Intake ESM example

Load CMIP6 Data with Intake ESM

Intake ESM is an experimental new package that aims to provide a higher-level interface to searching and loading Earth System Model data archives, such as CMIP6. The packages is under very active development, and features may be unstable. Please report any issues or suggestions on github.

import xarray as xr
xr.set_options(display_style='html')
import intake
%matplotlib inline

Intake ESM works by parsing an ESM Collection Spec and converting it to an intake catalog. The collection spec is stored in a .json file. Here we open it using intake.

cat_url = "https://storage.googleapis.com/cmip6/pangeo-cmip6.json"
col = intake.open_esm_datastore(cat_url)
col

pangeo-cmip6-ESM Collection with 235624 entries:
	> 15 activity_id(s)

	> 32 institution_id(s)

	> 69 source_id(s)

	> 101 experiment_id(s)

	> 135 member_id(s)

	> 29 table_id(s)

	> 313 variable_id(s)

	> 10 grid_label(s)

	> 235624 zstore(s)

	> 60 dcpp_init_year(s)

We can now use intake methods to search the collection, and, if desired, export a pandas dataframe.

cat = col.search(experiment_id=['historical', 'ssp585'], table_id='Oyr', variable_id='o2',
                 grid_label='gn')
cat.df

	activity_id	institution_id	source_id	experiment_id	member_id	table_id	variable_id	grid_label	zstore	dcpp_init_year
0	CMIP	CCCma	CanESM5-CanOE	historical	r1i1p2f1	Oyr	o2	gn	gs://cmip6/CMIP/CCCma/CanESM5-CanOE/historical...	NaN
1	CMIP	CCCma	CanESM5-CanOE	historical	r2i1p2f1	Oyr	o2	gn	gs://cmip6/CMIP/CCCma/CanESM5-CanOE/historical...	NaN
2	CMIP	CCCma	CanESM5-CanOE	historical	r3i1p2f1	Oyr	o2	gn	gs://cmip6/CMIP/CCCma/CanESM5-CanOE/historical...	NaN
3	CMIP	CCCma	CanESM5	historical	r10i1p1f1	Oyr	o2	gn	gs://cmip6/CMIP/CCCma/CanESM5/historical/r10i1...	NaN
4	CMIP	CCCma	CanESM5	historical	r10i1p2f1	Oyr	o2	gn	gs://cmip6/CMIP/CCCma/CanESM5/historical/r10i1...	NaN
...	...	...	...	...	...	...	...	...	...	...
132	ScenarioMIP	IPSL	IPSL-CM6A-LR	ssp585	r4i1p1f1	Oyr	o2	gn	gs://cmip6/ScenarioMIP/IPSL/IPSL-CM6A-LR/ssp58...	NaN
133	ScenarioMIP	IPSL	IPSL-CM6A-LR	ssp585	r6i1p1f1	Oyr	o2	gn	gs://cmip6/ScenarioMIP/IPSL/IPSL-CM6A-LR/ssp58...	NaN
134	ScenarioMIP	MIROC	MIROC-ES2L	ssp585	r1i1p1f2	Oyr	o2	gn	gs://cmip6/ScenarioMIP/MIROC/MIROC-ES2L/ssp585...	NaN
135	ScenarioMIP	MPI-M	MPI-ESM1-2-LR	ssp585	r10i1p1f1	Oyr	o2	gn	gs://cmip6/ScenarioMIP/MPI-M/MPI-ESM1-2-LR/ssp...	NaN
136	ScenarioMIP	MPI-M	MPI-ESM1-2-LR	ssp585	r1i1p1f1	Oyr	o2	gn	gs://cmip6/ScenarioMIP/MPI-M/MPI-ESM1-2-LR/ssp...	NaN

137 rows × 10 columns

Intake knows how to automatically open the datasets using xarray. Furthermore, intake esm contains special logic to concatenate and merge the individual results of our query into larger, more high-level aggregated xarray datasets.

dset_dict = cat.to_dataset_dict(zarr_kwargs={'consolidated': True})
list(dset_dict.keys())

