xarray.Dataset

Dimensions:
- S: 187
- M: 28
- L: 10
- Y: 181
- X: 360
- nbound: 2

Coordinates: (7)

(S)

datetime64[s]

2011-04-01 ... 2026-10-01

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

array(['2011-04-01T00:00:00', '2011-05-01T00:00:00', '2011-06-01T00:00:00',
       '2011-07-01T00:00:00', '2011-08-01T00:00:00', '2011-09-01T00:00:00',
       '2011-10-01T00:00:00', '2011-11-01T00:00:00', '2011-12-01T00:00:00',
       '2012-01-01T00:00:00', '2012-02-01T00:00:00', '2012-03-01T00:00:00',
       '2012-04-01T00:00:00', '2012-05-01T00:00:00', '2012-06-01T00:00:00',
       '2012-07-01T00:00:00', '2012-08-01T00:00:00', '2012-09-01T00:00:00',
       '2012-10-01T00:00:00', '2012-11-01T00:00:00', '2012-12-01T00:00:00',
       '2013-01-01T00:00:00', '2013-02-01T00:00:00', '2013-03-01T00:00:00',
       '2013-04-01T00:00:00', '2013-05-01T00:00:00', '2013-06-01T00:00:00',
       '2013-07-01T00:00:00', '2013-08-01T00:00:00', '2013-09-01T00:00:00',
       '2013-10-01T00:00:00', '2013-11-01T00:00:00', '2013-12-01T00:00:00',
       '2014-01-01T00:00:00', '2014-02-01T00:00:00', '2014-03-01T00:00:00',
       '2014-04-01T00:00:00', '2014-05-01T00:00:00', '2014-06-01T00:00:00',
       '2014-07-01T00:00:00', '2014-08-01T00:00:00', '2014-09-01T00:00:00',
       '2014-10-01T00:00:00', '2014-11-01T00:00:00', '2014-12-01T00:00:00',
       '2015-01-01T00:00:00', '2015-02-01T00:00:00', '2015-03-01T00:00:00',
       '2015-04-01T00:00:00', '2015-05-01T00:00:00', '2015-06-01T00:00:00',
       '2015-07-01T00:00:00', '2015-08-01T00:00:00', '2015-09-01T00:00:00',
       '2015-10-01T00:00:00', '2015-11-01T00:00:00', '2015-12-01T00:00:00',
       '2016-01-01T00:00:00', '2016-02-01T00:00:00', '2016-03-01T00:00:00',
       '2016-04-01T00:00:00', '2016-05-01T00:00:00', '2016-06-01T00:00:00',
       '2016-07-01T00:00:00', '2016-08-01T00:00:00', '2016-09-01T00:00:00',
       '2016-10-01T00:00:00', '2016-11-01T00:00:00', '2016-12-01T00:00:00',
       '2017-01-01T00:00:00', '2017-02-01T00:00:00', '2017-03-01T00:00:00',
       '2017-04-01T00:00:00', '2017-05-01T00:00:00', '2017-06-01T00:00:00',
       '2017-07-01T00:00:00', '2017-08-01T00:00:00', '2017-09-01T00:00:00',
       '2017-10-01T00:00:00', '2017-11-01T00:00:00', '2017-12-01T00:00:00',
       '2018-01-01T00:00:00', '2018-02-01T00:00:00', '2018-03-01T00:00:00',
       '2018-04-01T00:00:00', '2018-05-01T00:00:00', '2018-06-01T00:00:00',
       '2018-07-01T00:00:00', '2018-08-01T00:00:00', '2018-09-01T00:00:00',
       '2018-10-01T00:00:00', '2018-11-01T00:00:00', '2018-12-01T00:00:00',
       '2019-01-01T00:00:00', '2019-02-01T00:00:00', '2019-03-01T00:00:00',
       '2019-04-01T00:00:00', '2019-05-01T00:00:00', '2019-06-01T00:00:00',
       '2019-07-01T00:00:00', '2019-08-01T00:00:00', '2019-09-01T00:00:00',
       '2019-10-01T00:00:00', '2019-11-01T00:00:00', '2019-12-01T00:00:00',
       '2020-01-01T00:00:00', '2020-02-01T00:00:00', '2020-03-01T00:00:00',
       '2020-04-01T00:00:00', '2020-05-01T00:00:00', '2020-06-01T00:00:00',
       '2020-07-01T00:00:00', '2020-08-01T00:00:00', '2020-09-01T00:00:00',
       '2020-10-01T00:00:00', '2020-11-01T00:00:00', '2020-12-01T00:00:00',
       '2021-01-01T00:00:00', '2021-02-01T00:00:00', '2021-03-01T00:00:00',
       '2021-04-01T00:00:00', '2021-05-01T00:00:00', '2021-06-01T00:00:00',
       '2021-07-01T00:00:00', '2021-08-01T00:00:00', '2021-09-01T00:00:00',
       '2021-10-01T00:00:00', '2021-11-01T00:00:00', '2021-12-01T00:00:00',
       '2022-01-01T00:00:00', '2022-02-01T00:00:00', '2022-03-01T00:00:00',
       '2022-04-01T00:00:00', '2022-05-01T00:00:00', '2022-06-01T00:00:00',
       '2022-07-01T00:00:00', '2022-08-01T00:00:00', '2022-09-01T00:00:00',
       '2022-10-01T00:00:00', '2022-11-01T00:00:00', '2022-12-01T00:00:00',
       '2023-01-01T00:00:00', '2023-02-01T00:00:00', '2023-03-01T00:00:00',
       '2023-04-01T00:00:00', '2023-05-01T00:00:00', '2023-06-01T00:00:00',
       '2023-07-01T00:00:00', '2023-08-01T00:00:00', '2023-09-01T00:00:00',
       '2023-10-01T00:00:00', '2023-11-01T00:00:00', '2023-12-01T00:00:00',
       '2024-01-01T00:00:00', '2024-02-01T00:00:00', '2024-03-01T00:00:00',
       '2024-04-01T00:00:00', '2024-05-01T00:00:00', '2024-06-01T00:00:00',
       '2024-07-01T00:00:00', '2024-08-01T00:00:00', '2024-09-01T00:00:00',
       '2024-10-01T00:00:00', '2024-11-01T00:00:00', '2024-12-01T00:00:00',
       '2025-01-01T00:00:00', '2025-02-01T00:00:00', '2025-03-01T00:00:00',
       '2025-04-01T00:00:00', '2025-05-01T00:00:00', '2025-06-01T00:00:00',
       '2025-07-01T00:00:00', '2025-08-01T00:00:00', '2025-09-01T00:00:00',
       '2025-10-01T00:00:00', '2025-11-01T00:00:00', '2025-12-01T00:00:00',
       '2026-01-01T00:00:00', '2026-02-01T00:00:00', '2026-03-01T00:00:00',
       '2026-04-01T00:00:00', '2026-05-01T00:00:00', '2026-06-01T00:00:00',
       '2026-07-01T00:00:00', '2026-08-01T00:00:00', '2026-09-01T00:00:00',
       '2026-10-01T00:00:00'], dtype='datetime64[s]')

