<xarray.Dataset> Size: 13MB
Dimensions:         (tracer: 3, ocean_time: 0, s_rho: 20, s_w: 21, boundary: 4,
                     eta_rho: 291, xi_rho: 332, eta_psi: 290, xi_psi: 331,
                     eta_u: 291, xi_u: 331, eta_v: 290, xi_v: 332)
Coordinates:
  * ocean_time      (ocean_time) datetime64[ns] 0B 
    lat_psi         (eta_psi, xi_psi) float64 768kB dask.array<chunksize=(290, 331), meta=np.ndarray>
    lat_rho         (eta_rho, xi_rho) float64 773kB dask.array<chunksize=(291, 332), meta=np.ndarray>
    lat_u           (eta_u, xi_u) float64 771kB dask.array<chunksize=(291, 331), meta=np.ndarray>
    lat_v           (eta_v, xi_v) float64 770kB dask.array<chunksize=(290, 332), meta=np.ndarray>
    lon_psi         (eta_psi, xi_psi) float64 768kB dask.array<chunksize=(290, 331), meta=np.ndarray>
    lon_rho         (eta_rho, xi_rho) float64 773kB dask.array<chunksize=(291, 332), meta=np.ndarray>
    lon_u           (eta_u, xi_u) float64 771kB dask.array<chunksize=(291, 331), meta=np.ndarray>
    lon_v           (eta_v, xi_v) float64 770kB dask.array<chunksize=(290, 332), meta=np.ndarray>
  * s_rho           (s_rho) float64 160B -0.975 -0.925 -0.875 ... -0.075 -0.025
  * s_w             (s_w) float64 168B -1.0 -0.95 -0.9 -0.85 ... -0.1 -0.05 0.0
Dimensions without coordinates: tracer, boundary, eta_rho, xi_rho, eta_psi,
                                xi_psi, eta_u, xi_u, eta_v, xi_v
Data variables: (12/99)
    Akk_bak         float64 8B ...
    Akp_bak         float64 8B ...
    Akt_bak         (tracer) float64 24B dask.array<chunksize=(3,), meta=np.ndarray>
    Akv_bak         float64 8B ...
    BioIter         (ocean_time) float64 0B dask.array<chunksize=(0,), meta=np.ndarray>
    Charnok_alpha   (ocean_time) float64 0B dask.array<chunksize=(0,), meta=np.ndarray>
    ...              ...
    w               (ocean_time, s_w, eta_rho, xi_rho) float32 0B dask.array<chunksize=(0, 21, 291, 332), meta=np.ndarray>
    xl              float64 8B ...
    zeta            (ocean_time, eta_rho, xi_rho) float32 0B dask.array<chunksize=(0, 291, 332), meta=np.ndarray>
    zeta_mllw       (ocean_time, eta_rho, xi_rho) float64 0B dask.array<chunksize=(0, 291, 332), meta=np.ndarray>
    u_rotated       (ocean_time, s_rho, eta_rho, xi_rho) float64 0B dask.array<chunksize=(0, 20, 291, 332), meta=np.ndarray>
    v_rotated       (ocean_time, s_rho, eta_rho, xi_rho) float64 0B dask.array<chunksize=(0, 20, 291, 332), meta=np.ndarray>
Attributes: (12/39)
    CPP_options:       mode, ADD_FSOBC, ADD_M2OBC, ANA_BPFLUX, ANA_BSFLUX, AN...
    Conventions:       CF-1.4, SGRID-0.3
    NLM_LBC:           \nEDGE:    WEST   SOUTH  EAST   NORTH  \nzeta:    Clo ...
    NLM_TADV:          \nADVECTION:   HORIZONTAL   VERTICAL     \ntemp:      ...
    ana_file:          ROMS/Functionals/ana_btflux.h, ROMS/Functionals/ana_ra...
    bio_file:          ROMS/Nonlinear/Biology/hypoxia_srm.h
    ...                ...
    tide_file:         cbofs.roms.tides.nc
    tiling:            008x016
    title:             cbofs forecast RUN in operational mode
    type:              ROMS/TOMS history file
    var_info:          varinfo.yaml
    _xpublish_id:      subset/cbofs/subset?SubsetQuery(points=None, time=('20...

xarray.Dataset

Dimensions:
- tracer: 3
- ocean_time: 0
- s_rho: 20
- s_w: 21
- boundary: 4
- eta_rho: 291
- xi_rho: 332
- eta_psi: 290
- xi_psi: 331
- eta_u: 291
- xi_u: 331
- eta_v: 290
- xi_v: 332

Coordinates: (11)

ocean_time
(ocean_time)
datetime64[ns]
field :
time
long_name :
time since initialization
standard_name :
time
```
array([], dtype='datetime64[ns]')
```

lat_psi

(eta_psi, xi_psi)

float64

dask.array<chunksize=(290, 331), meta=np.ndarray>

field :: lat_psi
long_name :: latitude of PSI-points
standard_name :: grid_latitude_at_cell_corners
units :: degree_north

	Array	Chunk
Bytes	749.92 kiB	749.92 kiB
Shape	(290, 331)	(290, 331)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

lat_rho

(eta_rho, xi_rho)

float64

dask.array<chunksize=(291, 332), meta=np.ndarray>

field :: lat_rho
long_name :: latitude of RHO-points
standard_name :: grid_latitude_at_cell_center
units :: degree_north

	Array	Chunk
Bytes	754.78 kiB	754.78 kiB
Shape	(291, 332)	(291, 332)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

lat_u

(eta_u, xi_u)

float64

dask.array<chunksize=(291, 331), meta=np.ndarray>

field :: lat_u
long_name :: latitude of U-points
standard_name :: grid_latitude_at_cell_y_edges
units :: degree_north

