, 2), meta=np.ndarray>
Array Chunk Bytes 124.28 MB 13.08 MB Shape (34675, 224, 2) (3650, 224, 2) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - rlon_bnds(time, rlon, bnds)float64dask.array<chunksize=(1460, 256, 2), meta=np.ndarray>
Array Chunk Bytes 142.03 MB 14.95 MB Shape (34675, 256, 2) (3650, 256, 2) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - lat_vertices(time, rlat, rlon, vertices)float32dask.array<chunksize=(1460, 224, 256, 4), meta=np.ndarray>
- units :
- degrees_north
Array Chunk Bytes 31.81 GB 3.35 GB Shape (34675, 224, 256, 4) (3650, 224, 256, 4) Count 44 Tasks 11 Chunks Type float32 numpy.ndarray - lon_vertices(time, rlat, rlon, vertices)float32dask.array<chunksize=(1460, 224, 256, 4), meta=np.ndarray>
- units :
- degrees_east
Array Chunk Bytes 31.81 GB 3.35 GB Shape (34675, 224, 256, 4) (3650, 224, 256, 4) Count 44 Tasks 11 Chunks Type float32 numpy.ndarray - tos(time, rlat, rlon)float32dask.array<chunksize=(1460, 224, 256), meta=np.ndarray>
- standard_name :
- surface_temperature
- long_name :
- Sea Surface Temperature
- comment :
- temperature of liquid ocean. Note that the correct standard_name for this variable is ""sea_surface_temperature"", not ""surface_temperature"", but this was discovered too late to correct. To maintain consistency across CMIP5 models, the wrong standard_name will continue to be used.
- units :
- K
- original_name :
- TO
- cell_methods :
- time: mean
- cell_measures :
- area: areacello
- history :
- 2011-09-27T00:54:50Z 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_rcp85_r0i0p0.nc areacello: areacello_fx_MIROC5_rcp85_r0i0p0.nc
Array Chunk Bytes 7.95 GB 837.22 MB Shape (34675, 224, 256) (3650, 224, 256) Count 33 Tasks 11 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 :
- rcp85
- 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 :
- GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG includes CO2, N2O, methane, and fluorocarbons; Oz includes OH and H2O2; LU excludes change in lake fraction)
- parent_experiment_id :
- historical
- parent_experiment_rip :
- r1i1p1
- branch_time :
- 56940.0
- 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 :
- e2fd371f-d228-48bd-85d3-52fb8a4d963c
- product :
- output
- experiment :
- RCP8.5
- frequency :
- day
- creation_date :
- 2011-09-27T00:54:50Z
- history :
- 2011-09-27T00:54:50Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table day (27 April 2011) 86d1558d99b6ed1e7a886ab3fd717b58
- title :
- MIROC5 model output prepared for CMIP5 RCP8.5
- parent_experiment :
- historical
- modeling_realm :
- ocean
- realization :
- 1
- cmor_version :
- 2.7.1