MIROC5 model output prepared for CMIP5 historical
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_historical_r1i1p1.yaml")
ds=cat.netcdf.read()
Metadata
title | MIROC5 model output prepared for CMIP5 historical |
location | /shared/cmip5/data/historical/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_historical_r1i1p1.yaml |
last updated | 2013-06-14 |
Dataset Contents
<xarray.Dataset> Dimensions: (bnds: 2, rlat: 224, rlon: 256, time: 37595, vertices: 4) Coordinates: * time (time) float64 2.19e+04 2.19e+04 ... 5.949e+04 5.949e+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=(3650, 2), meta=np.ndarray> rlat_bnds (time, rlat, bnds) float64 dask.array<chunksize=(3650, 224, 2), meta=np.ndarray> rlon_bnds (time, rlon, bnds) float64 dask.array<chunksize=(3650, 256, 2), meta=np.ndarray> lat_vertices (time, rlat, rlon, vertices) float32 dask.array<chunksize=(3650, 224, 256, 4), meta=np.ndarray> lon_vertices (time, rlat, rlon, vertices) float32 dask.array<chunksize=(3650, 224, 256, 4), meta=np.ndarray> tos (time, rlat, rlon) float32 dask.array<chunksize=(3650, 224, 256), meta=np.ndarray> Attributes: institution: AORI (Atmosphere and Ocean Research Institute, Th... institute_id: MIROC experiment_id: historical 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: piControl parent_experiment_rip: r1i1p1 branch_time: 150015.0 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: ff1e71de-4b05-4a97-9bab-1232f476b575 product: output experiment: historical frequency: day creation_date: 2011-10-19T11:18:04Z history: 2011-10-19T11:18:04Z CMOR rewrote data to comply ... Conventions: CF-1.4 project_id: CMIP5 table_id: Table day (26 July 2011) f21c16b785432e6bd3f72e80... title: MIROC5 model output prepared for CMIP5 historical parent_experiment: pre-industrial control modeling_realm: ocean realization: 1 cmor_version: 2.7.1
xarray.Dataset
- bnds: 2
- rlat: 224
- rlon: 256
- time: 37595
- vertices: 4
- time(time)float642.19e+04 2.19e+04 ... 5.949e+04
- bounds :
- time_bnds
- units :
- days since 1850-1-1
- calendar :
- noleap
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([21900.5, 21901.5, 21902.5, ..., 59492.5, 59493.5, 59494.5])
- 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=(3650, 2), meta=np.ndarray>
Array Chunk Bytes 601.52 kB 58.40 kB Shape (37595, 2) (3650, 2) Count 33 Tasks 11 Chunks Type float64 numpy.ndarray - rlat_bnds(time, rlat, bnds)float64dask.array<chunksize=(3650, 224, 2), meta=np.ndarray>
Array Chunk Bytes 134.74 MB 13.08 MB Shape (37595, 224, 2) (3650, 224, 2) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - rlon_bnds(time, rlon, bnds)float64dask.array<chunksize=(3650, 256, 2), meta=np.ndarray>
Array Chunk Bytes 153.99 MB 14.95 MB Shape (37595, 256, 2) (3650, 256, 2) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - lat_vertices(time, rlat, rlon, vertices)float32dask.array<chunksize=(3650, 224, 256, 4), meta=np.ndarray>
- units :
- degrees_north
Array Chunk Bytes 34.49 GB 3.35 GB Shape (37595, 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=(3650, 224, 256, 4), meta=np.ndarray>
- units :
- degrees_east
Array Chunk Bytes 34.49 GB 3.35 GB Shape (37595, 224, 256, 4) (3650, 224, 256, 4) Count 44 Tasks 11 Chunks Type float32 numpy.ndarray - tos(time, rlat, rlon)float32dask.array<chunksize=(3650, 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 :
- 2011-10-19T11:18:04Z 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_historical_r0i0p0.nc areacello: areacello_fx_MIROC5_historical_r0i0p0.nc
Array Chunk Bytes 8.62 GB 837.22 MB Shape (37595, 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 :
- historical
- 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 :
- piControl
- parent_experiment_rip :
- r1i1p1
- branch_time :
- 150015.0
- 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 :
- ff1e71de-4b05-4a97-9bab-1232f476b575
- product :
- output
- experiment :
- historical
- frequency :
- day
- creation_date :
- 2011-10-19T11:18:04Z
- history :
- 2011-10-19T11:18:04Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table day (26 July 2011) f21c16b785432e6bd3f72e80f2cade49
- title :
- MIROC5 model output prepared for CMIP5 historical
- parent_experiment :
- pre-industrial control
- modeling_realm :
- ocean
- realization :
- 1
- cmor_version :
- 2.7.1