--> The keys in the returned dictionary of datasets are constructed as follows:
	'activity_id.institution_id.source_id.experiment_id.table_id.grid_label'
                
--> There is/are 17 group(s)
[########################################] | 100% Completed |  1min 27.1s

['CMIP.CCCma.CanESM5.historical.Oyr.gn',
 'CMIP.CCCma.CanESM5-CanOE.historical.Oyr.gn',
 'CMIP.CSIRO.ACCESS-ESM1-5.historical.Oyr.gn',
 'CMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM.historical.Oyr.gn',
 'CMIP.IPSL.IPSL-CM6A-LR.historical.Oyr.gn',
 'CMIP.MIROC.MIROC-ES2L.historical.Oyr.gn',
 'CMIP.MPI-M.MPI-ESM1-2-HR.historical.Oyr.gn',
 'CMIP.MPI-M.MPI-ESM1-2-LR.historical.Oyr.gn',
 'CMIP.NCC.NorESM2-LM.historical.Oyr.gn',
 'ScenarioMIP.CCCma.CanESM5.ssp585.Oyr.gn',
 'ScenarioMIP.CCCma.CanESM5-CanOE.ssp585.Oyr.gn',
 'ScenarioMIP.CSIRO.ACCESS-ESM1-5.ssp585.Oyr.gn',
 'ScenarioMIP.DKRZ.MPI-ESM1-2-HR.ssp585.Oyr.gn',
 'ScenarioMIP.DWD.MPI-ESM1-2-HR.ssp585.Oyr.gn',
 'ScenarioMIP.IPSL.IPSL-CM6A-LR.ssp585.Oyr.gn',
 'ScenarioMIP.MIROC.MIROC-ES2L.ssp585.Oyr.gn',
 'ScenarioMIP.MPI-M.MPI-ESM1-2-LR.ssp585.Oyr.gn']

ds = dset_dict['CMIP.CCCma.CanESM5.historical.Oyr.gn']
ds

xarray.Dataset

Dimensions:
- bnds: 2
- i: 360
- j: 291
- lev: 45
- member_id: 35
- time: 165
- vertices: 4

Coordinates: (9)

longitude

(j, i)

float64

dask.array<chunksize=(291, 360), meta=np.ndarray>

bounds :: vertices_longitude
long_name :: longitude
standard_name :: longitude
units :: degrees_east





  
      Array  Chunk 
  
  
     Bytes  838.08 kB   838.08 kB 
     Shape  (291, 360)   (291, 360) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

lev_bnds

(lev, bnds)

float64

dask.array<chunksize=(45, 2), meta=np.ndarray>





  
      Array  Chunk 
  
  
     Bytes  720 B   720 B 
     Shape  (45, 2)   (45, 2) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

latitude

(j, i)

float64

dask.array<chunksize=(291, 360), meta=np.ndarray>

bounds :: vertices_latitude
long_name :: latitude
standard_name :: latitude
units :: degrees_north





  
      Array  Chunk 
  
  
     Bytes  838.08 kB   838.08 kB 
     Shape  (291, 360)   (291, 360) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

time_bnds

(time, bnds)

object

dask.array<chunksize=(165, 2), meta=np.ndarray>





  
      Array  Chunk 
  
  
     Bytes  2.64 kB   2.64 kB 
     Shape  (165, 2)   (165, 2) 
     Count  2 Tasks  1 Chunks 
     Type  object  numpy.ndarray

j
(j)
int32
0 1 2 3 4 5 ... 286 287 288 289 290
long_name :
cell index along second dimension
units :
1
```
array([  0,   1,   2, ..., 288, 289, 290], dtype=int32)
```

time

(time)

