NorESM2-MM output prepared for CMIP6

Load in Python

from intake import open_catalog

cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/siconc_SImon_NorESM2-MM_piControl_r1i1p1f1_gn.yaml")
ds=cat.netcdf.read()

Metadata

title	NorESM2-MM output prepared for CMIP6
location	/shared/cmip6/data/piControl/seaIce/mon/OImon/siconc/NCC.NorESM2-MM/r1i1p1
tags	gridded,global,model,monthly
catalog_dir	https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/siconc_SImon_NorESM2-MM_piControl_r1i1p1f1_gn.yaml
last updated	2020-10-23

Dataset Contents

<xarray.Dataset>
Dimensions:             (bnds: 2, i: 360, j: 384, time: 6000, vertices: 4)
Coordinates:
  * time                (time) float64 4.377e+05 4.377e+05 ... 6.201e+05
  * j                   (j) int32 1 2 3 4 5 6 7 ... 378 379 380 381 382 383 384
  * i                   (i) int32 1 2 3 4 5 6 7 ... 354 355 356 357 358 359 360
    latitude            (j, i) float64 dask.array<chunksize=(384, 360), meta=np.ndarray>
    longitude           (j, i) float64 dask.array<chunksize=(384, 360), meta=np.ndarray>
    type                |S7 b'sea_ice'
Dimensions without coordinates: bnds, vertices
Data variables:
    time_bnds           (time, bnds) float64 dask.array<chunksize=(120, 2), meta=np.ndarray>
    vertices_latitude   (time, j, i, vertices) float64 dask.array<chunksize=(120, 384, 360, 4), meta=np.ndarray>
    vertices_longitude  (time, j, i, vertices) float64 dask.array<chunksize=(120, 384, 360, 4), meta=np.ndarray>
    siconc              (time, j, i) float32 dask.array<chunksize=(120, 384, 360), meta=np.ndarray>
Attributes:
    Conventions:               CF-1.7 CMIP-6.2
    activity_id:               CMIP
    branch_method:             Hybrid-restart from year 1200-01-01 of piContr...
    branch_time:               0.0
    branch_time_in_child:      0.0
    branch_time_in_parent:     438000.0
    contact:                   Please send any requests or bug reports to nor...
    creation_date:             2019-11-22T12:21:42Z
    data_specs_version:        01.00.31
    experiment:                pre-industrial control
    experiment_id:             piControl
    external_variables:        areacello
    forcing_index:             1
    frequency:                 mon
    further_info_url:          https://furtherinfo.es-doc.org/CMIP6.NCC.NorES...
    grid:                      tripolar grid with 1deg nominal resolution
    grid_label:                gn
    history:                   2019-11-22T12:21:42Z ; CMOR rewrote data to be...
    initialization_index:      1
    institution:               NorESM Climate modeling Consortium consisting ...
    institution_id:            NCC
    mip_era:                   CMIP6
    model_id:                  NorESM2-MM
    nominal_resolution:        100 km
    parent_activity_id:        CMIP
    parent_experiment_id:      piControl-spinup
    parent_mip_era:            CMIP6
    parent_source_id:          NorESM2-MM
    parent_sub_experiment_id:  none
    parent_time_units:         days since 0001-01-01
    parent_variant_label:      r1i1p1f1
    physics_index:             1
    product:                   model-output
    realization_index:         1
    realm:                     seaIce
    run_variant:               N/A
    source:                    NorESM2-MM (2017): 
aerosol: OsloAero
atmos:...
    source_id:                 NorESM2-MM
    source_type:               AOGCM AER BGC
    sub_experiment:            none
    sub_experiment_id:         none
    table_id:                  SImon
    table_info:                Creation Date:(24 July 2019) MD5:0bb394a356ef9...
    title:                     NorESM2-MM output prepared for CMIP6
    variable_id:               siconc
    variant_label:             r1i1p1f1
    license:                   CMIP6 model data produced by NCC is licensed u...
    cmor_version:              3.5.0
    tracking_id:               hdl:21.14100/579caf5c-ecf9-4fb8-9594-2fbf1a30eecb

xarray.Dataset

Dimensions:
- bnds: 2
- i: 360
- j: 384
- time: 6000
- vertices: 4

Coordinates: (6)

time
(time)
float64
4.377e+05 4.377e+05 ... 6.201e+05
bounds :
time_bnds
units :
days since 0001-01-01 00:00:00
calendar :
noleap
axis :
T
long_name :
time
standard_name :
time
```
array([437650.5, 437680. , 437709.5, ..., 620058.5, 620089. , 620119.5])
```
j
(j)
int32
1 2 3 4 5 6 ... 380 381 382 383 384
units :
1
long_name :
cell index along second dimension
```
array([  1,   2,   3, ..., 382, 383, 384], dtype=int32)
```
i
(i)
int32
1 2 3 4 5 6 ... 356 357 358 359 360
units :
1
long_name :
cell index along first dimension
```
array([  1,   2,   3, ..., 358, 359, 360], dtype=int32)
```

latitude

(j, i)

float64

dask.array<chunksize=(384, 360), meta=np.ndarray>

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

	Array	Chunk
Bytes	1.11 MB	1.11 MB
Shape	(384, 360)	(384, 360)
Count	245 Tasks	1 Chunks
Type	float64	numpy.ndarray

longitude

(j, i)

float64

dask.array<chunksize=(384, 360), meta=np.ndarray>

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

	Array	Chunk
Bytes	1.11 MB	1.11 MB
Shape	(384, 360)	(384, 360)
Count	245 Tasks	1 Chunks
Type	float64	numpy.ndarray

type
()
|S7
b'sea_ice'
long_name :
Sea Ice area type
standard_name :
area_type
```
array(b'sea_ice', dtype='|S7')
```

