inmcm4 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/thetao_Omon_inmcm4_piControl_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | inmcm4 model output prepared for CMIP5 pre-industrial control |
| location | /shared/cmip5/data/piControl/ocean/mon/Omon/thetao/INM.inmcm4/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/thetao_Omon_inmcm4_piControl_r1i1p1.yaml |
| last updated | 2013-06-14 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, lev: 40, rlat: 340, rlon: 360, time: 6000, vertices: 4)
Coordinates:
* time (time) float64 15.5 45.0 ... 1.825e+05 1.825e+05
* lev (lev) float64 -0.001043 -0.003128 ... -0.9718
* rlat (rlat) float64 -85.25 -84.75 ... 83.75 84.25
* rlon (rlon) float64 0.5 1.5 2.5 ... 357.5 358.5 359.5
lat (rlat, rlon) float32 dask.array<chunksize=(340, 360), meta=np.ndarray>
lon (rlat, rlon) float32 dask.array<chunksize=(340, 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, 40, 2), meta=np.ndarray>
eta (time, rlat, rlon) float32 dask.array<chunksize=(60, 340, 360), meta=np.ndarray>
depth (time, rlat, rlon) float32 dask.array<chunksize=(60, 340, 360), meta=np.ndarray>
rotated_latitude_longitude (time) int32 -2147483647 ... -2147483647
lat_vertices (time, rlat, rlon, vertices) float32 dask.array<chunksize=(60, 340, 360, 4), meta=np.ndarray>
lon_vertices (time, rlat, rlon, vertices) float32 dask.array<chunksize=(60, 340, 360, 4), meta=np.ndarray>
thetao (time, lev, rlat, rlon) float32 dask.array<chunksize=(60, 40, 340, 360), meta=np.ndarray>
Attributes:
institution: INM (Institute for Numerical Mathematics, Moscow...
institute_id: INM
experiment_id: piControl
source: inmcm4 (2009)
model_id: inmcm4
forcing: N/A
parent_experiment_id: N/A
branch_time: 0.0
contact: Evgeny Volodin, volodin@inm.ras.ru,INM RAS, Gubki...
history: Output from /data5/volodin/PICNTL 2010-06-04T14:2...
comment: no comments
references: Volodin, Diansky, Gusev 2010. Climate model INMCM...
initialization_method: 1
physics_version: 1
tracking_id: b783b6e6-76ac-4cd2-a67d-53388012237e
product: output
experiment: pre-industrial control
frequency: mon
creation_date: 2010-06-04T14:24:54Z
Conventions: CF-1.4
project_id: CMIP5
table_id: Table Omon (12 May 2010) f2afe576fb73a3a11aaa3cc8...
title: inmcm4 model output prepared for CMIP5 pre-indust...
parent_experiment: N/A
modeling_realm: ocean
realization: 1
cmor_version: 2.0.0xarray.Dataset
- bnds: 2
- lev: 40
- rlat: 340
- rlon: 360
- time: 6000
- vertices: 4
- time(time)float6415.5 45.0 ... 1.825e+05 1.825e+05
- bounds :
- time_bnds
- units :
- days since 1850-1-1
- calendar :
- 365_day
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([1.550000e+01, 4.500000e+01, 7.450000e+01, ..., 1.824235e+05, 1.824540e+05, 1.824845e+05]) - lev(lev)float64-0.001043 -0.003128 ... -0.9718
- bounds :
- lev_bnds
- axis :
- Z
- positive :
- up
- long_name :
- ocean sigma coordinate
- standard_name :
- ocean_sigma_coordinate
- formula :
- z(n,k,j,i) = eta(n,j,i) + sigma(k)*(depth(j,i)+eta(n,j,i))
- formula_terms :
- sigma: lev eta: eta depth: depth
array([-0.001043, -0.003128, -0.005423, -0.007987, -0.010894, -0.014213, -0.018009, -0.022346, -0.027286, -0.032891, -0.039222, -0.046343, -0.054316, -0.06321 , -0.073091, -0.084031, -0.096108, -0.1094 , -0.123993, -0.139978, -0.157455, -0.176529, -0.197315, -0.219939, -0.244538, -0.27126 , -0.300268, -0.331743, -0.365882, -0.402902, -0.443044, -0.486573, -0.533783, -0.585001, -0.640591, -0.700955, -0.766545, -0.837864, -0.915472, -0.971824]) - rlat(rlat)float64-85.25 -84.75 ... 83.75 84.25
- units :
- degrees
- axis :
- Y
- long_name :
- latitude in rotated pole grid
- standard_name :
- grid_latitude
array([-85.25, -84.75, -84.25, ..., 83.25, 83.75, 84.25])
- 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=(340, 360), meta=np.ndarray>
- standard_name :
- latitude
- long_name :
- latitude coordinate
- units :
- degrees_north
- bounds :
- lat_vertices
Array Chunk Bytes 489.60 kB 489.60 kB Shape (340, 360) (340, 360) Count 495 Tasks 1 Chunks Type float32 numpy.ndarray - lon(rlat, rlon)float32dask.array<chunksize=(340, 360), meta=np.ndarray>
- standard_name :
- longitude
- long_name :
- longitude coordinate
- units :
- degrees_east
- bounds :
- lon_vertices
Array Chunk Bytes 489.60 kB 489.60 kB Shape (340, 360) (340, 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, 40, 2), meta=np.ndarray>
- formula :
- z(n,k,j,i) = eta(n,j,i) + sigma(k)*(depth(j,i)+eta(n,j,i))
- standard_name :
- ocean_sigma_coordinate
- units :
- formula_terms :
- sigma: lev_bnds eta: eta depth: depth
Array Chunk Bytes 3.84 MB 38.40 kB Shape (6000, 40, 2) (60, 40, 2) Count 400 Tasks 100 Chunks Type float64 numpy.ndarray - eta(time, rlat, rlon)float32dask.array<chunksize=(60, 340, 360), meta=np.ndarray>
- long_name :
- Sea Surface Height
- units :
- m
- cell_methods :
- time: mean
Array Chunk Bytes 2.94 GB 29.38 MB Shape (6000, 340, 360) (60, 340, 360) Count 300 Tasks 100 Chunks Type float32 numpy.ndarray - depth(time, rlat, rlon)float32dask.array<chunksize=(60, 340, 360), meta=np.ndarray>
- long_name :
- Sea Floor Depth
- comment :
- Ocean bathymetry.