object

1850-07-02 12:00:00 ... 2014-07-02 12:00:00

axis :: T
bounds :: time_bnds
long_name :: time
standard_name :: time

array([cftime.DatetimeNoLeap(1850-07-02 12:00:00),
       cftime.DatetimeNoLeap(1851-07-02 12:00:00),
       cftime.DatetimeNoLeap(1852-07-02 12:00:00),
       cftime.DatetimeNoLeap(1853-07-02 12:00:00),
       cftime.DatetimeNoLeap(1854-07-02 12:00:00),
       cftime.DatetimeNoLeap(1855-07-02 12:00:00),
       cftime.DatetimeNoLeap(1856-07-02 12:00:00),
       cftime.DatetimeNoLeap(1857-07-02 12:00:00),
       cftime.DatetimeNoLeap(1858-07-02 12:00:00),
       cftime.DatetimeNoLeap(1859-07-02 12:00:00),
       cftime.DatetimeNoLeap(1860-07-02 12:00:00),
       cftime.DatetimeNoLeap(1861-07-02 12:00:00),
       cftime.DatetimeNoLeap(1862-07-02 12:00:00),
       cftime.DatetimeNoLeap(1863-07-02 12:00:00),
       cftime.DatetimeNoLeap(1864-07-02 12:00:00),
       cftime.DatetimeNoLeap(1865-07-02 12:00:00),
       cftime.DatetimeNoLeap(1866-07-02 12:00:00),
       cftime.DatetimeNoLeap(1867-07-02 12:00:00),
       cftime.DatetimeNoLeap(1868-07-02 12:00:00),
       cftime.DatetimeNoLeap(1869-07-02 12:00:00),
       cftime.DatetimeNoLeap(1870-07-02 12:00:00),
       cftime.DatetimeNoLeap(1871-07-02 12:00:00),
       cftime.DatetimeNoLeap(1872-07-02 12:00:00),
       cftime.DatetimeNoLeap(1873-07-02 12:00:00),
       cftime.DatetimeNoLeap(1874-07-02 12:00:00),
       cftime.DatetimeNoLeap(1875-07-02 12:00:00),
       cftime.DatetimeNoLeap(1876-07-02 12:00:00),
       cftime.DatetimeNoLeap(1877-07-02 12:00:00),
       cftime.DatetimeNoLeap(1878-07-02 12:00:00),
       cftime.DatetimeNoLeap(1879-07-02 12:00:00),
       cftime.DatetimeNoLeap(1880-07-02 12:00:00),
       cftime.DatetimeNoLeap(1881-07-02 12:00:00),
       cftime.DatetimeNoLeap(1882-07-02 12:00:00),
       cftime.DatetimeNoLeap(1883-07-02 12:00:00),
       cftime.DatetimeNoLeap(1884-07-02 12:00:00),
       cftime.DatetimeNoLeap(1885-07-02 12:00:00),
       cftime.DatetimeNoLeap(1886-07-02 12:00:00),
       cftime.DatetimeNoLeap(1887-07-02 12:00:00),
       cftime.DatetimeNoLeap(1888-07-02 12:00:00),
       cftime.DatetimeNoLeap(1889-07-02 12:00:00),
       cftime.DatetimeNoLeap(1890-07-02 12:00:00),
       cftime.DatetimeNoLeap(1891-07-02 12:00:00),
       cftime.DatetimeNoLeap(1892-07-02 12:00:00),
       cftime.DatetimeNoLeap(1893-07-02 12:00:00),
       cftime.DatetimeNoLeap(1894-07-02 12:00:00),
       cftime.DatetimeNoLeap(1895-07-02 12:00:00),
       cftime.DatetimeNoLeap(1896-07-02 12:00:00),
       cftime.DatetimeNoLeap(1897-07-02 12:00:00),
       cftime.DatetimeNoLeap(1898-07-02 12:00:00),
       cftime.DatetimeNoLeap(1899-07-02 12:00:00),
       cftime.DatetimeNoLeap(1900-07-02 12:00:00),
       cftime.DatetimeNoLeap(1901-07-02 12:00:00),
       cftime.DatetimeNoLeap(1902-07-02 12:00:00),
