FIO-ESM 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/hfls_Amon_FIO-ESM_piControl_r1i1p1.yaml")
ds=cat.netcdf.read()

Metadata

title	FIO-ESM model output prepared for CMIP5 pre-industrial control
location	/shared/cmip5/data/piControl/atmos/mon/Amon/hfls/FIO.FIO-ESM/r1i1p1
tags	gridded,global,model,monthly
catalog_dir	https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/hfls_Amon_FIO-ESM_piControl_r1i1p1.yaml
last updated	2017-08-17

Dataset Contents

<xarray.Dataset>
Dimensions:    (bnds: 2, lat: 64, lon: 128, time: 9600)
Coordinates:
  * time       (time) float64 15.5 45.0 74.5 ... 3.642e+04 3.645e+04 3.648e+04
  * 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=(1200, 2), meta=np.ndarray>
    lat_bnds   (time, lat, bnds) float64 dask.array<chunksize=(1200, 64, 2), meta=np.ndarray>
    lon_bnds   (time, lon, bnds) float64 dask.array<chunksize=(1200, 128, 2), meta=np.ndarray>
    hfls       (time, lat, lon) float32 dask.array<chunksize=(1200, 64, 128), meta=np.ndarray>
Attributes:
    institution:            FIO(The First Institution of Oceanography,SOA,Qin...
    institute_id:           FIO
    experiment_id:          piControl
    source:                 FIO-ESM
    model_id:               FIO-ESM
    forcing:                Nat
    parent_experiment_id:   N/A
    parent_experiment_rip:  N/A
    branch_time:            0.0
    contact:                Song Zhenya(songroy@fio.org.cn)
    initialization_method:  1
    physics_version:        1
    tracking_id:            a139b022-8d70-45fb-b00d-69bb6f9f1632
    product:                output
    experiment:             pre-industrial control
    frequency:              mon
    creation_date:          2012-05-11T15:41:12Z
    history:                2012-05-11T15:41:12Z CMOR rewrote data to comply ...
    Conventions:            CF-1.4
    project_id:             CMIP5
    table_id:               Table Amon (26 July 2011) 976b7fd1d9e1be31dddd28f...
    title:                  FIO-ESM model output prepared for CMIP5 pre-indus...
    parent_experiment:      N/A
    modeling_realm:         atmos
    realization:            1
    cmor_version:           2.8.0

xarray.Dataset

Dimensions:
- bnds: 2
- lat: 64
- lon: 128
- time: 9600

Coordinates: (3)

time
(time)
float64
15.5 45.0 ... 3.645e+04 3.648e+04
bounds :
time_bnds
calendar :
noleap
axis :
T
long_name :
time
standard_name :
time
```
array([1.55000e+01, 4.50000e+01, 7.45000e+01, ..., 3.64235e+04, 3.64540e+04,
       3.64845e+04])
```

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([-87.8638  , -85.096527, -82.312912, -79.525604, -76.7369  , -73.947517,
       -71.157753, -68.36776 , -65.577606, -62.787354, -59.997021, -57.206631,
       -54.416199, -51.625732, -48.835239, -46.044727, -43.254196, -40.46365 ,
       -37.673088, -34.882523, -32.091946, -29.301359, -26.510769, -23.720175,
       -20.929575, -18.138971, -15.348365, -12.557756,  -9.767145,  -6.976533,
        -4.185921,  -1.395307,   1.395307,   4.185921,   6.976533,   9.767145,
        12.557756,  15.348365,  18.138971,  20.929575,  23.720175,  26.510769,
        29.301359,  32.091946,  34.882523,  37.673088,  40.46365 ,  43.254196,
        46.044727,  48.835239,  51.625732,  54.416199,  57.206631,  59.997021,
        62.787354,  65.577606,  68.36776 ,  71.157753,  73.947517,  76.7369  ,
        79.525604,  82.312912,  85.096527,  87.8638  ])

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=(1200, 2), meta=np.ndarray>

	Array	Chunk
Bytes	153.60 kB	19.20 kB
Shape	(9600, 2)	(1200, 2)
Count	24 Tasks	8 Chunks
Type	float64	numpy.ndarray

lat_bnds

(time, lat, bnds)

float64

dask.array<chunksize=(1200, 64, 2), meta=np.ndarray>

	Array	Chunk
Bytes	9.83 MB	1.23 MB
Shape	(9600, 64, 2)	(1200, 64, 2)
Count	32 Tasks	8 Chunks
Type	float64	numpy.ndarray

lon_bnds

(time, lon, bnds)

float64

dask.array<chunksize=(1200, 128, 2), meta=np.ndarray>

	Array	Chunk
Bytes	19.66 MB	2.46 MB
Shape	(9600, 128, 2)	(1200, 128, 2)
Count	32 Tasks	8 Chunks
Type	float64	numpy.ndarray

hfls

(time, lat, lon)

float32

dask.array<chunksize=(1200, 64, 128), meta=np.ndarray>

standard_name :: surface_upward_latent_heat_flux
long_name :: Surface Upward Latent Heat Flux
comment :: includes both evaporation and sublimation
units :: W m-2
cell_methods :: time: mean
cell_measures :: area: areacella
associated_files :: baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_FIO-ESM_piControl_r0i0p0.nc areacella: areacella_fx_FIO-ESM_piControl_r0i0p0.nc

	Array	Chunk
Bytes	314.57 MB	39.32 MB
Shape	(9600, 64, 128)	(1200, 64, 128)
Count	24 Tasks	8 Chunks
Type	float32	numpy.ndarray

Attributes: (26)
institution :
FIO(The First Institution of Oceanography,SOA,Qingdao,China)
institute_id :
FIO
experiment_id :
piControl
source :
FIO-ESM
model_id :
FIO-ESM
forcing :
Nat
parent_experiment_id :
N/A
parent_experiment_rip :
N/A
branch_time :
0.0
contact :
Song Zhenya(songroy@fio.org.cn)
initialization_method :
1
physics_version :
1
tracking_id :
a139b022-8d70-45fb-b00d-69bb6f9f1632
product :
output
experiment :
pre-industrial control
frequency :
mon
creation_date :
2012-05-11T15:41:12Z
history :
2012-05-11T15:41:12Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
Conventions :
CF-1.4
project_id :
CMIP5
table_id :
Table Amon (26 July 2011) 976b7fd1d9e1be31dddd28f5dc79b7a1
title :
FIO-ESM model output prepared for CMIP5 pre-industrial control
parent_experiment :
N/A
modeling_realm :
atmos
realization :
1
cmor_version :
2.8.0