MRI-CGCM3 model output prepared for CMIP5 abrupt 4XCO2
Load in Python
from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/cl_Amon_MRI-CGCM3_abrupt4xCO2_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | MRI-CGCM3 model output prepared for CMIP5 abrupt 4XCO2 |
| location | /shared/cmip5/data/abrupt4xCO2/atmos/mon/Amon/cl/MRI.MRI-CGCM3/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/cl_Amon_MRI-CGCM3_abrupt4xCO2_r1i1p1.yaml |
| last updated | 2013-06-14 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, lat: 160, lev: 35, lon: 320, time: 1800)
Coordinates:
* time (time) float64 15.5 45.0 74.5 ... 5.471e+04 5.474e+04 5.477e+04
* lev (lev) float64 0.995 0.9825 0.965 ... 0.02447 0.01782 0.01269
* lat (lat) float64 -89.14 -88.03 -86.91 -85.79 ... 86.91 88.03 89.14
* lon (lon) float64 0.0 1.125 2.25 3.375 ... 355.5 356.6 357.8 358.9
Dimensions without coordinates: bnds
Data variables:
time_bnds (time, bnds) float64 dask.array<chunksize=(120, 2), meta=np.ndarray>
lev_bnds (time, lev, bnds) float64 dask.array<chunksize=(120, 35, 2), meta=np.ndarray>
p0 (time) float32 101325.0 101325.0 101325.0 ... 101325.0 101325.0
a (time, lev) float64 dask.array<chunksize=(120, 35), meta=np.ndarray>
b (time, lev) float64 dask.array<chunksize=(120, 35), meta=np.ndarray>
ps (time, lat, lon) float32 dask.array<chunksize=(120, 160, 320), meta=np.ndarray>
a_bnds (time, lev, bnds) float64 dask.array<chunksize=(120, 35, 2), meta=np.ndarray>
b_bnds (time, lev, bnds) float64 dask.array<chunksize=(120, 35, 2), meta=np.ndarray>
lat_bnds (time, lat, bnds) float64 dask.array<chunksize=(120, 160, 2), meta=np.ndarray>
lon_bnds (time, lon, bnds) float64 dask.array<chunksize=(120, 320, 2), meta=np.ndarray>
cl (time, lev, lat, lon) float32 dask.array<chunksize=(120, 35, 160, 320), meta=np.ndarray>
Attributes:
institution: MRI (Meteorological Research Institute, Tsukuba, ...
institute_id: MRI
experiment_id: abrupt4xCO2
source: MRI-CGCM3 2011 atmosphere: GSMUV (gsmuv-101124, T...
model_id: MRI-CGCM3
forcing: GHG (CO2 only)
parent_experiment_id: piControl
parent_experiment_rip: r1i1p1
branch_time: 14610.0
contact: Seiji Yukimoto (yukimoto@mri-jma.go.jp)
history: Output from /sharex2/cmip5/abrupt4xCO2/run-C_abru...
references: Model described by Yukimoto et al. (Technical Rep...
initialization_method: 1
physics_version: 1
tracking_id: e7a014bd-2ae1-4fe8-9ddb-7e618faf1218
product: output
experiment: abrupt 4XCO2
frequency: mon
creation_date: 2011-06-07T21:57:59Z
Conventions: CF-1.4
project_id: CMIP5
table_id: Table Amon (27 April 2011) a5a1c518f52ae340313ba0...
title: MRI-CGCM3 model output prepared for CMIP5 abrupt ...