Data variables: (4)

time_bnds

(time, bnds)

float64

dask.array<chunksize=(120, 2), meta=np.ndarray>

	Array	Chunk
Bytes	96.00 kB	1.92 kB
Shape	(6000, 2)	(120, 2)
Count	150 Tasks	50 Chunks
Type	float64	numpy.ndarray

vertices_latitude

(time, j, i, vertices)

float64

dask.array<chunksize=(120, 384, 360, 4), meta=np.ndarray>

units :: degrees_north

	Array	Chunk
Bytes	26.54 GB	530.84 MB
Shape	(6000, 384, 360, 4)	(120, 384, 360, 4)
Count	200 Tasks	50 Chunks
Type	float64	numpy.ndarray

vertices_longitude

(time, j, i, vertices)

float64

dask.array<chunksize=(120, 384, 360, 4), meta=np.ndarray>

units :: degrees_east

	Array	Chunk
Bytes	26.54 GB	530.84 MB
Shape	(6000, 384, 360, 4)	(120, 384, 360, 4)
Count	200 Tasks	50 Chunks
Type	float64	numpy.ndarray

siconc

(time, j, i)

float32

dask.array<chunksize=(120, 384, 360), meta=np.ndarray>

standard_name :: sea_ice_area_fraction
long_name :: Sea-Ice Area Percentage (Ocean Grid)
comment :: Percentage of grid cell covered by sea ice
units :: %
original_name :: aice
original_units :: 1
history :: 2019-11-22T12:21:42Z altered by CMOR: Converted units from '1' to '%'. 2019-11-22T12:21:42Z altered by CMOR: Treated scalar dimension: 'type'. 2019-11-22T12:21:42Z altered by CMOR: Converted type from 'd' to 'f'.
cell_methods :: area: mean where sea time: mean
cell_measures :: area: areacello

	Array	Chunk
Bytes	3.32 GB	66.36 MB
Shape	(6000, 384, 360)	(120, 384, 360)
Count	150 Tasks	50 Chunks
Type	float32	numpy.ndarray

Attributes: (49)
Conventions :
CF-1.7 CMIP-6.2
activity_id :
CMIP
branch_method :
Hybrid-restart from year 1200-01-01 of piControl-spinup
branch_time :
0.0
branch_time_in_child :
0.0
branch_time_in_parent :
438000.0
contact :
Please send any requests or bug reports to noresm-ncc@met.no.
creation_date :
2019-11-22T12:21:42Z
data_specs_version :
01.00.31
experiment :
pre-industrial control
experiment_id :
piControl
external_variables :
areacello
forcing_index :
1
frequency :
mon
further_info_url :
https://furtherinfo.es-doc.org/CMIP6.NCC.NorESM2-MM.piControl.none.r1i1p1f1
grid :
tripolar grid with 1deg nominal resolution
grid_label :
gn
history :
2019-11-22T12:21:42Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.
initialization_index :
1
institution :
NorESM Climate modeling Consortium consisting of CICERO (Center for International Climate and Environmental Research, Oslo 0349), MET-Norway (Norwegian Meteorological Institute, Oslo 0313), NERSC (Nansen Environmental and Remote Sensing Center, Bergen 5006), NILU (Norwegian Institute for Air Research, Kjeller 2027), UiB (University of Bergen, Bergen 5007), UiO (University of Oslo, Oslo 0313) and UNI (Uni Research, Bergen 5008), Norway. Mailing address: NCC, c/o MET-Norway, Henrik Mohns plass 1, Oslo 0313, Norway
institution_id :
NCC
mip_era :
CMIP6
model_id :
NorESM2-MM
nominal_resolution :
100 km
parent_activity_id :
CMIP
parent_experiment_id :
piControl-spinup
parent_mip_era :
CMIP6
parent_source_id :
NorESM2-MM
parent_sub_experiment_id :
none
parent_time_units :
days since 0001-01-01
parent_variant_label :
r1i1p1f1
physics_index :
1
product :
model-output
realization_index :
1
realm :
seaIce
run_variant :
N/A
source :
NorESM2-MM (2017): aerosol: OsloAero atmos: CAM-OSLO (1 degree resolution; 288 x 192; 32 levels; top level 3 mb) atmosChem: OsloChemSimp land: CLM landIce: CISM ocean: MICOM (1 degree resolution; 360 x 384; 70 levels; top grid cell minimum 0-2.5 m [native model uses hybrid density and generic upper-layer coordinate interpolated to z-level for contributed data]) ocnBgchem: HAMOCC seaIce: CICE
source_id :
NorESM2-MM
source_type :
AOGCM AER BGC
sub_experiment :
none
sub_experiment_id :
none
table_id :
SImon
table_info :
Creation Date:(24 July 2019) MD5:0bb394a356ef9d214d027f1aca45853e
title :
NorESM2-MM output prepared for CMIP6
variable_id :
siconc
variant_label :
r1i1p1f1
license :
CMIP6 model data produced by NCC 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.
cmor_version :
3.5.0
tracking_id :
hdl:21.14100/579caf5c-ecf9-4fb8-9594-2fbf1a30eecb