       cftime.DatetimeNoLeap(1903-07-02 12:00:00),
       cftime.DatetimeNoLeap(1904-07-02 12:00:00),
       cftime.DatetimeNoLeap(1905-07-02 12:00:00),
       cftime.DatetimeNoLeap(1906-07-02 12:00:00),
       cftime.DatetimeNoLeap(1907-07-02 12:00:00),
       cftime.DatetimeNoLeap(1908-07-02 12:00:00),
       cftime.DatetimeNoLeap(1909-07-02 12:00:00),
       cftime.DatetimeNoLeap(1910-07-02 12:00:00),
       cftime.DatetimeNoLeap(1911-07-02 12:00:00),
       cftime.DatetimeNoLeap(1912-07-02 12:00:00),
       cftime.DatetimeNoLeap(1913-07-02 12:00:00),
       cftime.DatetimeNoLeap(1914-07-02 12:00:00),
       cftime.DatetimeNoLeap(1915-07-02 12:00:00),
       cftime.DatetimeNoLeap(1916-07-02 12:00:00),
       cftime.DatetimeNoLeap(1917-07-02 12:00:00),
       cftime.DatetimeNoLeap(1918-07-02 12:00:00),
       cftime.DatetimeNoLeap(1919-07-02 12:00:00),
       cftime.DatetimeNoLeap(1920-07-02 12:00:00),
       cftime.DatetimeNoLeap(1921-07-02 12:00:00),
       cftime.DatetimeNoLeap(1922-07-02 12:00:00),
       cftime.DatetimeNoLeap(1923-07-02 12:00:00),
       cftime.DatetimeNoLeap(1924-07-02 12:00:00),
       cftime.DatetimeNoLeap(1925-07-02 12:00:00),
       cftime.DatetimeNoLeap(1926-07-02 12:00:00),
       cftime.DatetimeNoLeap(1927-07-02 12:00:00),
       cftime.DatetimeNoLeap(1928-07-02 12:00:00),
       cftime.DatetimeNoLeap(1929-07-02 12:00:00),
       cftime.DatetimeNoLeap(1930-07-02 12:00:00),
       cftime.DatetimeNoLeap(1931-07-02 12:00:00),
       cftime.DatetimeNoLeap(1932-07-02 12:00:00),
       cftime.DatetimeNoLeap(1933-07-02 12:00:00),
       cftime.DatetimeNoLeap(1934-07-02 12:00:00),
       cftime.DatetimeNoLeap(1935-07-02 12:00:00),
       cftime.DatetimeNoLeap(1936-07-02 12:00:00),
       cftime.DatetimeNoLeap(1937-07-02 12:00:00),
       cftime.DatetimeNoLeap(1938-07-02 12:00:00),
       cftime.DatetimeNoLeap(1939-07-02 12:00:00),
       cftime.DatetimeNoLeap(1940-07-02 12:00:00),
       cftime.DatetimeNoLeap(1941-07-02 12:00:00),
       cftime.DatetimeNoLeap(1942-07-02 12:00:00),
       cftime.DatetimeNoLeap(1943-07-02 12:00:00),
       cftime.DatetimeNoLeap(1944-07-02 12:00:00),
       cftime.DatetimeNoLeap(1945-07-02 12:00:00),
       cftime.DatetimeNoLeap(1946-07-02 12:00:00),
       cftime.DatetimeNoLeap(1947-07-02 12:00:00),
       cftime.DatetimeNoLeap(1948-07-02 12:00:00),
       cftime.DatetimeNoLeap(1949-07-02 12:00:00),
       cftime.DatetimeNoLeap(1950-07-02 12:00:00),
       cftime.DatetimeNoLeap(1951-07-02 12:00:00),
       cftime.DatetimeNoLeap(1952-07-02 12:00:00),
       cftime.DatetimeNoLeap(1953-07-02 12:00:00),
       cftime.DatetimeNoLeap(1954-07-02 12:00:00),
       cftime.DatetimeNoLeap(1955-07-02 12:00:00),
       cftime.DatetimeNoLeap(1956-07-02 12:00:00),
       cftime.DatetimeNoLeap(1957-07-02 12:00:00),
       cftime.DatetimeNoLeap(1958-07-02 12:00:00),
