xarray.Dataset

Dimensions:
- S: 112
- M: 10
- L: 9
- Y: 181
- X: 360
- nbound: 2

Coordinates: (7)

(S)

datetime64[ns]

2017-02-01 ... 2026-05-01

long_name :: Forecast start time
standard_name :: forecast_reference_time
units :: hours since 1960-01-01
calendar :: standard

array(['2017-02-01T00:00:00.000000000', '2017-03-01T00:00:00.000000000',
       '2017-04-01T00:00:00.000000000', '2017-05-01T00:00:00.000000000',
       '2017-06-01T00:00:00.000000000', '2017-07-01T00:00:00.000000000',
       '2017-08-01T00:00:00.000000000', '2017-09-01T00:00:00.000000000',
       '2017-10-01T00:00:00.000000000', '2017-11-01T00:00:00.000000000',
       '2017-12-01T00:00:00.000000000', '2018-01-01T00:00:00.000000000',
       '2018-02-01T00:00:00.000000000', '2018-03-01T00:00:00.000000000',
       '2018-04-01T00:00:00.000000000', '2018-05-01T00:00:00.000000000',
       '2018-06-01T00:00:00.000000000', '2018-07-01T00:00:00.000000000',
       '2018-08-01T00:00:00.000000000', '2018-09-01T00:00:00.000000000',
       '2018-10-01T00:00:00.000000000', '2018-11-01T00:00:00.000000000',
       '2018-12-01T00:00:00.000000000', '2019-01-01T00:00:00.000000000',
       '2019-02-01T00:00:00.000000000', '2019-03-01T00:00:00.000000000',
       '2019-04-01T00:00:00.000000000', '2019-05-01T00:00:00.000000000',
       '2019-06-01T00:00:00.000000000', '2019-07-01T00:00:00.000000000',
       '2019-08-01T00:00:00.000000000', '2019-09-01T00:00:00.000000000',
       '2019-10-01T00:00:00.000000000', '2019-11-01T00:00:00.000000000',
       '2019-12-01T00:00:00.000000000', '2020-01-01T00:00:00.000000000',
       '2020-02-01T00:00:00.000000000', '2020-03-01T00:00:00.000000000',
       '2020-04-01T00:00:00.000000000', '2020-05-01T00:00:00.000000000',
       '2020-06-01T00:00:00.000000000', '2020-07-01T00:00:00.000000000',
       '2020-08-01T00:00:00.000000000', '2020-09-01T00:00:00.000000000',
       '2020-10-01T00:00:00.000000000', '2020-11-01T00:00:00.000000000',
       '2020-12-01T00:00:00.000000000', '2021-01-01T00:00:00.000000000',
       '2021-02-01T00:00:00.000000000', '2021-03-01T00:00:00.000000000',
       '2021-04-01T00:00:00.000000000', '2021-05-01T00:00:00.000000000',
       '2021-06-01T00:00:00.000000000', '2021-07-01T00:00:00.000000000',
       '2021-08-01T00:00:00.000000000', '2021-09-01T00:00:00.000000000',
       '2021-10-01T00:00:00.000000000', '2021-11-01T00:00:00.000000000',
       '2021-12-01T00:00:00.000000000', '2022-01-01T00:00:00.000000000',
       '2022-02-01T00:00:00.000000000', '2022-03-01T00:00:00.000000000',
       '2022-04-01T00:00:00.000000000', '2022-05-01T00:00:00.000000000',
       '2022-06-01T00:00:00.000000000', '2022-07-01T00:00:00.000000000',
       '2022-08-01T00:00:00.000000000', '2022-09-01T00:00:00.000000000',
       '2022-10-01T00:00:00.000000000', '2022-11-01T00:00:00.000000000',
       '2022-12-01T00:00:00.000000000', '2023-01-01T00:00:00.000000000',
       '2023-02-01T00:00:00.000000000', '2023-03-01T00:00:00.000000000',
       '2023-04-01T00:00:00.000000000', '2023-05-01T00:00:00.000000000',
       '2023-06-01T00:00:00.000000000', '2023-07-01T00:00:00.000000000',
       '2023-08-01T00:00:00.000000000', '2023-09-01T00:00:00.000000000',
       '2023-10-01T00:00:00.000000000', '2023-11-01T00:00:00.000000000',
       '2023-12-01T00:00:00.000000000', '2024-01-01T00:00:00.000000000',
       '2024-02-01T00:00:00.000000000', '2024-03-01T00:00:00.000000000',
       '2024-04-01T00:00:00.000000000', '2024-05-01T00:00:00.000000000',
       '2024-06-01T00:00:00.000000000', '2024-07-01T00:00:00.000000000',
       '2024-08-01T00:00:00.000000000', '2024-09-01T00:00:00.000000000',
       '2024-10-01T00:00:00.000000000', '2024-11-01T00:00:00.000000000',
       '2024-12-01T00:00:00.000000000', '2025-01-01T00:00:00.000000000',
       '2025-02-01T00:00:00.000000000', '2025-03-01T00:00:00.000000000',
       '2025-04-01T00:00:00.000000000', '2025-05-01T00:00:00.000000000',
       '2025-06-01T00:00:00.000000000', '2025-07-01T00:00:00.000000000',
       '2025-08-01T00:00:00.000000000', '2025-09-01T00:00:00.000000000',
       '2025-10-01T00:00:00.000000000', '2025-11-01T00:00:00.000000000',
       '2025-12-01T00:00:00.000000000', '2026-01-01T00:00:00.000000000',
       '2026-02-01T00:00:00.000000000', '2026-03-01T00:00:00.000000000',
       '2026-04-01T00:00:00.000000000', '2026-05-01T00:00:00.000000000'],
      dtype='datetime64[ns]')

