<xarray.Dataset> Size: 306GB
Dimensions: (time: 25933, latitude: 465, longitude: 705)
Coordinates:
* latitude (latitude) float64 4kB 25.05 25.15 25.25 ... 71.25 71.35 71.45
* longitude (longitude) float64 6kB -24.95 -24.85 -24.75 ... 45.35 45.45
* time (time) datetime64[ns] 207kB 1950-01-01 1950-01-02 ... 2020-12-31
Data variables:
hu (time, latitude, longitude) float32 34GB dask.array<chunksize=(40, 465, 705), meta=np.ndarray>
pp (time, latitude, longitude) float32 34GB dask.array<chunksize=(40, 465, 705), meta=np.ndarray>
rr (time, latitude, longitude) float32 34GB dask.array<chunksize=(40, 465, 705), meta=np.ndarray>
tg (time, latitude, longitude) float64 68GB dask.array<chunksize=(40, 465, 705), meta=np.ndarray>
tn (time, latitude, longitude) float64 68GB dask.array<chunksize=(40, 465, 705), meta=np.ndarray>
tx (time, latitude, longitude) float64 68GB dask.array<chunksize=(40, 465, 705), meta=np.ndarray>
Attributes:
CDI: Climate Data Interface version 1.6.3 (http://c...
CDO: Climate Data Operators version 1.6.3 (http://c...
Conventions: CF-1.4
NCO: netCDF Operators version 4.7.5 (Homepage = htt...
history: Mon Sep 6 09:34:28 2021: ncap2 -O -4 -s where...
nco_openmp_thread_number: 1
pangeo-forge:inputs_hash: ee8d7eaac44856a139b11abb3c3475cac42cfc8e049f9d...
pangeo-forge:recipe_hash: 298aa637305d386ab8baa2da2b0664249770641089f5a2...
pangeo-forge:version: 0.9.1 Dimensions: time : 25933latitude : 465longitude : 705
Coordinates: (3)
latitude
(latitude)
float64
25.05 25.15 25.25 ... 71.35 71.45
axis : Y long_name : Latitude values standard_name : latitude units : degrees_north array([25.049861, 25.149861, 25.249861, ..., 71.24986 , 71.34986 , 71.44986 ]) longitude
(longitude)
float64
-24.95 -24.85 ... 45.35 45.45
axis : X long_name : Longitude values standard_name : longitude units : degrees_east array([-24.95014, -24.85014, -24.75014, ..., 45.24986, 45.34986, 45.44986]) time
(time)
datetime64[ns]
1950-01-01 ... 2020-12-31
long_name : Time in days standard_name : time array(['1950-01-01T00:00:00.000000000', '1950-01-02T00:00:00.000000000',
'1950-01-03T00:00:00.000000000', ..., '2020-12-29T00:00:00.000000000',
'2020-12-30T00:00:00.000000000', '2020-12-31T00:00:00.000000000'],
dtype='datetime64[ns]') Data variables: (6)
hu
(time, latitude, longitude)
float32
dask.array<chunksize=(40, 465, 705), meta=np.ndarray>
cell_methods : ensemble: mean long_name : mean relative humidity standard_name : relative_humidity units : %
Array
Chunk
Bytes
31.67 GiB
50.02 MiB
Shape
(25933, 465, 705)
(40, 465, 705)
Dask graph
649 chunks in 2 graph layers
Data type
float32 numpy.ndarray
705
465
25933
pp
(time, latitude, longitude)
float32
dask.array<chunksize=(40, 465, 705), meta=np.ndarray>
long_name : sea level pressure standard_name : air_pressure_at_sea_level units : hPa
Array
Chunk
Bytes
31.67 GiB
50.02 MiB
Shape
(25933, 465, 705)
(40, 465, 705)
Dask graph
649 chunks in 2 graph layers
Data type
float32 numpy.ndarray
705
465
25933
rr
(time, latitude, longitude)
float32
dask.array<chunksize=(40, 465, 705), meta=np.ndarray>
long_name : rainfall standard_name : thickness_of_rainfall_amount units : mm
Array
Chunk
Bytes
31.67 GiB
50.02 MiB
Shape
(25933, 465, 705)
(40, 465, 705)
Dask graph
649 chunks in 2 graph layers
Data type
float32 numpy.ndarray
705
465
25933
tg