- units :
- m
Array Chunk Bytes 2.94 GB 29.38 MB Shape (6000, 340, 360) (60, 340, 360) Count 400 Tasks 100 Chunks Type float32 numpy.ndarray - rotated_latitude_longitude(time)int32-2147483647 ... -2147483647
- grid_mapping_name :
- rotated_latitude_longitude
- grid_north_pole_latitude :
- 70.0
- grid_north_pole_longitude :
- 100.0
- north_pole_grid_longitude :
- -80.0
array([-2147483647, -2147483647, -2147483647, ..., -2147483647, -2147483647, -2147483647], dtype=int32) - lat_vertices(time, rlat, rlon, vertices)float32dask.array<chunksize=(60, 340, 360, 4), meta=np.ndarray>
- units :
- degrees_north
Array Chunk Bytes 11.75 GB 117.50 MB Shape (6000, 340, 360, 4) (60, 340, 360, 4) Count 400 Tasks 100 Chunks Type float32 numpy.ndarray - lon_vertices(time, rlat, rlon, vertices)float32dask.array<chunksize=(60, 340, 360, 4), meta=np.ndarray>
- units :
- degrees_east
Array Chunk Bytes 11.75 GB 117.50 MB Shape (6000, 340, 360, 4) (60, 340, 360, 4) Count 400 Tasks 100 Chunks Type float32 numpy.ndarray - thetao(time, lev, rlat, rlon)float32dask.array<chunksize=(60, 40, 340, 360), meta=np.ndarray>
- standard_name :
- sea_water_potential_temperature
- long_name :
- Sea Water Potential Temperature
- units :
- K
- original_name :
- thetao
- cell_methods :
- time: mean (interval: 1 month)
- cell_measures :
- area: areacello volume: volcello
- history :
- 2010-06-04T14:24:53Z altered by CMOR: Reordered dimensions, original order: time rlat rlon lev.
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_fx_inmcm4_piControl_r0i0p0.nc areacello: areacello_fx_inmcm4_piControl_r0i0p0.nc volcello: volcello_fx_inmcm4_piControl_r0i0p0.nc
- grid_mapping :
- rotated_latitude_longitude
Array Chunk Bytes 117.50 GB 1.18 GB Shape (6000, 40, 340, 360) (60, 40, 340, 360) Count 300 Tasks 100 Chunks Type float32 numpy.ndarray
- institution :
- INM (Institute for Numerical Mathematics, Moscow, Russia)
- institute_id :
- INM
- experiment_id :
- piControl
- source :
- inmcm4 (2009)
- model_id :
- inmcm4
- forcing :
- N/A
- parent_experiment_id :
- N/A
- branch_time :
- 0.0
- contact :
- Evgeny Volodin, volodin@inm.ras.ru,INM RAS, Gubkina 8, Moscow, 119333 Russia,+7-495-9383904
- history :
- Output from /data5/volodin/PICNTL 2010-06-04T14:24:54Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- comment :
- no comments
- references :
- Volodin, Diansky, Gusev 2010. Climate model INMCM4.0. Izvestia RAS. Atmospheric and oceanic physics, V.46, N4, in print.
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- b783b6e6-76ac-4cd2-a67d-53388012237e
- product :
- output
- experiment :
- pre-industrial control
- frequency :
- mon
- creation_date :
- 2010-06-04T14:24:54Z
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table Omon (12 May 2010) f2afe576fb73a3a11aaa3cc8f2e62cf3
- title :
- inmcm4 model output prepared for CMIP5 pre-industrial control
- parent_experiment :
- N/A
- modeling_realm :
- ocean
- realization :
- 1
- cmor_version :
- 2.0.0