CanESM2 model output prepared for CMIP5 pre-industrial control

Load in Python

from intake import open_catalog

cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/snd_LImon_CanESM2_piControl_r1i1p1.yaml")
ds=cat.netcdf.read()

Metadata

title	CanESM2 model output prepared for CMIP5 pre-industrial control
location	/shared/cmip5/data/piControl/landIce/mon/LImon/snd/CCCma.CanESM2/r1i1p1
tags	gridded,global,model,monthly
catalog_dir	https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/snd_LImon_CanESM2_piControl_r1i1p1.yaml
last updated	2013-06-14

Dataset Contents

<xarray.Dataset>
Dimensions:    (bnds: 2, lat: 64, lon: 128, time: 11952)
Coordinates:
  * time       (time) float64 6.024e+04 6.027e+04 ... 4.237e+05 4.237e+05
  * lat        (lat) float64 -87.86 -85.1 -82.31 -79.53 ... 82.31 85.1 87.86
  * lon        (lon) float64 0.0 2.812 5.625 8.438 ... 348.8 351.6 354.4 357.2
Dimensions without coordinates: bnds
Data variables:
    time_bnds  (time, bnds) float64 dask.array<chunksize=(3552, 2), meta=np.ndarray>
    lat_bnds   (time, lat, bnds) float64 dask.array<chunksize=(3552, 64, 2), meta=np.ndarray>
    lon_bnds   (time, lon, bnds) float64 dask.array<chunksize=(3552, 128, 2), meta=np.ndarray>
    snd        (time, lat, lon) float32 dask.array<chunksize=(3552, 64, 128), meta=np.ndarray>
Attributes:
    institution:            CCCma (Canadian Centre for Climate Modelling and ...
    institute_id:           CCCma
    experiment_id:          piControl
    source:                 CanESM2 2010 atmosphere: CanAM4 (AGCM15i, T63L35)...
    model_id:               CanESM2
    forcing:                N/A
    parent_experiment_id:   N/A
    parent_experiment_rip:  N/A
    branch_time:            0.0
    contact:                cccma_info@ec.gc.ca
    references:             http://www.cccma.ec.gc.ca/models
    initialization_method:  1
    physics_version:        1
    tracking_id:            09cb9a5a-824a-453e-8d2f-dd1ac1169a95
    branch_time_YMDH:       2015:01:01:00
    CCCma_runid:            IGA
    CCCma_parent_runid:     IBA
    CCCma_data_licence:     1) GRANT OF LICENCE - The Government of Canada (E...
    product:                output
    experiment:             pre-industrial control
    frequency:              mon
    creation_date:          2011-03-17T21:53:26Z
    history:                2011-03-17T21:53:26Z CMOR rewrote data to comply ...
    Conventions:            CF-1.4
    project_id:             CMIP5
    table_id:               Table LImon (31 January 2011) 6f05b7e5f64aaa34bca...
    title:                  CanESM2 model output prepared for CMIP5 pre-indus...
    parent_experiment:      N/A
    modeling_realm:         landIce land
    realization:            1
    cmor_version:           2.5.4

xarray.Dataset

Dimensions:
- bnds: 2
- lat: 64
- lon: 128
- time: 11952

Coordinates: (3)

time
(time)
float64
6.024e+04 6.027e+04 ... 4.237e+05
bounds :
time_bnds
units :
days since 1850-1-1
calendar :
365_day
axis :
T
long_name :
time
standard_name :
time
```
array([ 60240.5,  60270. ,  60299.5, ..., 423688.5, 423719. , 423749.5])
```

lat

(lat)

float64

-87.86 -85.1 -82.31 ... 85.1 87.86

bounds :: lat_bnds
units :: degrees_north
axis :: Y
long_name :: latitude
standard_name :: latitude

array([-87.863801, -85.096529, -82.312915, -79.525609, -76.736902, -73.947518,
       -71.157755, -68.367759, -65.57761 , -62.787354, -59.997023, -57.206634,
       -54.416202, -51.625736, -48.835243, -46.044729, -43.254197, -40.463651,
       -37.673092, -34.882523, -32.091946, -29.301362, -26.510772, -23.720176,
       -20.929577, -18.138973, -15.348367, -12.557759,  -9.767148,  -6.976536,
        -4.185923,  -1.395309,   1.395309,   4.185923,   6.976536,   9.767148,
        12.557759,  15.348367,  18.138973,  20.929577,  23.720176,  26.510772,
        29.301362,  32.091946,  34.882523,  37.673092,  40.463651,  43.254197,
        46.044729,  48.835243,  51.625736,  54.416202,  57.206634,  59.997023,
        62.787354,  65.57761 ,  68.367759,  71.157755,  73.947518,  76.736902,
        79.525609,  82.312915,  85.096529,  87.863801])

lon

(lon)

float64

0.0 2.812 5.625 ... 354.4 357.2

bounds :: lon_bnds
units :: degrees_east
axis :: X
long_name :: longitude
standard_name :: longitude

