NOAA GFDL GFDL-CM3, pre-industrial control (run 1) experiment output for CMIP5 AR5
Load in Python
from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/wmo_Omon_GFDL-CM3_piControl_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | NOAA GFDL GFDL-CM3, pre-industrial control (run 1) experiment output for CMIP5 AR5 |
| location | /shared/cmip5/data/piControl/ocean/mon/Omon/wmo/NOAA-GFDL.GFDL-CM3/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/wmo_Omon_GFDL-CM3_piControl_r1i1p1.yaml |
| last updated | 2015-01-17 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, lev: 50, rlat: 200, rlon: 360, time: 9600, vertices: 4)
Coordinates:
* bnds (bnds) float64 1.0 2.0
* lev (lev) float64 10.0 20.0 30.0 ... 4.769e+03 5.133e+03 5.5e+03
* time (time) float64 15.5 45.0 74.5 ... 2.919e+05 2.92e+05 2.92e+05
* rlon (rlon) float64 -279.5 -278.5 -277.5 -276.5 ... 77.5 78.5 79.5
* rlat (rlat) float64 -81.5 -80.5 -79.5 -78.5 ... 86.5 87.5 88.5 89.5
lat (rlat, rlon) float32 dask.array<chunksize=(200, 360), meta=np.ndarray>
lon (rlat, rlon) float32 dask.array<chunksize=(200, 360), meta=np.ndarray>
* vertices (vertices) int32 0 1 2 3
Data variables:
average_DT (time) float64 dask.array<chunksize=(60,), meta=np.ndarray>
average_T1 (time) float64 dask.array<chunksize=(60,), meta=np.ndarray>
average_T2 (time) float64 dask.array<chunksize=(60,), meta=np.ndarray>
time_bnds (time, bnds) float64 dask.array<chunksize=(60, 2), meta=np.ndarray>
wmo (time, lev, rlat, rlon) float32 dask.array<chunksize=(60, 50, 200, 360), meta=np.ndarray>
lat_vertices (time, rlat, rlon, vertices) float64 dask.array<chunksize=(60, 200, 360, 4), meta=np.ndarray>
lev_bnds (time, lev, bnds) float64 dask.array<chunksize=(60, 50, 2), meta=np.ndarray>
lon_vertices (time, rlat, rlon, vertices) float64 dask.array<chunksize=(60, 200, 360, 4), meta=np.ndarray>
Attributes:
title: NOAA GFDL GFDL-CM3, pre-industrial control (run 1...
institute_id: NOAA GFDL
source: GFDL-CM3 2010 atmosphere: AM3 (AM3p9,C48L48); sea...
contact: gfdl.climate.model.info@noaa.gov
project_id: CMIP5
table_id: Table Omon (31 Jan 2011)
experiment_id: piControl
realization: 1
modeling_realm: ocean
tracking_id: 125ef03c-c4dc-45cc-a2ca-5323ceb53985
Conventions: CF-1.4
references: The GFDL Data Portal (http://nomads.gfdl.noaa.gov...
comment: GFDL experiment name: CM3Z_Control-1860_D1
GFDL ...
gfdl_experiment_name: CM3Z_Control-1860_D1
creation_date: 2012-03-21T22:54:03Z
model_id: GFDL-CM3
branch_time: 0.0
experiment: pre-industrial control
forcing: N/A
frequency: mon
initialization_method: 1
parent_experiment_id: N/A
physics_version: 1
product: output1
institution: NOAA GFDL(201 Forrestal Rd, Princeton, NJ, 08540)
history: File was processed by fremetar (GFDL analog of CM...
parent_experiment_rip: N/Axarray.Dataset
- bnds: 2
- lev: 50
- rlat: 200
- rlon: 360
- time: 9600
- vertices: 4
- bnds(bnds)float641.0 2.0
- long_name :
- vertex number
- cartesian_axis :
- N
array([1., 2.])
