CMCC-CM2-SR5 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_CMCC-CM2-SR5_piControl_r1i1p1f1_gn.yaml")
ds=cat.netcdf.read()
Metadata
title | CMCC-CM2-SR5 output prepared for CMIP6 |
location | /shared/cmip6/data/piControl/seaIce/mon/OImon/siconc/CMCC-CM2-SR5/r1i1p1 |
tags | gridded,global,model,monthly |
catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/siconc_SImon_CMCC-CM2-SR5_piControl_r1i1p1f1_gn.yaml |
last updated | 2020-09-29 |
Dataset Contents
<xarray.Dataset> Dimensions: (bnds: 2, i: 291, j: 360, time: 6000, vertices: 4) Coordinates: * time (time) float64 15.5 45.0 74.5 ... 1.825e+05 1.825e+05 * i (i) int32 0 1 2 3 4 5 6 ... 284 285 286 287 288 289 290 * j (j) int32 0 1 2 3 4 5 6 ... 353 354 355 356 357 358 359 latitude (i, j) float64 dask.array<chunksize=(291, 360), meta=np.ndarray> longitude (i, j) float64 dask.array<chunksize=(291, 360), meta=np.ndarray> type |S7 b'sea_ice' Dimensions without coordinates: bnds, vertices Data variables: time_bnds (time, bnds) float64 dask.array<chunksize=(3000, 2), meta=np.ndarray> vertices_latitude (time, i, j, vertices) float64 dask.array<chunksize=(3000, 291, 360, 4), meta=np.ndarray> vertices_longitude (time, i, j, vertices) float64 dask.array<chunksize=(3000, 291, 360, 4), meta=np.ndarray> siconc (time, i, j) float32 dask.array<chunksize=(3000, 291, 360), meta=np.ndarray> Attributes: Conventions: CF-1.7 CMIP-6.2 activity_id: CMIP branch_method: standard branch_time_in_child: 0.0 branch_time_in_parent: 0.0 comment: none contact: T. Lovato creation_date: 2020-06-09T15:27:42Z 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.CMCC.CMCC-CM... grid: native seaice curvilinear grid grid_label: gn history: 2020-06-09T15:27:42Z ;rewrote data to be consiste... initialization_index: 1 institution: Fondazione Centro Euro-Mediterraneo sui Cambiamen... institution_id: CMCC mip_era: CMIP6 nominal_resolution: 100 km parent_activity_id: CMIP parent_experiment_id: piControl-spinup parent_mip_era: CMIP6 parent_source_id: CMCC-CM2-SR5 parent_time_units: days since 1850-01-01 parent_variant_label: r1i1p1f1 physics_index: 1 product: model-output realization_index: 1 realm: seaIce references: none run_variant: 1st realization source: CMCC-CM2-SR5 (2016): aerosol: MAM3 atmos: CAM5... source_id: CMCC-CM2-SR5 source_type: AOGCM sub_experiment: none sub_experiment_id: none table_id: SImon table_info: Creation Date:(05 February 2020) MD5:6a248fd76c55... title: CMCC-CM2-SR5 output prepared for CMIP6 variable_id: siconc variant_label: r1i1p1f1 license: CMIP6 model data produced by CMCC is licensed und... cmor_version: 3.5.0 tracking_id: hdl:21.14100/25c7f954-970d-4902-9819-13b8d7b4ea12
xarray.Dataset
- bnds: 2
- i: 291
- j: 360
- time: 6000
- vertices: 4
- time(time)float6415.5 45.0 ... 1.825e+05 1.825e+05
- bounds :
- time_bnds
- units :
- days since 1850-01-01
- 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])
- i(i)int320 1 2 3 4 5 ... 286 287 288 289 290
- units :
- 1
- long_name :
- first spatial index for variables stored on an unstructured grid
array([ 0, 1, 2, ..., 288, 289, 290], dtype=int32)
- j(j)int320 1 2 3 4 5 ... 355 356 357 358 359
- units :
- 1
- long_name :
- second spatial index for variables stored on an unstructured grid
array([ 0, 1, 2, ..., 357, 358, 359], dtype=int32)
- latitude(i, j)float64dask.array<chunksize=(291, 360), meta=np.ndarray>
- standard_name :
- latitude
- long_name :
- latitude
- units :
- degrees_north
- bounds :
