CMCC-CM model output prepared for CMIP5 historical
Load in Python
from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/snw_LImon_CMCC-CM_historical_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | CMCC-CM model output prepared for CMIP5 historical |
| location | /shared/cmip5/data/historical/landIce/mon/LImon/snw/CMCC.CMCC-CM/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/snw_LImon_CMCC-CM_historical_r1i1p1.yaml |
| last updated | 2013-06-14 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, lat: 240, lon: 480, time: 1872)
Coordinates:
* time (time) float64 15.5 45.0 74.5 ... 2.116e+03 2.146e+03 2.176e+03
* lat (lat) float64 -89.43 -88.68 -87.94 -87.19 ... 87.94 88.68 89.43
* lon (lon) float64 0.0 0.75 1.5 2.25 3.0 ... 357.0 357.8 358.5 359.2
Dimensions without coordinates: bnds
Data variables:
time_bnds (time, bnds) float64 dask.array<chunksize=(120, 2), meta=np.ndarray>
lat_bnds (time, lat, bnds) float64 dask.array<chunksize=(120, 240, 2), meta=np.ndarray>
lon_bnds (time, lon, bnds) float64 dask.array<chunksize=(120, 480, 2), meta=np.ndarray>
snw (time, lat, lon) float32 dask.array<chunksize=(120, 240, 480), meta=np.ndarray>
Attributes:
institution: CMCC - Centro Euro-Mediterraneo per i Cambiamenti
institute_id: CMCC
experiment_id: historical
source: CMCC-CM
model_id: CMCC-CM
forcing: Nat,Ant,GHG,SA,TO,Sl
parent_experiment_id: piControl
parent_experiment_rip: N/A
branch_time: 109562.0
contact: Silvio Gualdi (gualdi@bo.ingv.it)
history: Model output postprocessed with CDO 2011-11-30T13...
comment: simulation starting at the end of the piControl r...
references: model described in the documentation at http://ww...
initialization_method: 1
physics_version: 1
tracking_id: 203e5975-051d-4121-bda8-4b3ccba09079
product: output
experiment: historical
frequency: mon
creation_date: 2011-11-30T13:23:24Z
Conventions: CF-1.4
project_id: CMIP5
table_id: Table LImon (27 April 2011) 5a70adac85c24b52fe62c...
title: CMCC-CM model output prepared for CMIP5 historical
parent_experiment: pre-industrial control
modeling_realm: landIce land
realization: 1
cmor_version: 2.7.1xarray.Dataset
- bnds: 2
- lat: 240
- lon: 480
- time: 1872
- time(time)float6415.5 45.0 ... 2.146e+03 2.176e+03
- bounds :
- time_bnds
- calendar :
- standard
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([ 15.5, 45. , 74.5, ..., 2115.5, 2146. , 2176.5])
- lat(lat)float64-89.43 -88.68 ... 88.68 89.43
- bounds :
- lat_bnds
- units :
- degrees_north
- axis :
- Y
- long_name :
- latitude
- standard_name :
- latitude
array([-89.427084, -88.684919, -87.938371, ..., 87.938371, 88.684919, 89.427084]) - lon(lon)float640.0 0.75 1.5 ... 357.8 358.5 359.2
- bounds :
- lon_bnds
- units :
- degrees_east
- axis :
- X
- long_name :
- longitude
- standard_name :
- longitude
array([ 0. , 0.75, 1.5 , ..., 357.75, 358.5 , 359.25])
- time_bnds(time, bnds)float64dask.array<chunksize=(120, 2), meta=np.ndarray>
Array Chunk Bytes 29.95 kB 1.92 kB Shape (1872, 2) (120, 2) Count 48 Tasks 16 Chunks Type float64 numpy.ndarray - lat_bnds(time, lat, bnds)float64dask.array<chunksize=(120, 240, 2), meta=np.ndarray>
Array Chunk Bytes 7.19 MB 460.80 kB Shape (1872, 240, 2) (120, 240, 2) Count 64 Tasks 16 Chunks Type float64 numpy.ndarray - lon_bnds(time, lon, bnds)float64dask.array<chunksize=(120, 480, 2), meta=np.ndarray>
Array Chunk Bytes 14.38 MB 921.60 kB Shape (1872, 480, 2) (120, 480, 2) Count 64 Tasks 16 Chunks Type float64 numpy.ndarray - snw(time, lat, lon)float32dask.array<chunksize=(120, 240, 480), meta=np.ndarray>
- standard_name :
- surface_snow_amount
- long_name :
- Surface Snow Amount
- comment :
- Computed as the mass of surface snow on the land portion of the grid cell divided by the land area in the grid cell; reported as 0.0 where the land fraction is 0; excluded is snow on vegetation canopy or on sea ice.
- units :
- kg m-2
- original_name :
- snw
- cell_methods :
- time: mean (interval: 1 month) area: mean where land
- cell_measures :
- area: areacella
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_landIce_fx_CMCC-CM_historical_r0i0p0.nc areacella: areacella_fx_CMCC-CM_historical_r0i0p0.nc
- history :
- 2011-11-30T13:23:24Z altered by CMOR: Inverted axis: lat.
Array Chunk Bytes 862.62 MB 55.30 MB Shape (1872, 240, 480) (120, 240, 480) Count 48 Tasks 16 Chunks Type float32 numpy.ndarray
- institution :
- CMCC - Centro Euro-Mediterraneo per i Cambiamenti
- institute_id :
- CMCC
- experiment_id :
- historical
- source :
- CMCC-CM
- model_id :
- CMCC-CM
- forcing :
- Nat,Ant,GHG,SA,TO,Sl
- parent_experiment_id :
- piControl
- parent_experiment_rip :
- N/A
- branch_time :
- 109562.0
- contact :
- Silvio Gualdi (gualdi@bo.ingv.it)
- history :
- Model output postprocessed with CDO 2011-11-30T13:23:24Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- comment :
- simulation starting at the end of the piControl run, thus after 600+300=900 years spin-up at pre-industrial GHG concentrations
- references :
- model described in the documentation at http://www.cmcc.it/data-models/models
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- 203e5975-051d-4121-bda8-4b3ccba09079
- product :
- output
- experiment :
- historical
- frequency :
- mon
- creation_date :
- 2011-11-30T13:23:24Z
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table LImon (27 April 2011) 5a70adac85c24b52fe62c758c1dca0e5
- title :
- CMCC-CM model output prepared for CMIP5 historical
- parent_experiment :
- pre-industrial control
- modeling_realm :
- landIce land
- realization :
- 1
- cmor_version :
- 2.7.1