(time, latitude, longitude)
float64
dask.array<chunksize=(40, 465, 705), meta=np.ndarray>
long_name : mean temperature standard_name : air_temperature units : Celsius
Array
Chunk
Bytes
63.34 GiB
100.04 MiB
Shape
(25933, 465, 705)
(40, 465, 705)
Dask graph
649 chunks in 2 graph layers
Data type
float64 numpy.ndarray
705
465
25933
tn
(time, latitude, longitude)
float64
dask.array<chunksize=(40, 465, 705), meta=np.ndarray>
long_name : minimum temperature standard_name : air_temperature units : Celsius
Array
Chunk
Bytes
63.34 GiB
100.04 MiB
Shape
(25933, 465, 705)
(40, 465, 705)
Dask graph
649 chunks in 2 graph layers
Data type
float64 numpy.ndarray
705
465
25933
tx
(time, latitude, longitude)
float64
dask.array<chunksize=(40, 465, 705), meta=np.ndarray>
long_name : maximum temperature standard_name : air_temperature units : Celsius
Array
Chunk
Bytes
63.34 GiB
100.04 MiB
Shape
(25933, 465, 705)
(40, 465, 705)
Dask graph
649 chunks in 2 graph layers
Data type
float64 numpy.ndarray
705
465
25933
Indexes: (3)
PandasIndex
PandasIndex(Index([ 25.04986061562095, 25.14986061529165, 25.24986061496235,
25.34986061463305, 25.449860614303752, 25.549860613974452,
25.649860613645153, 25.749860613315853, 25.849860612986554,
25.94986061265726,
...
70.54986046578995, 70.64986046546065, 70.74986046513135,
70.84986046480205, 70.94986046447275, 71.04986046414345,
71.14986046381415, 71.24986046348485, 71.34986046315555,
71.44986046282625],
dtype='float64', name='latitude', length=465)) PandasIndex
PandasIndex(Index([-24.950139509199623, -24.850139509599675, -24.750139509999723,
-24.650139510399775, -24.550139510799823, -24.450139511199875,
-24.350139511599924, -24.250139511999976, -24.150139512400024,
-24.050139512800076,
...
44.54986021276558, 44.649860212365525, 44.74986021196548,
44.84986021156543, 44.94986021116539, 45.04986021076533,
45.149860210365276, 45.249860209965235, 45.34986020956518,
45.449860209165124],
dtype='float64', name='longitude', length=705)) PandasIndex
PandasIndex(DatetimeIndex(['1950-01-01', '1950-01-02', '1950-01-03', '1950-01-04',
'1950-01-05', '1950-01-06', '1950-01-07', '1950-01-08',
'1950-01-09', '1950-01-10',
...
'2020-12-22', '2020-12-23', '2020-12-24', '2020-12-25',
'2020-12-26', '2020-12-27', '2020-12-28', '2020-12-29',
'2020-12-30', '2020-12-31'],
dtype='datetime64[ns]', name='time', length=25933, freq=None)) Attributes: (9)
CDI : Climate Data Interface version 1.6.3 (http://code.zmaw.de/projects/cdi) CDO : Climate Data Operators version 1.6.3 (http://code.zmaw.de/projects/cdo) Conventions : CF-1.4 NCO : netCDF Operators version 4.7.5 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco) history : Mon Sep 6 09:34:28 2021: ncap2 -O -4 -s where(hu<5) hu=-9999; /data2/Else/EOBSv23.1e/Grid_0.1deg/hu/hu_ens_mean_0.1deg_reg_v23.1e.nc /data2/Else/EOBSv23.1e/Grid_0.1deg/hu/hu_ens_mean_0.1deg_reg_v23.1e_corr.nc
Tue Jul 27 13:19:13 2021: cdo -O -z zip_1 mergetime /data2/Else/Humidity/Backtransformed/agg/hu_ensmean_master.nc ../hu_ens_mean_0.1deg_reg_v23.1e.nc hu_ens_mean_0.1deg_reg_v23.1e_test.nc nco_openmp_thread_number : 1 pangeo-forge:inputs_hash : ee8d7eaac44856a139b11abb3c3475cac42cfc8e049f9d6c3116a6796d0998c6 pangeo-forge:recipe_hash : 298aa637305d386ab8baa2da2b0664249770641089f5a23fb1711e4c51d77f3f pangeo-forge:version : 0.9.1 
