<xarray.Dataset> Size: 650GB
Dimensions: (j: 1146, i: 720, time: 859, k: 45, i_g: 720, j_g: 1146, k_l: 45)
Coordinates: (12/29)
CS (j, i) float32 3MB dask.array<chunksize=(1146, 720), meta=np.ndarray>
Depth (j, i) float32 3MB dask.array<chunksize=(1146, 720), meta=np.ndarray>
PHrefC (k) float32 180B dask.array<chunksize=(45,), meta=np.ndarray>
SN (j, i) float32 3MB dask.array<chunksize=(1146, 720), meta=np.ndarray>
XC (j, i) float32 3MB dask.array<chunksize=(1146, 720), meta=np.ndarray>
YC (j, i) float32 3MB dask.array<chunksize=(1146, 720), meta=np.ndarray>
... ...
* k_l (k_l) int64 360B 0 1 2 3 4 5 6 7 8 9 ... 36 37 38 39 40 41 42 43 44
rA (j, i) float32 3MB dask.array<chunksize=(1146, 720), meta=np.ndarray>
rAs (j_g, i) float32 3MB dask.array<chunksize=(1146, 720), meta=np.ndarray>
rAw (j, i_g) float32 3MB dask.array<chunksize=(1146, 720), meta=np.ndarray>
rhoRef (k) float32 180B dask.array<chunksize=(45,), meta=np.ndarray>
* time (time) datetime64[ns] 7kB 2011-09-13T05:30:00 ... 2012-11-15T05:...
Data variables:
KPPhbl (time, j, i) float32 3GB dask.array<chunksize=(1, 1146, 720), meta=np.ndarray>
Salt (time, k, j, i) float32 128GB dask.array<chunksize=(1, 45, 1146, 720), meta=np.ndarray>
Theta (time, k, j, i) float32 128GB dask.array<chunksize=(1, 45, 1146, 720), meta=np.ndarray>
U (time, k, j, i_g) float32 128GB dask.array<chunksize=(1, 45, 1146, 720), meta=np.ndarray>
V (time, k, j_g, i) float32 128GB dask.array<chunksize=(1, 45, 1146, 720), meta=np.ndarray>
W (time, k_l, j, i) float32 128GB dask.array<chunksize=(1, 45, 1146, 720), meta=np.ndarray>
oceQnet (time, j, i) float32 3GB dask.array<chunksize=(1, 1146, 720), meta=np.ndarray>
oceTAUX (time, j, i_g) float32 3GB dask.array<chunksize=(1, 1146, 720), meta=np.ndarray>
oceTAUY (time, j_g, i) float32 3GB dask.array<chunksize=(1, 1146, 720), meta=np.ndarray> Dimensions: j : 1146i : 720time : 859k : 45i_g : 720j_g : 1146k_l : 45
Coordinates: (29)
CS
(j, i)
float32
dask.array<chunksize=(1146, 720), meta=np.ndarray>
coordinate : YC XC long_name : AngleCS standard_name : Cos of grid orientation angle units :
Array
Chunk
Bytes
3.15 MiB
3.15 MiB
Shape
(1146, 720)
(1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
Depth
(j, i)
float32
dask.array<chunksize=(1146, 720), meta=np.ndarray>
coordinate : XC YC long_name : ocean depth standard_name : ocean_depth units : m
Array
Chunk
Bytes
3.15 MiB
3.15 MiB
Shape
(1146, 720)
(1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
PHrefC
(k)
float32
dask.array<chunksize=(45,), meta=np.ndarray>
long_name : Reference Hydrostatic Pressure standard_name : cell_reference_pressure units : m2 s-2
Array
Chunk
Bytes
180 B
180 B
Shape
(45,)
(45,)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
45
1
SN
(j, i)
float32
dask.array<chunksize=(1146, 720), meta=np.ndarray>
coordinate : YC XC long_name : AngleSN standard_name : Sin of grid orientation angle units :
Array
Chunk
Bytes
3.15 MiB
3.15 MiB
Shape
(1146, 720)
(1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
XC
(j, i)
float32
dask.array<chunksize=(1146, 720), meta=np.ndarray>
coordinate : YC XC long_name : longitude standard_name : longitude units : degrees_east
Array
Chunk
Bytes
3.15 MiB
3.15 MiB
Shape
(1146, 720)
(1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
YC
(j, i)
float32
dask.array<chunksize=(1146, 720), meta=np.ndarray>
coordinate : YC XC long_name : latitude standard_name : latitude units : degrees_north
Array
Chunk
Bytes
3.15 MiB
3.15 MiB
Shape
(1146, 720)
(1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
Z
(k)
float32
dask.array<chunksize=(45,), meta=np.ndarray>