       cftime.DatetimeNoLeap(1959-07-02 12:00:00),
       cftime.DatetimeNoLeap(1960-07-02 12:00:00),
       cftime.DatetimeNoLeap(1961-07-02 12:00:00),
       cftime.DatetimeNoLeap(1962-07-02 12:00:00),
       cftime.DatetimeNoLeap(1963-07-02 12:00:00),
       cftime.DatetimeNoLeap(1964-07-02 12:00:00),
       cftime.DatetimeNoLeap(1965-07-02 12:00:00),
       cftime.DatetimeNoLeap(1966-07-02 12:00:00),
       cftime.DatetimeNoLeap(1967-07-02 12:00:00),
       cftime.DatetimeNoLeap(1968-07-02 12:00:00),
       cftime.DatetimeNoLeap(1969-07-02 12:00:00),
       cftime.DatetimeNoLeap(1970-07-02 12:00:00),
       cftime.DatetimeNoLeap(1971-07-02 12:00:00),
       cftime.DatetimeNoLeap(1972-07-02 12:00:00),
       cftime.DatetimeNoLeap(1973-07-02 12:00:00),
       cftime.DatetimeNoLeap(1974-07-02 12:00:00),
       cftime.DatetimeNoLeap(1975-07-02 12:00:00),
       cftime.DatetimeNoLeap(1976-07-02 12:00:00),
       cftime.DatetimeNoLeap(1977-07-02 12:00:00),
       cftime.DatetimeNoLeap(1978-07-02 12:00:00),
       cftime.DatetimeNoLeap(1979-07-02 12:00:00),
       cftime.DatetimeNoLeap(1980-07-02 12:00:00),
       cftime.DatetimeNoLeap(1981-07-02 12:00:00),
       cftime.DatetimeNoLeap(1982-07-02 12:00:00),
       cftime.DatetimeNoLeap(1983-07-02 12:00:00),
       cftime.DatetimeNoLeap(1984-07-02 12:00:00),
       cftime.DatetimeNoLeap(1985-07-02 12:00:00),
       cftime.DatetimeNoLeap(1986-07-02 12:00:00),
       cftime.DatetimeNoLeap(1987-07-02 12:00:00),
       cftime.DatetimeNoLeap(1988-07-02 12:00:00),
       cftime.DatetimeNoLeap(1989-07-02 12:00:00),
       cftime.DatetimeNoLeap(1990-07-02 12:00:00),
       cftime.DatetimeNoLeap(1991-07-02 12:00:00),
       cftime.DatetimeNoLeap(1992-07-02 12:00:00),
       cftime.DatetimeNoLeap(1993-07-02 12:00:00),
       cftime.DatetimeNoLeap(1994-07-02 12:00:00),
       cftime.DatetimeNoLeap(1995-07-02 12:00:00),
       cftime.DatetimeNoLeap(1996-07-02 12:00:00),
       cftime.DatetimeNoLeap(1997-07-02 12:00:00),
       cftime.DatetimeNoLeap(1998-07-02 12:00:00),
       cftime.DatetimeNoLeap(1999-07-02 12:00:00),
       cftime.DatetimeNoLeap(2000-07-02 12:00:00),
       cftime.DatetimeNoLeap(2001-07-02 12:00:00),
       cftime.DatetimeNoLeap(2002-07-02 12:00:00),
       cftime.DatetimeNoLeap(2003-07-02 12:00:00),
       cftime.DatetimeNoLeap(2004-07-02 12:00:00),
       cftime.DatetimeNoLeap(2005-07-02 12:00:00),
       cftime.DatetimeNoLeap(2006-07-02 12:00:00),
       cftime.DatetimeNoLeap(2007-07-02 12:00:00),
       cftime.DatetimeNoLeap(2008-07-02 12:00:00),
       cftime.DatetimeNoLeap(2009-07-02 12:00:00),
       cftime.DatetimeNoLeap(2010-07-02 12:00:00),
       cftime.DatetimeNoLeap(2011-07-02 12:00:00),
       cftime.DatetimeNoLeap(2012-07-02 12:00:00),
       cftime.DatetimeNoLeap(2013-07-02 12:00:00),
       cftime.DatetimeNoLeap(2014-07-02 12:00:00)], dtype=object)