(M)

int64

1 2 3 4 5 6 7 ... 23 24 25 26 27 28

long_name :: Ensemble member
standard_name :: realization

array([ 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])

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

target

(S, L)

datetime64[s]

2011-04-01 ... 2027-07-01

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

array([['2011-04-01T00:00:00', '2011-05-01T00:00:00',
        '2011-06-01T00:00:00', ..., '2011-11-01T00:00:00',
        '2011-12-01T00:00:00', '2012-01-01T00:00:00'],
       ['2011-05-01T00:00:00', '2011-06-01T00:00:00',
        '2011-07-01T00:00:00', ..., '2011-12-01T00:00:00',
        '2012-01-01T00:00:00', '2012-02-01T00:00:00'],
       ['2011-06-01T00:00:00', '2011-07-01T00:00:00',
        '2011-08-01T00:00:00', ..., '2012-01-01T00:00:00',
        '2012-02-01T00:00:00', '2012-03-01T00:00:00'],
       ...,
       ['2026-08-01T00:00:00', '2026-09-01T00:00:00',
        '2026-10-01T00:00:00', ..., '2027-03-01T00:00:00',
        '2027-04-01T00:00:00', '2027-05-01T00:00:00'],
       ['2026-09-01T00:00:00', '2026-10-01T00:00:00',
        '2026-11-01T00:00:00', ..., '2027-04-01T00:00:00',
        '2027-05-01T00:00:00', '2027-06-01T00:00:00'],
       ['2026-10-01T00:00:00', '2026-11-01T00:00:00',
        '2026-12-01T00:00:00', ..., '2027-05-01T00:00:00',
        '2027-06-01T00:00:00', '2027-07-01T00:00:00']],
      shape=(187, 10), dtype='datetime64[s]')