- lev(lev)float6410.0 20.0 ... 5.133e+03 5.5e+03
- long_name :
- ocean depth coordinate
- units :
- m
- cartesian_axis :
- Z
- positive :
- down
- bounds :
- lev_bnds
- axis :
- Z
- standard_name :
- depth
- description :
- generic ocean model vertical coordinate (nondimensional or dimensional)
array([ 10. , 20. , 30. , 40. , 50. , 60. , 70. , 80. , 90. , 100. , 110. , 120. , 130. , 140. , 150. , 160. , 170. , 180. , 190. , 200. , 210. , 220. , 230.561417, 243.361404, 260.610382, 284.462891, 316.990295, 360.154968, 415.785461, 485.553619, 570.953491, 673.28241 , 793.625 , 932.839294, 1091.546021, 1270.120605, 1468.688843, 1687.125 , 1925.053589, 2181.85376 , 2456.667725, 2748.410889, 3055.7854 , 3377.297852, 3711.276123, 4055.891357, 4409.181641, 4769.075684, 5133.418457, 5500. ]) - time(time)float6415.5 45.0 ... 2.92e+05 2.92e+05
- long_name :
- time
- units :
- days since 0001-01-01 00:00:00
- cartesian_axis :
- T
- calendar_type :
- noleap
- calendar :
- noleap
- bounds :
- time_bnds
- standard_name :
- time
- axis :
- T
array([1.550000e+01, 4.500000e+01, 7.450000e+01, ..., 2.919235e+05, 2.919540e+05, 2.919845e+05]) - rlon(rlon)float64-279.5 -278.5 -277.5 ... 78.5 79.5
- long_name :
- longitude in rotated pole grid
- units :
- degrees
- axis :
- X
- standard_name :
- grid_longitude
array([-279.5, -278.5, -277.5, ..., 77.5, 78.5, 79.5])
- rlat(rlat)float64-81.5 -80.5 -79.5 ... 88.5 89.5
- long_name :
- latitude in rotated pole grid
- units :
- degrees
- axis :
- Y
- standard_name :
- grid_latitude
array([-81.5 , -80.5 , -79.5 , -78.5 , -77.5 , -76.5 , -75.5 , -74.5 , -73.5 , -72.5 , -71.5 , -70.5 , -69.5 , -68.5 , -67.5 , -66.5 , -65.5 , -64.5 , -63.5 , -62.5 , -61.5 , -60.5 , -59.5 , -58.5 , -57.5 , -56.5 , -55.5 , -54.5 , -53.5 , -52.5 , -51.5 , -50.5 , -49.5 , -48.5 , -47.5 , -46.5 , -45.5 , -44.5 , -43.5 , -42.5 , -41.5 , -40.5 , -39.5 , -38.5 , -37.5 , -36.5 , -35.5 , -34.5 , -33.5 , -32.5 , -31.5 , -30.5 , -29.5 , -28.501426, -27.507105, -26.519792, -25.542121, -24.576562, -23.625377, -22.690584, -21.773917, -20.876803, -20.000333, -19.145246, -18.311912, -17.500333, -16.710136, -15.940584, -15.190584, -14.458711, -13.743228, -13.04212 , -12.353125, -11.673771, -11.001426, -10.333333, -9.666666, -9.002051, -8.343542, -7.695041, -7.060205, -6.442354, -5.844389, -5.268724, -4.717221, -4.191149, -3.691149, -3.217221, -2.768724, -2.344389, -1.942354, -1.560205, -1.195041, -0.843542, -0.502051, -0.166666, 0.166667, 0.502052, 0.843543, 1.195042, 1.560206, 1.942354, 2.34439 , 2.768725, 3.217222, 3.69115 , 4.19115 , 4.717222, 5.268725, 5.84439 , 6.442354, 7.060206, 7.695042, 8.343543, 9.002052, 9.666667, 10.333334, 11.001426, 11.673772, 12.353125, 13.042121, 13.743229, 14.458711, 15.190584, 15.940584, 16.710137, 17.500334, 18.311913, 19.145246, 20.000334, 20.876804, 21.773918, 22.690585, 23.625378, 24.576563, 25.542122, 26.519792, 27.507106, 28.501427, 29.500001, 30.500001, 31.500001, 32.500001, 