array([  0.    ,   2.8125,   5.625 ,   8.4375,  11.25  ,  14.0625,  16.875 ,
        19.6875,  22.5   ,  25.3125,  28.125 ,  30.9375,  33.75  ,  36.5625,
        39.375 ,  42.1875,  45.    ,  47.8125,  50.625 ,  53.4375,  56.25  ,
        59.0625,  61.875 ,  64.6875,  67.5   ,  70.3125,  73.125 ,  75.9375,
        78.75  ,  81.5625,  84.375 ,  87.1875,  90.    ,  92.8125,  95.625 ,
        98.4375, 101.25  , 104.0625, 106.875 , 109.6875, 112.5   , 115.3125,
       118.125 , 120.9375, 123.75  , 126.5625, 129.375 , 132.1875, 135.    ,
       137.8125, 140.625 , 143.4375, 146.25  , 149.0625, 151.875 , 154.6875,
       157.5   , 160.3125, 163.125 , 165.9375, 168.75  , 171.5625, 174.375 ,
       177.1875, 180.    , 182.8125, 185.625 , 188.4375, 191.25  , 194.0625,
       196.875 , 199.6875, 202.5   , 205.3125, 208.125 , 210.9375, 213.75  ,
       216.5625, 219.375 , 222.1875, 225.    , 227.8125, 230.625 , 233.4375,
       236.25  , 239.0625, 241.875 , 244.6875, 247.5   , 250.3125, 253.125 ,
       255.9375, 258.75  , 261.5625, 264.375 , 267.1875, 270.    , 272.8125,
       275.625 , 278.4375, 281.25  , 284.0625, 286.875 , 289.6875, 292.5   ,
       295.3125, 298.125 , 300.9375, 303.75  , 306.5625, 309.375 , 312.1875,
       315.    , 317.8125, 320.625 , 323.4375, 326.25  , 329.0625, 331.875 ,
       334.6875, 337.5   , 340.3125, 343.125 , 345.9375, 348.75  , 351.5625,
       354.375 , 357.1875])

Data variables: (4)

time_bnds

(time, bnds)

float64

dask.array<chunksize=(3552, 2), meta=np.ndarray>

	Array	Chunk
Bytes	191.23 kB	56.83 kB
Shape	(11952, 2)	(3552, 2)
Count	24 Tasks	8 Chunks
Type	float64	numpy.ndarray

lat_bnds

(time, lat, bnds)

float64

dask.array<chunksize=(3552, 64, 2), meta=np.ndarray>

	Array	Chunk
Bytes	12.24 MB	3.64 MB
Shape	(11952, 64, 2)	(3552, 64, 2)
Count	32 Tasks	8 Chunks
Type	float64	numpy.ndarray

lon_bnds

(time, lon, bnds)

float64

dask.array<chunksize=(3552, 128, 2), meta=np.ndarray>

	Array	Chunk
Bytes	24.48 MB	7.27 MB
Shape	(11952, 128, 2)	(3552, 128, 2)
Count	32 Tasks	8 Chunks
Type	float64	numpy.ndarray

snd

(time, lat, lon)

float32

dask.array<chunksize=(3552, 64, 128), meta=np.ndarray>

standard_name :: surface_snow_thickness
long_name :: Snow Depth
comment :: where land over land, this is computed as the mean thickness of snow in the land portion of the grid cell (averaging over the entire land portion, including the snow-free fraction). Reported as 0.0 where the land fraction is 0.
units :: m
original_name :: ZN
cell_methods :: time: mean (interval: 15 minutes) area: mean where land
cell_measures :: area: areacella
history :: 2011-03-17T21:53:26Z altered by CMOR: replaced missing value flag (1e+38) with standard missing value (1e+20).
associated_files :: baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_landIce_fx_CanESM2_piControl_r0i0p0.nc areacella: areacella_fx_CanESM2_piControl_r0i0p0.nc

	Array	Chunk
Bytes	391.64 MB	116.39 MB
Shape	(11952, 64, 128)	(3552, 64, 128)
Count	24 Tasks	8 Chunks
Type	float32	numpy.ndarray

Attributes: (31)
institution :
CCCma (Canadian Centre for Climate Modelling and Analysis, Victoria, BC, Canada)
institute_id :
CCCma
experiment_id :
piControl
source :
CanESM2 2010 atmosphere: CanAM4 (AGCM15i, T63L35) ocean: CanOM4 (OGCM4.0, 256x192L40) and CMOC1.2 sea ice: CanSIM1 (Cavitating Fluid, T63 Gaussian Grid) land: CLASS2.7 and CTEM1
model_id :
CanESM2
forcing :
N/A
parent_experiment_id :
N/A
parent_experiment_rip :
N/A
branch_time :
0.0
contact :
cccma_info@ec.gc.ca
references :
http://www.cccma.ec.gc.ca/models
initialization_method :
1
physics_version :
1
tracking_id :
09cb9a5a-824a-453e-8d2f-dd1ac1169a95
branch_time_YMDH :
2015:01:01:00
CCCma_runid :
IGA
CCCma_parent_runid :
IBA
CCCma_data_licence :
1) GRANT OF LICENCE - The Government of Canada (Environment Canada) is the owner of all intellectual property rights (including copyright) that may exist in this Data product. You (as "The Licensee") are hereby granted a non-exclusive, non-assignable, non-transferable unrestricted licence to use this data product for any purpose including the right to share these data with others and to make value-added and derivative products from it. This licence is not a sale of any or all of the owner's rights. 2) NO WARRANTY - This Data product is provided "as-is"; it has not been designed or prepared to meet the Licensee's particular requirements. Environment Canada makes no warranty, either express or implied, including but not limited to, warranties of merchantability and fitness for a particular purpose. In no event will Environment Canada be liable for any indirect, special, consequential or other damages attributed to the Licensee's use of the Data product.
product :
output
experiment :
pre-industrial control
frequency :
mon
creation_date :
2011-03-17T21:53:26Z
history :
2011-03-17T21:53:26Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
Conventions :
CF-1.4
project_id :
CMIP5
table_id :
Table LImon (31 January 2011) 6f05b7e5f64aaa34bcac127ca47ac655
title :
CanESM2 model output prepared for CMIP5 pre-industrial control
parent_experiment :
N/A
modeling_realm :
landIce land
realization :
1
cmor_version :
2.5.4