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/sit_OImon_MIROC5_piControl_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | MIROC5 model output prepared for CMIP5 pre-industrial control |
| location | /shared/cmip5/data/piControl/seaIce/mon/OImon/sit/MIROC.MIROC5/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/sit_OImon_MIROC5_piControl_r1i1p1.yaml |
| last updated | 2013-06-14 |
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 -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=(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>
sit (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: 03189437-e18b-4940-a86b-47fb2dd19f6c
product: output
experiment: pre-industrial control
frequency: mon
creation_date: 2011-09-15T07:34:51Z
history: 2011-09-15T07:34:51Z CMOR rewrote data to comply ...
Conventions: CF-1.4
project_id: CMIP5
table_id: Table OImon (26 July 2011) b40ae6f6b2a738f91076c5...
title: MIROC5 model output prepared for CMIP5 pre-indust...
parent_experiment: N/A
modeling_realm: seaIce ocean
realization: 1
cmor_version: 2.7.1xarray.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)float64-88.08 -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 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 - sit(time, rlat, rlon)float32dask.array<chunksize=(1200, 224, 256), meta=np.ndarray>
- standard_name :
- sea_ice_thickness
- long_name :
- Sea Ice Thickness
- comment :
- the mean thickness of sea ice in the ocean portion of the grid cell (averaging over the entire ocean portion, including the ice-free fraction). Reported as 0.0 in regions free of sea ice.
- units :
- m
- original_name :
- HIG
- original_units :
- cm
- history :
- 2011-09-15T07:34:51Z altered by CMOR: Converted units from 'cm' to 'm'. 2011-09-15T07:34:51Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20).
- cell_methods :
- time: mean area: mean where sea
- cell_measures :
- area: areacello
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_seaIce_fx_MIROC5_piControl_r0i0p0.nc areacello: areacello_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 :
- 03189437-e18b-4940-a86b-47fb2dd19f6c
- product :
- output
- experiment :
- pre-industrial control
- frequency :
- mon
- creation_date :
- 2011-09-15T07:34:51Z
- history :
- 2011-09-15T07:34:51Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table OImon (26 July 2011) b40ae6f6b2a738f91076c512dcfee1a5
- title :
- MIROC5 model output prepared for CMIP5 pre-industrial control
- parent_experiment :
- N/A
- modeling_realm :
- seaIce ocean
- realization :
- 1
- cmor_version :
- 2.7.1