33.500001, 34.500001, 35.500001, 36.500001, 37.500001, 38.500001, 39.500001, 40.500001, 41.500001, 42.500001, 43.500001, 44.500001, 45.500001, 46.500001, 47.500001, 48.500001, 49.500001, 50.500001, 51.500001, 52.500001, 53.500001, 54.500001, 55.500001, 56.500001, 57.500001, 58.500001, 59.500001, 60.500001, 61.500001, 62.500001, 63.500001, 64.500001, 65.500001, 66.500001, 67.500001, 68.500001, 69.500001, 70.500001, 71.500001, 72.500001, 73.500001, 74.500001, 75.500001, 76.500001, 77.500001, 78.500001, 79.500001, 80.500001, 81.500001, 82.500001, 83.500001, 84.500001, 85.500001, 86.500001, 87.500001, 88.500001, 89.500001]) - lat(rlat, rlon)float32dask.array<chunksize=(200, 360), meta=np.ndarray>
- long_name :
- latitude coordinate
- units :
- degrees_north
- standard_name :
- latitude
- bounds :
- lat_vertices
Array Chunk Bytes 288.00 kB 288.00 kB Shape (200, 360) (200, 360) Count 795 Tasks 1 Chunks Type float32 numpy.ndarray - lon(rlat, rlon)float32dask.array<chunksize=(200, 360), meta=np.ndarray>
- long_name :
- longitude coordinate
- units :
- degrees_east
- standard_name :
- longitude
- bounds :
- lon_vertices
Array Chunk Bytes 288.00 kB 288.00 kB Shape (200, 360) (200, 360) Count 795 Tasks 1 Chunks Type float32 numpy.ndarray - vertices(vertices)int320 1 2 3
array([0, 1, 2, 3], dtype=int32)
- average_DT(time)float64dask.array<chunksize=(60,), meta=np.ndarray>
- long_name :
- Length of average period
- units :
- days
Array Chunk Bytes 76.80 kB 480 B Shape (9600,) (60,) Count 480 Tasks 160 Chunks Type float64 numpy.ndarray - average_T1(time)float64dask.array<chunksize=(60,), meta=np.ndarray>
- long_name :
- Start time for average period
- units :
- days since 0001-01-01 00:00:00
Array Chunk Bytes 76.80 kB 480 B Shape (9600,) (60,) Count 480 Tasks 160 Chunks Type float64 numpy.ndarray - average_T2(time)float64dask.array<chunksize=(60,), meta=np.ndarray>
- long_name :
- End time for average period
- units :
- days since 0001-01-01 00:00:00
Array Chunk Bytes 76.80 kB 480 B Shape (9600,) (60,) Count 480 Tasks 160 Chunks Type float64 numpy.ndarray - time_bnds(time, bnds)float64dask.array<chunksize=(60, 2), meta=np.ndarray>
- long_name :
- time axis boundaries
- units :
- days since 0001-01-01 00:00:00
Array Chunk Bytes 153.60 kB 960 B Shape (9600, 2) (60, 2) Count 480 Tasks 160 Chunks Type float64 numpy.ndarray - wmo(time, lev, rlat, rlon)float32dask.array<chunksize=(60, 50, 200, 360), meta=np.ndarray>
- original_name :
- tz_trans*1.e9
- cell_methods :
- time: mean
- valid_range :
- [-1.e+20 1.e+20]
- units :
- kg s-1
- long_name :
- Upward Ocean Mass Transport
- standard_name :
- upward_ocean_mass_transport
- cell_measures :
- area: areacello
- comments :
- Note: This model output is presented on the model's tripolar grid. The North Pole singularity is avoided by using this nonregular grid north of 65N. More information about the ocean and sea ice model's grid can be found at http://nomads.gfdl.noaa.gov/.