M
(M)
int64
1 2 3 4 5 6 7 8 9 10
long_name :
Ensemble member
standard_name :
realization
```
array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10])
```
L
(L)
int64
0 1 2 3 4 5 6 7 8
long_name :
Lead
standard_name :
forecast_period
```
array([0, 1, 2, 3, 4, 5, 6, 7, 8])
```

target

(S, L)

datetime64[ns]

2017-02-01 ... 2027-01-01

long_name :: Forecast target period
standard_name :: time
bounds :: target_bnds
units :: hours since 1960-01-01
calendar :: standard

array([['2017-02-01T00:00:00.000000000', '2017-03-01T00:00:00.000000000',
        '2017-04-01T00:00:00.000000000', ...,
        '2017-08-01T00:00:00.000000000', '2017-09-01T00:00:00.000000000',
        '2017-10-01T00:00:00.000000000'],
       ['2017-03-01T00:00:00.000000000', '2017-04-01T00:00:00.000000000',
        '2017-05-01T00:00:00.000000000', ...,
        '2017-09-01T00:00:00.000000000', '2017-10-01T00:00:00.000000000',
        '2017-11-01T00:00:00.000000000'],
       ['2017-04-01T00:00:00.000000000', '2017-05-01T00:00:00.000000000',
        '2017-06-01T00:00:00.000000000', ...,
        '2017-10-01T00:00:00.000000000', '2017-11-01T00:00:00.000000000',
        '2017-12-01T00:00:00.000000000'],
       ...,
       ['2026-03-01T00:00:00.000000000', '2026-04-01T00:00:00.000000000',
        '2026-05-01T00:00:00.000000000', ...,
        '2026-09-01T00:00:00.000000000', '2026-10-01T00:00:00.000000000',
        '2026-11-01T00:00:00.000000000'],
       ['2026-04-01T00:00:00.000000000', '2026-05-01T00:00:00.000000000',
        '2026-06-01T00:00:00.000000000', ...,
        '2026-10-01T00:00:00.000000000', '2026-11-01T00:00:00.000000000',
        '2026-12-01T00:00:00.000000000'],
       ['2026-05-01T00:00:00.000000000', '2026-06-01T00:00:00.000000000',
        '2026-07-01T00:00:00.000000000', ...,
        '2026-11-01T00:00:00.000000000', '2026-12-01T00:00:00.000000000',
        '2027-01-01T00:00:00.000000000']],
      shape=(112, 9), dtype='datetime64[ns]')

(Y)