long_name : vertical coordinate of cell center positive : down standard_name : depth units : m
Array
Chunk
Bytes
180 B
180 B
Shape
(45,)
(45,)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
45
1
Zl
(k_l)
float32
dask.array<chunksize=(45,), meta=np.ndarray>
long_name : vertical coordinate of lower cell interface positive : down standard_name : depth_at_lower_w_location units : m
Array
Chunk
Bytes
180 B
180 B
Shape
(45,)
(45,)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
45
1
drF
(k)
float32
dask.array<chunksize=(45,), meta=np.ndarray>
long_name : cell z size standard_name : cell_z_size units : m
Array
Chunk
Bytes
180 B
180 B
Shape
(45,)
(45,)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
45
1
dxC
(j, i_g)
float32
dask.array<chunksize=(1146, 720), meta=np.ndarray>
coordinate : YC XG long_name : cell x size standard_name : cell_x_size_at_u_location units : m
Array
Chunk
Bytes
3.15 MiB
3.15 MiB
Shape
(1146, 720)
(1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
dxF
(j, i)
float32
dask.array<chunksize=(1146, 720), meta=np.ndarray>
coordinate : YC XC long_name : cell x size standard_name : cell_x_size_at_t_location units : m
Array
Chunk
Bytes
3.15 MiB
3.15 MiB
Shape
(1146, 720)
(1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
dxG
(j_g, i)
float32
dask.array<chunksize=(1146, 720), meta=np.ndarray>
coordinate : YG XC long_name : cell x size standard_name : cell_x_size_at_v_location units : m
Array
Chunk
Bytes
3.15 MiB
3.15 MiB
Shape
(1146, 720)
(1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
dyC
(j_g, i)
float32
dask.array<chunksize=(1146, 720), meta=np.ndarray>
coordinate : YG XC long_name : cell y size standard_name : cell_y_size_at_v_location units : m
Array
Chunk
Bytes
3.15 MiB
3.15 MiB
Shape
(1146, 720)
(1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
dyF
(j, i)
float32
dask.array<chunksize=(1146, 720), meta=np.ndarray>
coordinate : YC XC long_name : cell y size standard_name : cell_y_size_at_t_location units : m
Array
Chunk
Bytes
3.15 MiB
3.15 MiB
Shape
(1146, 720)
(1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
dyG
(j, i_g)
float32
dask.array<chunksize=(1146, 720), meta=np.ndarray>
coordinate : YC XG long_name : cell y size standard_name : cell_y_size_at_u_location units : m
Array
Chunk
Bytes
3.15 MiB
3.15 MiB
Shape
(1146, 720)
(1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
hFacC
(k, j, i)
float32
dask.array<chunksize=(45, 1146, 720), meta=np.ndarray>
long_name : vertical fraction of open cell standard_name : cell_vertical_fraction
Array
Chunk
Bytes
141.64 MiB
141.64 MiB
Shape
(45, 1146, 720)
(45, 1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
45
hFacS
(k, j_g, i)
float32
dask.array<chunksize=(45, 1146, 720), meta=np.ndarray>
long_name : vertical fraction of open cell standard_name : cell_vertical_fraction_at_v_location
Array
Chunk
Bytes
141.64 MiB
141.64 MiB
Shape
(45, 1146, 720)
(45, 1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
45
hFacW
(k, j, i_g)
float32
dask.array<chunksize=(45, 1146, 720), meta=np.ndarray>
long_name : vertical fraction of open cell standard_name : cell_vertical_fraction_at_u_location
Array
Chunk
Bytes
141.64 MiB
141.64 MiB
Shape
(45, 1146, 720)
(45, 1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
45
i
(i)
int64
13104 13105 13106 ... 13822 13823
axis : X long_name : x-dimension of the t grid standard_name : x_grid_index swap_dim : XC array([13104, 13105, 13106, ..., 13821, 13822, 13823]) i_g
(i_g)
int64
13104 13105 13106 ... 13822 13823