i
(i)
int32
0 1 2 3 4 5 ... 355 356 357 358 359
long_name :
cell index along first dimension
units :
1
```
array([  0,   1,   2, ..., 357, 358, 359], dtype=int32)
```

lev

(lev)

float64

3.047 9.454 ... 5.375e+03 5.625e+03

axis :: Z
bounds :: lev_bnds
long_name :: ocean depth coordinate
positive :: down
standard_name :: depth
units :: m

array([3.046773e+00, 9.454049e+00, 1.636397e+01, 2.389871e+01, 3.220929e+01,
       4.148185e+01, 5.194513e+01, 6.387905e+01, 7.762451e+01, 9.359412e+01,
       1.122835e+02, 1.342823e+02, 1.602840e+02, 1.910925e+02, 2.276233e+02,
       2.708962e+02, 3.220169e+02, 3.821444e+02, 4.524429e+02, 5.340197e+02,
       6.278525e+02, 7.347150e+02, 8.551112e+02, 9.892289e+02, 1.136922e+03,
       1.297724e+03, 1.470893e+03, 1.655472e+03, 1.850365e+03, 2.054414e+03,
       2.266454e+03, 2.485371e+03, 2.710133e+03, 2.939812e+03, 3.173588e+03,
       3.410756e+03, 3.650712e+03, 3.892950e+03, 4.137047e+03, 4.382654e+03,
       4.629485e+03, 4.877303e+03, 5.125919e+03, 5.375177e+03, 5.624952e+03])

member_id

(member_id)

<U9

'r10i1p1f1' ... 'r9i1p2f1'

array(['r10i1p1f1', 'r10i1p2f1', 'r11i1p1f1', 'r12i1p1f1', 'r13i1p1f1',
       'r14i1p1f1', 'r15i1p1f1', 'r16i1p1f1', 'r17i1p1f1', 'r18i1p1f1',
       'r19i1p1f1', 'r1i1p1f1', 'r1i1p2f1', 'r20i1p1f1', 'r21i1p1f1',
       'r22i1p1f1', 'r23i1p1f1', 'r24i1p1f1', 'r25i1p1f1', 'r2i1p1f1',
       'r2i1p2f1', 'r3i1p1f1', 'r3i1p2f1', 'r4i1p1f1', 'r4i1p2f1', 'r5i1p1f1',
       'r5i1p2f1', 'r6i1p1f1', 'r6i1p2f1', 'r7i1p1f1', 'r7i1p2f1', 'r8i1p1f1',
       'r8i1p2f1', 'r9i1p1f1', 'r9i1p2f1'], dtype='<U9')

Data variables: (3)

vertices_latitude

(j, i, vertices)

float64

dask.array<chunksize=(291, 360, 4), meta=np.ndarray>

units :: degrees_north





  
      Array  Chunk 
  
  
     Bytes  3.35 MB   3.35 MB 
     Shape  (291, 360, 4)   (291, 360, 4) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

vertices_longitude

(j, i, vertices)

float64

dask.array<chunksize=(291, 360, 4), meta=np.ndarray>

units :: degrees_east





  
      Array  Chunk 
  
  
     Bytes  3.35 MB   3.35 MB 
     Shape  (291, 360, 4)   (291, 360, 4) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

(member_id, time, lev, j, i)

float32

dask.array<chunksize=(1, 12, 45, 291, 360), meta=np.ndarray>

cell_measures :: area: areacello volume: volcello
cell_methods :: area: mean where sea time: mean
comment :: 'Mole concentration' means number of moles per unit volume, also called 'molarity', and is used in the construction mole_concentration_of_X_in_Y, where X is a material constituent of Y. A chemical or biological species denoted by X may be described by a single term such as 'nitrogen' or a phrase such as 'nox_expressed_as_nitrogen'.
history :: meanm2y_mltby1em3
long_name :: Dissolved Oxygen Concentration
original_name :: O2
standard_name :: mole_concentration_of_dissolved_molecular_oxygen_in_sea_water
units :: mol m-3