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_ocean_fx_GFDL-CM3_piControl_r0i0p0.nc areacello: areacello_fx_GFDL-CM3_piControl_r0i0p0.nc
- original_units :
- kg s-1
Array Chunk Bytes 138.24 GB 864.00 MB Shape (9600, 50, 200, 360) (60, 50, 200, 360) Count 480 Tasks 160 Chunks Type float32 numpy.ndarray - lat_vertices(time, rlat, rlon, vertices)float64dask.array<chunksize=(60, 200, 360, 4), meta=np.ndarray>
- units :
- degrees_north
Array Chunk Bytes 22.12 GB 138.24 MB Shape (9600, 200, 360, 4) (60, 200, 360, 4) Count 640 Tasks 160 Chunks Type float64 numpy.ndarray - lev_bnds(time, lev, bnds)float64dask.array<chunksize=(60, 50, 2), meta=np.ndarray>
Array Chunk Bytes 7.68 MB 48.00 kB Shape (9600, 50, 2) (60, 50, 2) Count 640 Tasks 160 Chunks Type float64 numpy.ndarray - lon_vertices(time, rlat, rlon, vertices)float64dask.array<chunksize=(60, 200, 360, 4), meta=np.ndarray>
- units :
- degrees_east
Array Chunk Bytes 22.12 GB 138.24 MB Shape (9600, 200, 360, 4) (60, 200, 360, 4) Count 640 Tasks 160 Chunks Type float64 numpy.ndarray
- title :
- NOAA GFDL GFDL-CM3, pre-industrial control (run 1) experiment output for CMIP5 AR5
- institute_id :
- NOAA GFDL
- source :
- GFDL-CM3 2010 atmosphere: AM3 (AM3p9,C48L48); sea ice: SIS (SISp2,Tripolar360x200); land: LM3 (LM3p7_cCM3,C48); ocean: MOM4 (MOM4p1_x1_Z50_cCM3,Tripolar360x200L50)
- contact :
- gfdl.climate.model.info@noaa.gov
- project_id :
- CMIP5
- table_id :
- Table Omon (31 Jan 2011)
- experiment_id :
- piControl
- realization :
- 1
- modeling_realm :
- ocean
- tracking_id :
- 125ef03c-c4dc-45cc-a2ca-5323ceb53985
- Conventions :
- CF-1.4
- references :
- The GFDL Data Portal (http://nomads.gfdl.noaa.gov/) provides access to NOAA/GFDL's publicly available model input and output data sets. From this web site one can view and download data sets and documentation, including those related to the GFDL coupled models experiments run for the IPCC's 5th Assessment Report and the US CCSP.
- comment :
- GFDL experiment name: CM3Z_Control-1860_D1 GFDL parent experiment name: N/A CMIP5 experiment ID: piControl Initial conditions from this experiment (CMIP5 expt. 3.1) were taken from 01Jan0281 of the 1860 control model spin-up experiment CM3Y_Control-1860_I7_TIM_RCP2. Spin up for this experiment included experiments CM3Y_Control-1860_I2 (0001-0300, dynamic potential vegetation), CM3Y_I6_1700-1860_LandUse (1701-1859, dynamic vegetation, historical land use), CM3Y_Control-1860_I7_TIM (0001-0100, static 1859 vegetation, TIM solar irradiance), CM3Y_Control-1860_I7_TIM_RCP (0101-0200), and CM3Y_Control-1860_I7_TIM_RCP2 (0201-0280). This model includes direct and indirect aerosol effects.
- gfdl_experiment_name :
- CM3Z_Control-1860_D1
- creation_date :
- 2012-03-21T22:54:03Z
- model_id :
- GFDL-CM3
- branch_time :
- 0.0
- experiment :
- pre-industrial control
- forcing :
- N/A
- frequency :
- mon
- initialization_method :
- 1
- parent_experiment_id :
- N/A
- physics_version :
- 1
- product :
- output1
- institution :
- NOAA GFDL(201 Forrestal Rd, Princeton, NJ, 08540)
- history :
- File was processed by fremetar (GFDL analog of CMOR). TripleID: [exper_id_bjHsI67ZTv,realiz_id_cbf2FR2EN8,run_id_XhhqRnrz0b]
- parent_experiment_rip :
- N/A