axis : X c_grid_axis_shift : -0.5 long_name : x-dimension of the u grid standard_name : x_grid_index_at_u_location swap_dim : XG array([13104, 13105, 13106, ..., 13821, 13822, 13823]) j
(j)
int64
4499 4500 4501 ... 5642 5643 5644
axis : Y long_name : y-dimension of the t grid standard_name : y_grid_index swap_dim : YC array([4499, 4500, 4501, ..., 5642, 5643, 5644]) j_g
(j_g)
int64
4499 4500 4501 ... 5642 5643 5644
axis : Y c_grid_axis_shift : -0.5 long_name : y-dimension of the v grid standard_name : y_grid_index_at_v_location swap_dim : YG array([4499, 4500, 4501, ..., 5642, 5643, 5644]) k
(k)
int64
0 1 2 3 4 5 6 ... 39 40 41 42 43 44
axis : Z long_name : z-dimension of the t grid standard_name : z_grid_index swap_dim : Z array([ 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]) k_l
(k_l)
int64
0 1 2 3 4 5 6 ... 39 40 41 42 43 44
axis : Z c_grid_axis_shift : -0.5 long_name : z-dimension of the w grid standard_name : z_grid_index_at_lower_w_location swap_dim : Zl array([ 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]) rA
(j, i)
float32
dask.array<chunksize=(1146, 720), meta=np.ndarray>
coordinate : YC XC long_name : cell area standard_name : cell_area units : m2
Array
Chunk
Bytes
3.15 MiB
3.15 MiB
Shape
(1146, 720)
(1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
rAs
(j_g, i)
float32
dask.array<chunksize=(1146, 720), meta=np.ndarray>
coordinate : YG XC long_name : cell area standard_name : cell_area_at_v_location units : m2
Array
Chunk
Bytes
3.15 MiB
3.15 MiB
Shape
(1146, 720)
(1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
rAw
(j, i_g)
float32
dask.array<chunksize=(1146, 720), meta=np.ndarray>
coordinate : YG XC long_name : cell area standard_name : cell_area_at_u_location units : m2
Array
Chunk
Bytes
3.15 MiB
3.15 MiB
Shape
(1146, 720)
(1146, 720)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
rhoRef
(k)
float32
dask.array<chunksize=(45,), meta=np.ndarray>
coordinate : Z long_name : 1D, vertical reference density profile standard_name : reference_density_profile units : kg m-3
Array
Chunk
Bytes
180 B
180 B
Shape
(45,)
(45,)
Dask graph
1 chunks in 2 graph layers
Data type
float32 numpy.ndarray
45
1
time
(time)
datetime64[ns]
2011-09-13T05:30:00 ... 2012-11-...
array(['2011-09-13T05:30:00.000000000', '2011-09-13T17:30:00.000000000',
'2011-09-14T05:30:00.000000000', ..., '2012-11-14T05:30:00.000000000',
'2012-11-14T17:30:00.000000000', '2012-11-15T05:30:00.000000000'],
dtype='datetime64[ns]') Data variables: (9)
KPPhbl
(time, j, i)
float32
dask.array<chunksize=(1, 1146, 720), meta=np.ndarray>
long_name : KPP boundary layer depth, bulk Ri criterion standard_name : KPP_boundary_layer units : m
Array
Chunk
Bytes
2.64 GiB
3.15 MiB
Shape
(859, 1146, 720)
(1, 1146, 720)
Dask graph
859 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
859
Salt
(time, k, j, i)
float32
dask.array<chunksize=(1, 45, 1146, 720), meta=np.ndarray>
long_name : Salinity standard_name : SALT units : psu
Array
Chunk
Bytes
118.82 GiB
141.64 MiB
Shape
(859, 45, 1146, 720)
(1, 45, 1146, 720)
Dask graph
859 chunks in 2 graph layers
Data type
float32 numpy.ndarray
859
1
720
1146
45
Theta
(time, k, j, i)
float32
dask.array<chunksize=(1, 45, 1146, 720), meta=np.ndarray>
long_name : Potential Temperature standard_name : THETA units : degC
Array
Chunk
Bytes
118.82 GiB
141.64 MiB
Shape
(859, 45, 1146, 720)
(1, 45, 1146, 720)
Dask graph
859 chunks in 2 graph layers
Data type
float32 numpy.ndarray
859
1
720
1146
45
U
(time, k, j, i_g)
float32
dask.array<chunksize=(1, 45, 1146, 720), meta=np.ndarray>
long_name : Zonal Component of Velocity mate : V standard_name : sea_water_x_velocity units : m s-1