(Y)

int64

-90 -89 -88 -87 -86 ... 87 88 89 90

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])

X
(X)
int64
0 1 2 3 4 5 ... 355 356 357 358 359
long_name :
Longitude
standard_name :
longitude
units :
degree_east
```
array([  0,   1,   2, ..., 357, 358, 359], shape=(360,))
```

target_bnds

(S, L, nbound)

datetime64[s]

2011-04-01 ... 2027-08-01

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

array([[['2011-04-01T00:00:00', '2011-05-01T00:00:00'],
        ['2011-05-01T00:00:00', '2011-06-01T00:00:00'],
        ['2011-06-01T00:00:00', '2011-07-01T00:00:00'],
        ...,
        ['2011-11-01T00:00:00', '2011-12-01T00:00:00'],
        ['2011-12-01T00:00:00', '2012-01-01T00:00:00'],
        ['2012-01-01T00:00:00', '2012-02-01T00:00:00']],

       [['2011-05-01T00:00:00', '2011-06-01T00:00:00'],
        ['2011-06-01T00:00:00', '2011-07-01T00:00:00'],
        ['2011-07-01T00:00:00', '2011-08-01T00:00:00'],
        ...,
        ['2011-12-01T00:00:00', '2012-01-01T00:00:00'],
        ['2012-01-01T00:00:00', '2012-02-01T00:00:00'],
        ['2012-02-01T00:00:00', '2012-03-01T00:00:00']],

       [['2011-06-01T00:00:00', '2011-07-01T00:00:00'],
        ['2011-07-01T00:00:00', '2011-08-01T00:00:00'],
        ['2011-08-01T00:00:00', '2011-09-01T00:00:00'],
        ...,
...
        ['2027-03-01T00:00:00', '2027-04-01T00:00:00'],
        ['2027-04-01T00:00:00', '2027-05-01T00:00:00'],
        ['2027-05-01T00:00:00', '2027-06-01T00:00:00']],

       [['2026-09-01T00:00:00', '2026-10-01T00:00:00'],
        ['2026-10-01T00:00:00', '2026-11-01T00:00:00'],
        ['2026-11-01T00:00:00', '2026-12-01T00:00:00'],
        ...,
        ['2027-04-01T00:00:00', '2027-05-01T00:00:00'],
        ['2027-05-01T00:00:00', '2027-06-01T00:00:00'],
        ['2027-06-01T00:00:00', '2027-07-01T00:00:00']],

       [['2026-10-01T00:00:00', '2026-11-01T00:00:00'],
        ['2026-11-01T00:00:00', '2026-12-01T00:00:00'],
        ['2026-12-01T00:00:00', '2027-01-01T00:00:00'],
        ...,
        ['2027-05-01T00:00:00', '2027-06-01T00:00:00'],
        ['2027-06-01T00:00:00', '2027-07-01T00:00:00'],
        ['2027-07-01T00:00:00', '2027-08-01T00:00:00']]],
      shape=(187, 10, 2), dtype='datetime64[s]')

Data variables: (1)

tas

(S, M, L, Y, X)

float64

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

long_name :: Near-surface air temperature
standard_name :: air_temperature
units :: degree_Celsius
coordinates :: target target_bnds

	Array	Chunk
Bytes	25.42 GiB	509.06 kiB
Shape	(187, 28, 10, 181, 360)	(1, 1, 1, 181, 360)
Dask graph	52360 chunks in 28 graph layers
Data type	float64 numpy.ndarray

Attributes: (3)
Conventions :
CF-1.13
institution :
US National Weather Service - NCEP
history :
2026-09-01T16:00 GRIB to CDM+CF via cfgrib-0.9.15.1/ecCodes-2.48.0 with {"source": "../../../../data/original/NMME/NOAA-NCEP/CFSv2/forecast/2011/01/13/00/flxf.01.2011011300.201105.avrg.grib.grb2", "filter_by_keys": {"typeOfLevel": "heightAboveGround", "level": 2, "shortName": "avg_2t"}, "encode_cf": ["parameter", "time", "geography", "vertical"]}