parent_experiment: pre-industrial control
modeling_realm: atmos
realization: 1
cmor_version: 2.6.0xarray.Dataset
- bnds: 2
- lat: 160
- lev: 35
- lon: 320
- time: 1800
- time(time)float6415.5 45.0 ... 5.474e+04 5.477e+04
- bounds :
- time_bnds
- units :
- days since 1851-01-01
- calendar :
- standard
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([1.55000e+01, 4.50000e+01, 7.45000e+01, ..., 5.47105e+04, 5.47410e+04, 5.47715e+04]) - lev(lev)float640.995 0.9825 ... 0.01782 0.01269
- bounds :
- lev_bnds
- units :
- 1
- axis :
- Z
- positive :
- down
- long_name :
- hybrid sigma pressure coordinate
- standard_name :
- atmosphere_hybrid_sigma_pressure_coordinate
- formula :
- p = a*p0 + b*ps
- formula_terms :
- p0: p0 a: a b: b ps: ps
array([0.994996, 0.98249 , 0.964983, 0.942465, 0.914922, 0.882353, 0.845271, 0.804677, 0.761574, 0.716962, 0.671845, 0.626721, 0.582097, 0.538472, 0.495847, 0.454224, 0.414116, 0.37602 , 0.339429, 0.303853, 0.269806, 0.237784, 0.20779 , 0.179825, 0.15389 , 0.129985, 0.108109, 0.088385, 0.070994, 0.056 , 0.043351, 0.032904, 0.024469, 0.017815, 0.01269 ]) - lat(lat)float64-89.14 -88.03 ... 88.03 89.14
- bounds :
- lat_bnds
- units :
- degrees_north
- axis :
- Y
- long_name :
- latitude
- standard_name :
- latitude
array([-89.14152, -88.02943, -86.91077, -85.79063, -84.66992, -83.54895, -82.42782, -81.30659, -80.18531, -79.06398, -77.94262, -76.82124, -75.69984, -74.57843, -73.45701, -72.33558, -71.21414, -70.09269, -68.97124, -67.84978, -66.72833, -65.60686, -64.4854 , -63.36393, -62.24246, -61.12099, -59.99952, -58.87804, -57.75657, -56.63509, -55.51361, -54.39214, -53.27066, -52.14917, -51.02769, -49.90621, -48.78473, -47.66325, -46.54176, -45.42028, -44.29879, -43.17731, -42.05582, -40.93434, -39.81285, -38.69137, -37.56988, -36.44839, -35.32691, -34.20542, -33.08393, -31.96244, -30.84096, -29.71947, -28.59798, -27.47649, -26.355 , -25.23351, -24.11203, -22.99054, -21.86905, -20.74756, -19.62607, -18.50458, -17.38309, -16.2616 , -15.14011, -14.01862, -12.89713, -11.77564, -10.65415, -9.53266, -8.41117, -7.28968, -6.16819, -5.0467 , -3.92521, -2.80372, -1.68223, -0.56074, 0.56074, 1.68223, 2.80372, 3.92521, 5.0467 , 6.16819, 7.28968, 8.41117, 9.53266, 10.65415, 11.77564, 12.89713, 14.01862, 15.14011, 16.2616 , 17.38309, 18.50458, 19.62607, 20.74756, 21.86905, 22.99054, 24.11203, 25.23351, 26.355 , 27.47649, 28.59798, 29.71947, 30.84096, 31.96244, 33.08393, 34.20542, 35.32691, 36.44839, 37.56988, 38.69137, 39.81285, 40.93434, 42.05582, 43.17731, 44.29879, 45.42028, 46.54176, 47.66325, 48.78473, 49.90621, 51.02769, 52.14917, 53.27066, 54.39214, 55.51361, 56.63509, 57.75657, 58.87804, 59.99952, 61.12099, 62.24246, 63.36393, 64.4854 , 65.60686, 66.72833, 67.84978, 68.97124, 70.09269, 71.21414, 72.33558, 73.45701, 74.57843, 75.69984, 76.82124, 77.94262, 79.06398, 80.18531, 81.30659, 82.42782, 83.54895, 84.66992, 85.79063, 86.91077, 88.02943, 89.14152]) - lon(lon)float640.0 1.125 2.25 ... 357.8 358.9
- bounds :
- lon_bnds
- units :
- degrees_east
- axis :
- X
- long_name :
- longitude
- standard_name :
- longitude
array([ 0. , 1.125, 2.25 , ..., 356.625, 357.75 , 358.875])
- time_bnds(time, bnds)float64dask.array<chunksize=(120, 2), meta=np.ndarray>
Array Chunk Bytes 28.80 kB 1.92 kB Shape (1800, 2) (120, 2) Count 45 Tasks 15 Chunks Type float64 numpy.ndarray - lev_bnds(time, lev, bnds)float64dask.array<chunksize=(120, 35, 2), meta=np.ndarray>
- formula :
- p = a*p0 + b*ps
- standard_name :
- atmosphere_hybrid_sigma_pressure_coordinate
- units :
- 1
- formula_terms :
- p0: p0 a: a_bnds b: b_bnds ps: ps
Array Chunk Bytes 1.01 MB 67.20 kB Shape (1800, 35, 2) (120, 35, 2) Count 60 Tasks 15 Chunks Type float64 numpy.ndarray - p0(time)float32101325.0 101325.0 ... 101325.0
- long_name :
- vertical coordinate formula term: reference pressure
- units :
- Pa