Array
Chunk
Bytes
118.82 GiB
141.64 MiB
Shape
(859, 45, 1146, 720)
(1, 45, 1146, 720)
Dask graph
859 chunks in 2 graph layers
Data type
float32 numpy.ndarray
859
1
720
1146
45
V
(time, k, j_g, i)
float32
dask.array<chunksize=(1, 45, 1146, 720), meta=np.ndarray>
long_name : Meridional Component of Velocity mate : U standard_name : sea_water_y_velocity units : m s-1
Array
Chunk
Bytes
118.82 GiB
141.64 MiB
Shape
(859, 45, 1146, 720)
(1, 45, 1146, 720)
Dask graph
859 chunks in 2 graph layers
Data type
float32 numpy.ndarray
859
1
720
1146
45
W
(time, k_l, j, i)
float32
dask.array<chunksize=(1, 45, 1146, 720), meta=np.ndarray>
long_name : Vertical Component of Velocity standard_name : sea_water_z_velocity units : m s-1
Array
Chunk
Bytes
118.82 GiB
141.64 MiB
Shape
(859, 45, 1146, 720)
(1, 45, 1146, 720)
Dask graph
859 chunks in 2 graph layers
Data type
float32 numpy.ndarray
859
1
720
1146
45
oceQnet
(time, j, i)
float32
dask.array<chunksize=(1, 1146, 720), meta=np.ndarray>
long_name : net surface heat flux into the ocean (+=down), >0 increases theta standard_name : oceQnet units : W/m^2
Array
Chunk
Bytes
2.64 GiB
3.15 MiB
Shape
(859, 1146, 720)
(1, 1146, 720)
Dask graph
859 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
859
oceTAUX
(time, j, i_g)
float32
dask.array<chunksize=(1, 1146, 720), meta=np.ndarray>
long_name : zonal surface wind stress, >0 increases uVel mate : oceTAUY standard_name : oceTAUX units : N/m^2
Array
Chunk
Bytes
2.64 GiB
3.15 MiB
Shape
(859, 1146, 720)
(1, 1146, 720)
Dask graph
859 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
859
oceTAUY
(time, j_g, i)
float32
dask.array<chunksize=(1, 1146, 720), meta=np.ndarray>
long_name : meridional surf. wind stress, >0 increases vVel mate : oceTAUX standard_name : oceTAUY units : N/m^2
Array
Chunk
Bytes
2.64 GiB
3.15 MiB
Shape
(859, 1146, 720)
(1, 1146, 720)
Dask graph
859 chunks in 2 graph layers
Data type
float32 numpy.ndarray
720
1146
859
Indexes: (7)
PandasIndex
PandasIndex(Index([13104, 13105, 13106, 13107, 13108, 13109, 13110, 13111, 13112, 13113,
...
13814, 13815, 13816, 13817, 13818, 13819, 13820, 13821, 13822, 13823],
dtype='int64', name='i', length=720)) PandasIndex
PandasIndex(Index([13104, 13105, 13106, 13107, 13108, 13109, 13110, 13111, 13112, 13113,
...
13814, 13815, 13816, 13817, 13818, 13819, 13820, 13821, 13822, 13823],
dtype='int64', name='i_g', length=720)) PandasIndex
PandasIndex(Index([4499, 4500, 4501, 4502, 4503, 4504, 4505, 4506, 4507, 4508,
...
5635, 5636, 5637, 5638, 5639, 5640, 5641, 5642, 5643, 5644],
dtype='int64', name='j', length=1146)) PandasIndex
PandasIndex(Index([4499, 4500, 4501, 4502, 4503, 4504, 4505, 4506, 4507, 4508,
...
5635, 5636, 5637, 5638, 5639, 5640, 5641, 5642, 5643, 5644],
dtype='int64', name='j_g', length=1146)) PandasIndex
PandasIndex(Index([ 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],
dtype='int64', name='k')) PandasIndex
PandasIndex(Index([ 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],
dtype='int64', name='k_l')) PandasIndex
PandasIndex(DatetimeIndex(['2011-09-13 05:30:00', '2011-09-13 17:30:00',
'2011-09-14 05:30:00', '2011-09-14 17:30:00',
'2011-09-15 05:30:00', '2011-09-15 17:30:00',
'2011-09-16 05:30:00', '2011-09-16 17:30:00',
'2011-09-17 05:30:00', '2011-09-17 17:30:00',
...
'2012-11-10 17:30:00', '2012-11-11 05:30:00',
'2012-11-11 17:30:00', '2012-11-12 05:30:00',
'2012-11-12 17:30:00', '2012-11-13 05:30:00',
'2012-11-13 17:30:00', '2012-11-14 05:30:00',
'2012-11-14 17:30:00', '2012-11-15 05:30:00'],
dtype='datetime64[ns]', name='time', length=859, freq=None)) Attributes: (0)