float32

-90.0 -89.0 -88.0 ... 89.0 90.0

long_name :: Latitude
standard_name :: latitude
units :: degree_north

array([-90., -89., -88., -87., -86., -85., -84., -83., -82., -81., -80., -79.,
       -78., -77., -76., -75., -74., -73., -72., -71., -70., -69., -68., -67.,
       -66., -65., -64., -63., -62., -61., -60., -59., -58., -57., -56., -55.,
       -54., -53., -52., -51., -50., -49., -48., -47., -46., -45., -44., -43.,
       -42., -41., -40., -39., -38., -37., -36., -35., -34., -33., -32., -31.,
       -30., -29., -28., -27., -26., -25., -24., -23., -22., -21., -20., -19.,
       -18., -17., -16., -15., -14., -13., -12., -11., -10.,  -9.,  -8.,  -7.,
        -6.,  -5.,  -4.,  -3.,  -2.,  -1.,   0.,   1.,   2.,   3.,   4.,   5.,
         6.,   7.,   8.,   9.,  10.,  11.,  12.,  13.,  14.,  15.,  16.,  17.,
        18.,  19.,  20.,  21.,  22.,  23.,  24.,  25.,  26.,  27.,  28.,  29.,
        30.,  31.,  32.,  33.,  34.,  35.,  36.,  37.,  38.,  39.,  40.,  41.,
        42.,  43.,  44.,  45.,  46.,  47.,  48.,  49.,  50.,  51.,  52.,  53.,
        54.,  55.,  56.,  57.,  58.,  59.,  60.,  61.,  62.,  63.,  64.,  65.,
        66.,  67.,  68.,  69.,  70.,  71.,  72.,  73.,  74.,  75.,  76.,  77.,
        78.,  79.,  80.,  81.,  82.,  83.,  84.,  85.,  86.,  87.,  88.,  89.,
        90.], dtype=float32)

X
(X)
float32
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
Longitude
standard_name :
longitude
units :
degree_east
```
array([  0.,   1.,   2., ..., 357., 358., 359.], shape=(360,), dtype=float32)
```

target_bnds

(S, L, nbound)

datetime64[ns]

2017-02-01 ... 2027-02-01

units :: hours since 1960-01-01
calendar :: standard

array([[['2017-02-01T00:00:00.000000000',
         '2017-03-01T00:00:00.000000000'],
        ['2017-03-01T00:00:00.000000000',
         '2017-04-01T00:00:00.000000000'],
        ['2017-04-01T00:00:00.000000000',
         '2017-05-01T00:00:00.000000000'],
        ...,
        ['2017-08-01T00:00:00.000000000',
         '2017-09-01T00:00:00.000000000'],
        ['2017-09-01T00:00:00.000000000',
         '2017-10-01T00:00:00.000000000'],
        ['2017-10-01T00:00:00.000000000',
         '2017-11-01T00:00:00.000000000']],

       [['2017-03-01T00:00:00.000000000',
         '2017-04-01T00:00:00.000000000'],
        ['2017-04-01T00:00:00.000000000',
         '2017-05-01T00:00:00.000000000'],
        ['2017-05-01T00:00:00.000000000',
         '2017-06-01T00:00:00.000000000'],
...
         '2026-11-01T00:00:00.000000000'],
        ['2026-11-01T00:00:00.000000000',
         '2026-12-01T00:00:00.000000000'],
        ['2026-12-01T00:00:00.000000000',
         '2027-01-01T00:00:00.000000000']],

       [['2026-05-01T00:00:00.000000000',
         '2026-06-01T00:00:00.000000000'],
        ['2026-06-01T00:00:00.000000000',
         '2026-07-01T00:00:00.000000000'],
        ['2026-07-01T00:00:00.000000000',
         '2026-08-01T00:00:00.000000000'],
        ...,
        ['2026-11-01T00:00:00.000000000',
         '2026-12-01T00:00:00.000000000'],
        ['2026-12-01T00:00:00.000000000',
         '2027-01-01T00:00:00.000000000'],
        ['2027-01-01T00:00:00.000000000',
         '2027-02-01T00:00:00.000000000']]],
      shape=(112, 9, 2), dtype='datetime64[ns]')

Data variables: (1)

sst

(S, M, L, Y, X)

float32

dask.array<chunksize=(1, 1, 9, 181, 360), meta=np.ndarray>

long_name :: Sea surface temperature
standard_name :: sea_surface_temperature
units :: degree_Celsius

	Array	Chunk
Bytes	2.45 GiB	2.24 MiB
Shape	(112, 10, 9, 181, 360)	(1, 1, 9, 181, 360)
Dask graph	1120 chunks in 5 graph layers
Data type	float32 numpy.ndarray

Attributes: (7)
CDI :
Climate Data Interface version 1.9.1 (http://mpimet.mpg.de/cdi)
Conventions :
CF-1.13
Title :
Unknown
Contact :
Unknown
History :
File written by GFIO v1.0.8
CDO :
Climate Data Operators version 1.9.1 (http://mpimet.mpg.de/cdo)
history :
Sat Feb 15 04:57:31 2020: cdo.exe -s -O chname,TS,sst tmpvout2.nc 20170116_1x1_sst_ens01.ncTS