  
      Array  Chunk 
  
  
     Bytes  108.90 GB   226.28 MB 
     Shape  (35, 165, 45, 291, 360)   (1, 12, 45, 291, 360) 
     Count  1505 Tasks  490 Chunks 
     Type  float32  numpy.ndarray

Attributes: (52)
contact :
ec.cccma.info-info.ccmac.ec@canada.ca
parent_activity_id :
CMIP
license :
CMIP6 model data produced by The Government of Canada (Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada) is licensed under a Creative Commons Attribution ShareAlike 4.0 International License (https://creativecommons.org/licenses). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and at https:///pcmdi.llnl.gov/. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.
intake_esm_varname :
o2
mip_era :
CMIP6
Conventions :
CF-1.7 CMIP-6.2
variable_id :
o2
version :
v20190429
source_type :
AOGCM
variant_label :
r9i1p2f1
table_id :
Oyr
external_variables :
areacello volcello
cmor_version :
3.4.0
references :
Geophysical Model Development Special issue on CanESM5 (https://www.geosci-model-dev.net/special_issues.html)
institution_id :
CCCma
forcing_index :
1
source :
CanESM5 (2019): aerosol: interactive atmos: CanAM5 (T63L49 native atmosphere, T63 Linear Gaussian Grid; 128 x 64 longitude/latitude; 49 levels; top level 1 hPa) atmosChem: specified oxidants for aerosols land: CLASS3.6/CTEM1.2 landIce: specified ice sheets ocean: NEMO3.4.1 (ORCA1 tripolar grid, 1 deg with refinement to 1/3 deg within 20 degrees of the equator; 361 x 290 longitude/latitude; 45 vertical levels; top grid cell 0-6.19 m) ocnBgchem: Canadian Model of Ocean Carbon (CMOC); NPZD ecosystem with OMIP prescribed carbonate chemistry seaIce: LIM2
realization_index :
9
CCCma_parent_runid :
p2-pictrl
tracking_id :
hdl:21.14100/41426118-701c-482b-ae16-82932e459080 hdl:21.14100/eec166d5-9295-4804-8d89-84aba920b811 hdl:21.14100/f0f2847d-bbce-4736-896a-f9e3cbb0e0c3 hdl:21.14100/b74e3b07-ed7b-43b3-976f-3b4a55c5e175 hdl:21.14100/13d7408e-82f9-4a16-8df4-566be14a3a98 hdl:21.14100/61cf3578-a156-42ed-bcae-b7f40ad10006 hdl:21.14100/c6962c8d-fa1f-4a37-a9b5-9b582f4a3e6b hdl:21.14100/8f2d67cc-cc88-411f-a1d2-4ef8e750680b hdl:21.14100/0831d083-1a2a-4458-ad36-45d147602204 hdl:21.14100/d33a8318-1b3c-45e5-8a11-da0ef4ecf843 hdl:21.14100/016fd306-f6da-4738-958e-bea744adfaf3 hdl:21.14100/20a231ca-ffe0-442b-b108-482157972ed4 hdl:21.14100/6bf5ab72-1e53-49d6-811b-77d0fa3ae243 hdl:21.14100/aa79d225-29ee-45cb-801f-3a76c1f86c4d hdl:21.14100/6fc32405-158a-4de6-b4b4-658e333e503f hdl:21.14100/17b8cc29-f5c9-4288-98f1-eb4bcd94c53b hdl:21.14100/d89491b9-6c8e-4e5e-850c-0617b735b70e hdl:21.14100/ef1f08a7-cc33-4e95-8dbb-d477d3b47453 hdl:21.14100/39a9a206-c798-4f74-a776-d8fba0a27211 hdl:21.14100/b82755e0-528f-4eec-93b8-f448144863e2 hdl:21.14100/7c231895-a470-48a3-962a-e398b0a74e00 hdl:21.14100/82cd73fd-2af7-4c7e-9fc2-fa4f7fca96cd hdl:21.14100/af60d07f-a4e8-4e2e-a8c9-2751869d09e7 hdl:21.14100/9d312870-1e23-40a4-9fd0-d7e057eecd89 hdl:21.14100/ef98f4e6-4eb5-4177-9b82-988d6ab51316 hdl:21.14100/cc1b9d02-bc6f-4ee4-b81e-8da5b4807169 hdl:21.14100/76dfee08-3aae-446d-8199-6f0e1174a3d4 hdl:21.14100/a9e89083-8b09-445e-888f-86179165d14c hdl:21.14100/fe25b1d7-1d16-4871-a0e9-4f469844e106 hdl:21.14100/02053d4c-4bda-486b-9853-998ac4ed41ae hdl:21.14100/75e52ad8-bc26-4153-ab02-cde78cf88355 hdl:21.14100/089723f9-e9f3-4bb2-b5fb-caf37cd987b7 hdl:21.14100/9347e50e-bcdc-47c6-9d58-d18bd90f00d9 hdl:21.14100/6c06e2a5-0005-46c4-9753-d20fb161abb4 hdl:21.14100/d6d1a7a2-41cc-419c-a912-3bafa10e2c01
initialization_index :
1
branch_method :
Spin-up documentation
status :