array([101325., 101325., 101325., ..., 101325., 101325., 101325.], dtype=float32) - a(time, lev)float64dask.array<chunksize=(120, 35), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: a(k)
Array Chunk Bytes 504.00 kB 33.60 kB Shape (1800, 35) (120, 35) Count 60 Tasks 15 Chunks Type float64 numpy.ndarray - b(time, lev)float64dask.array<chunksize=(120, 35), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: b(k)
Array Chunk Bytes 504.00 kB 33.60 kB Shape (1800, 35) (120, 35) Count 60 Tasks 15 Chunks Type float64 numpy.ndarray - ps(time, lat, lon)float32dask.array<chunksize=(120, 160, 320), meta=np.ndarray>
- standard_name :
- surface_air_pressure
- long_name :
- Surface Air Pressure
- comment :
- not, in general, the same as mean sea-level pressure
- units :
- Pa
- cell_methods :
- time: mean
- cell_measures :
- area: areacella
Array Chunk Bytes 368.64 MB 24.58 MB Shape (1800, 160, 320) (120, 160, 320) Count 45 Tasks 15 Chunks Type float32 numpy.ndarray - a_bnds(time, lev, bnds)float64dask.array<chunksize=(120, 35, 2), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: a(k+1/2)
Array Chunk Bytes 1.01 MB 67.20 kB Shape (1800, 35, 2) (120, 35, 2) Count 60 Tasks 15 Chunks Type float64 numpy.ndarray - b_bnds(time, lev, bnds)float64dask.array<chunksize=(120, 35, 2), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: b(k+1/2)
Array Chunk Bytes 1.01 MB 67.20 kB Shape (1800, 35, 2) (120, 35, 2) Count 60 Tasks 15 Chunks Type float64 numpy.ndarray - lat_bnds(time, lat, bnds)float64dask.array<chunksize=(120, 160, 2), meta=np.ndarray>
Array Chunk Bytes 4.61 MB 307.20 kB Shape (1800, 160, 2) (120, 160, 2) Count 60 Tasks 15 Chunks Type float64 numpy.ndarray - lon_bnds(time, lon, bnds)float64dask.array<chunksize=(120, 320, 2), meta=np.ndarray>
Array Chunk Bytes 9.22 MB 614.40 kB Shape (1800, 320, 2) (120, 320, 2) Count 60 Tasks 15 Chunks Type float64 numpy.ndarray - cl(time, lev, lat, lon)float32dask.array<chunksize=(120, 35, 160, 320), meta=np.ndarray>
- standard_name :
- cloud_area_fraction_in_atmosphere_layer
- long_name :
- Cloud Area Fraction
- comment :
- Includes both large-scale and convective cloud.
- units :
- %
- original_name :
- CVR
- cell_methods :
- time: mean (interval: 30 minutes)
- cell_measures :
- area: areacella
- history :
- 2011-06-07T21:57:59Z altered by CMOR: replaced missing value flag (-9.99e+33) with standard missing value (1e+20).
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MRI-CGCM3_abrupt4xCO2_r0i0p0.nc areacella: areacella_fx_MRI-CGCM3_abrupt4xCO2_r0i0p0.nc
Array Chunk Bytes 12.90 GB 860.16 MB Shape (1800, 35, 160, 320) (120, 35, 160, 320) Count 45 Tasks 15 Chunks Type float32 numpy.ndarray
- institution :
- MRI (Meteorological Research Institute, Tsukuba, Japan)
- institute_id :
- MRI
- experiment_id :
- abrupt4xCO2
- source :
- MRI-CGCM3 2011 atmosphere: GSMUV (gsmuv-101124, TL159L48); ocean: MRI.COM3 (MRICOM-3_0-20101116, 1x0.5L51); sea ice: MRI.COM3; land: HAL (HAL_cmip5_v0.31_01); aerosol: MASINGAR-mk2 (masingar_mk2-20101111, TL95L48)
- model_id :
- MRI-CGCM3
- forcing :
- GHG (CO2 only)
- parent_experiment_id :
- piControl
- parent_experiment_rip :
- r1i1p1
- branch_time :
- 14610.0
- contact :
- Seiji Yukimoto (yukimoto@mri-jma.go.jp)
- history :
- Output from /sharex2/cmip5/abrupt4xCO2/run-C_abrupt4xCO2_01/grads/atm_eta_avr_mon.ctl 2011-06-07T21:57:59Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- references :
- Model described by Yukimoto et al. (Technical Report of the Meteorological Research Institute, 2011, 64, 83pp.)
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- e7a014bd-2ae1-4fe8-9ddb-7e618faf1218
- product :
- output
- experiment :
- abrupt 4XCO2
- frequency :
- mon
- creation_date :
- 2011-06-07T21:57:59Z
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table Amon (27 April 2011) a5a1c518f52ae340313ba0aada03f862
- title :
- MRI-CGCM3 model output prepared for CMIP5 abrupt 4XCO2
- parent_experiment :
- pre-industrial control
- modeling_realm :
- atmos
- realization :
- 1
- cmor_version :
- 2.6.0