- vertices_latitude
Array Chunk Bytes 838.08 kB 838.08 kB Shape (291, 360) (291, 360) Count 5 Tasks 1 Chunks Type float64 numpy.ndarray - longitude(i, j)float64dask.array<chunksize=(291, 360), meta=np.ndarray>
- standard_name :
- longitude
- long_name :
- longitude
- units :
- degrees_east
- bounds :
- vertices_longitude
Array Chunk Bytes 838.08 kB 838.08 kB Shape (291, 360) (291, 360) Count 5 Tasks 1 Chunks Type float64 numpy.ndarray - type()|S7b'sea_ice'
- long_name :
- Sea Ice area type
- standard_name :
- area_type
array(b'sea_ice', dtype='|S7')
- time_bnds(time, bnds)float64dask.array<chunksize=(3000, 2), meta=np.ndarray>
Array Chunk Bytes 96.00 kB 48.00 kB Shape (6000, 2) (3000, 2) Count 6 Tasks 2 Chunks Type float64 numpy.ndarray - vertices_latitude(time, i, j, vertices)float64dask.array<chunksize=(3000, 291, 360, 4), meta=np.ndarray>
- units :
- degrees_north
Array Chunk Bytes 20.11 GB 10.06 GB Shape (6000, 291, 360, 4) (3000, 291, 360, 4) Count 8 Tasks 2 Chunks Type float64 numpy.ndarray - vertices_longitude(time, i, j, vertices)float64dask.array<chunksize=(3000, 291, 360, 4), meta=np.ndarray>
- units :
- degrees_east
Array Chunk Bytes 20.11 GB 10.06 GB Shape (6000, 291, 360, 4) (3000, 291, 360, 4) Count 8 Tasks 2 Chunks Type float64 numpy.ndarray - siconc(time, i, j)float32dask.array<chunksize=(3000, 291, 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
- cell_methods :
- area: mean where sea time: mean
- cell_measures :
- area: areacello
- history :
- 2020-06-09T15:27:35Z altered by CMOR: Treated scalar dimension: 'type'.
Array Chunk Bytes 2.51 GB 1.26 GB Shape (6000, 291, 360) (3000, 291, 360) Count 6 Tasks 2 Chunks Type float32 numpy.ndarray
- Conventions :
- CF-1.7 CMIP-6.2
- activity_id :
- CMIP
- branch_method :
- standard
- branch_time_in_child :
- 0.0
- branch_time_in_parent :
- 0.0
- comment :
- none
- contact :
- T. Lovato
- creation_date :
- 2020-06-09T15:27:42Z
- 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.CMCC.CMCC-CM2-SR5.piControl.none.r1i1p1f1
- grid :
- native seaice curvilinear grid
- grid_label :
- gn
- history :
- 2020-06-09T15:27:42Z ;rewrote data to be consistent with CMIP for variable siconc found in table SImon.; none
- initialization_index :
- 1
- institution :
- Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy
- institution_id :
- CMCC
- mip_era :
- CMIP6
- nominal_resolution :
- 100 km
- parent_activity_id :
- CMIP
- parent_experiment_id :
- piControl-spinup
- parent_mip_era :
- CMIP6
- parent_source_id :
- CMCC-CM2-SR5
- parent_time_units :
- days since 1850-01-01
- parent_variant_label :
- r1i1p1f1
- physics_index :
- 1
- product :
- model-output
- realization_index :
- 1
- realm :
- seaIce
- references :
- none
- run_variant :
- 1st realization
- source :
- CMCC-CM2-SR5 (2016): aerosol: MAM3 atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa) atmosChem: none land: CLM4.5 (BGC mode) landIce: none ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m) ocnBgchem: none seaIce: CICE4.0
- source_id :
- CMCC-CM2-SR5
- source_type :
- AOGCM
- sub_experiment :
- none
- sub_experiment_id :
- none
- table_id :
- SImon
- table_info :
- Creation Date:(05 February 2020) MD5:6a248fd76c55aa6d6f7b3cc6866b5faf
- title :
- CMCC-CM2-SR5 output prepared for CMIP6
- variable_id :
- siconc
- variant_label :
- r1i1p1f1
- license :
- CMIP6 model data produced by CMCC 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:21.14100/25c7f954-970d-4902-9819-13b8d7b4ea12