2019-10-25;created;by nhn2@columbia.edu
table_info :
Creation Date:(20 February 2019) MD5:374fbe5a2bcca535c40f7f23da271e49
activity_id :
CMIP
YMDH_branch_time_in_parent :
5950:01:01:00
creation_date :
2019-05-30T08:58:45Z
product :
model-output
YMDH_branch_time_in_child :
1850:01:01:00
frequency :
yr
data_specs_version :
01.00.29
experiment :
all-forcing simulation of the recent past
CCCma_model_hash :
Unknown
branch_time_in_parent :
1496500.0
institution :
Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC V8P 5C2, Canada
parent_source_id :
CanESM5
sub_experiment_id :
none
nominal_resolution :
100 km
parent_experiment_id :
piControl
further_info_url :
https://furtherinfo.es-doc.org/CMIP6.CCCma.CanESM5.historical.none.r9i1p2f1
source_id :
CanESM5
history :
2019-05-02T13:53:53Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-30T08:58:40Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr. 2019-05-02T13:55:44Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-02T13:55:48Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-02T13:57:46Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-02T13:57:48Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-02T13:59:47Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-02T14:03:56Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-02T14:03:56Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-02T14:05:56Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-02T14:05:59Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-02T13:43:39Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-09T03:45:13Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-02T14:08:04Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-01T20:20:11Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-01T20:23:33Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-01T20:26:53Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-01T20:30:19Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-01T20:33:43Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-02T13:47:48Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-03T22:15:10Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-01T20:03:35Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-09T03:45:41Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-01T20:06:50Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-09T03:46:25Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-02T13:47:47Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-09T03:52:34Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-01T20:11:36Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-09T03:53:05Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-01T20:13:32Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-30T08:58:34Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr. 2019-05-02T13:49:43Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-30T08:58:24Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr. 2019-05-01T20:16:55Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.; Output from $runid 2019-05-30T08:58:45Z ;rewrote data to be consistent with CMIP for variable o2 found in table Oyr.
CCCma_runid :
p2-his09
grid_label :
gn
title :
CanESM5 output prepared for CMIP6
parent_time_units :
days since 1850-01-01 0:0:0.0
grid :
ORCA1 tripolar grid, 1 deg with refinement to 1/3 deg within 20 degrees of the equator; 361 x 290 longitude/latitude; 45 vertical levels; top grid cell 0-6.19 m
experiment_id :
historical
branch_time_in_child :
0.0
sub_experiment :
none
realm :
ocnBgchem
parent_mip_era :
CMIP6