	Array	Chunk
Bytes	752.51 kiB	752.51 kiB
Shape	(291, 331)	(291, 331)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

lat_v

(eta_v, xi_v)

float64

dask.array<chunksize=(290, 332), meta=np.ndarray>

field :: lat_v
long_name :: latitude of V-points
standard_name :: grid_latitude_at_cell_x_edges
units :: degree_north

	Array	Chunk
Bytes	752.19 kiB	752.19 kiB
Shape	(290, 332)	(290, 332)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

lon_psi

(eta_psi, xi_psi)

float64

dask.array<chunksize=(290, 331), meta=np.ndarray>

field :: lon_psi
long_name :: longitude of PSI-points
standard_name :: grid_longitude_at_cell_corners
units :: degree_east

	Array	Chunk
Bytes	749.92 kiB	749.92 kiB
Shape	(290, 331)	(290, 331)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

lon_rho

(eta_rho, xi_rho)

float64

dask.array<chunksize=(291, 332), meta=np.ndarray>

field :: lon_rho
long_name :: longitude of RHO-points
standard_name :: grid_longitude_at_cell_center
units :: degree_east

	Array	Chunk
Bytes	754.78 kiB	754.78 kiB
Shape	(291, 332)	(291, 332)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

lon_u

(eta_u, xi_u)

float64

dask.array<chunksize=(291, 331), meta=np.ndarray>

field :: lon_u
long_name :: longitude of U-points
standard_name :: grid_longitude_at_cell_y_edges
units :: degree_east

	Array	Chunk
Bytes	752.51 kiB	752.51 kiB
Shape	(291, 331)	(291, 331)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

lon_v

(eta_v, xi_v)

float64

dask.array<chunksize=(290, 332), meta=np.ndarray>

field :: lon_v
long_name :: longitude of V-points
standard_name :: grid_longitude_at_cell_x_edges
units :: degree_east

	Array	Chunk
Bytes	752.19 kiB	752.19 kiB
Shape	(290, 332)	(290, 332)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

s_rho
(s_rho)
float64
-0.975 -0.925 ... -0.075 -0.025
formula_terms :
s: s_rho C: Cs_r eta: zeta depth: h depth_c: hc
long_name :
S-coordinate at RHO-points
positive :
up
standard_name :
ocean_s_coordinate_g1
valid_max :
0.0
valid_min :
-1.0
```
array([-0.975, -0.925, -0.875, -0.825, -0.775, -0.725, -0.675, -0.625, -0.575,
       -0.525, -0.475, -0.425, -0.375, -0.325, -0.275, -0.225, -0.175, -0.125,
       -0.075, -0.025])
```
s_w
(s_w)
float64
-1.0 -0.95 -0.9 ... -0.1 -0.05 0.0
formula_terms :
s: s_w C: Cs_w eta: zeta depth: h depth_c: hc
long_name :
S-coordinate at W-points
positive :
up
standard_name :
ocean_s_coordinate_g1
valid_max :
0.0
valid_min :
-1.0
```
array([-1.  , -0.95, -0.9 , -0.85, -0.8 , -0.75, -0.7 , -0.65, -0.6 , -0.55,
       -0.5 , -0.45, -0.4 , -0.35, -0.3 , -0.25, -0.2 , -0.15, -0.1 , -0.05,
        0.  ])
```

Data variables: (99)

Akk_bak
()
float64
...
long_name :
background vertical mixing coefficient for turbulent energy
units :
meter2 second-1
```
[1 values with dtype=float64]
```
Akp_bak
()
float64
...
long_name :
background vertical mixing coefficient for length scale
units :
meter2 second-1
```
[1 values with dtype=float64]
```

Akt_bak

(tracer)

float64

dask.array<chunksize=(3,), meta=np.ndarray>

long_name :: background vertical mixing coefficient for tracers
units :: meter2 second-1

	Array	Chunk
Bytes	24 B	24 B
Shape	(3,)	(3,)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

Akv_bak
()
float64
...
long_name :
background vertical mixing coefficient for momentum
units :
meter2 second-1
```
[1 values with dtype=float64]
```

BioIter

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: number of iterations to achieve convergence

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

Charnok_alpha

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: Charnock factor for surface roughness

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

CrgBan_cw

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: surface flux due to Craig and Banner wave breaking

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

Cs_r

(s_rho)

float64

dask.array<chunksize=(20,), meta=np.ndarray>

long_name :: S-coordinate stretching curves at RHO-points
valid_max :: 0.0
valid_min :: -1.0

	Array	Chunk
Bytes	160 B	160 B
Shape	(20,)	(20,)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

Cs_w

(s_w)

float64

dask.array<chunksize=(21,), meta=np.ndarray>

long_name :: S-coordinate stretching curves at W-points
valid_max :: 0.0
valid_min :: -1.0

	Array	Chunk
Bytes	168 B	168 B
Shape	(21,)	(21,)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

FSobc_in

(boundary)

float64

dask.array<chunksize=(4,), meta=np.ndarray>

long_name :: free-surface inflow, nudging inverse time scale
units :: second-1

	Array	Chunk
Bytes	32 B	32 B
Shape	(4,)	(4,)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

FSobc_out

(boundary)

float64

dask.array<chunksize=(4,), meta=np.ndarray>

long_name :: free-surface outflow, nudging inverse time scale
units :: second-1

	Array	Chunk
Bytes	32 B	32 B
Shape	(4,)	(4,)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

Falpha
()
float64
...
long_name :
Power-law shape barotropic filter parameter
```
[1 values with dtype=float64]
```
Fbeta
()
float64
...
long_name :
Power-law shape barotropic filter parameter
```
[1 values with dtype=float64]
```
Fgamma
()
float64
...
long_name :
Power-law shape barotropic filter parameter
```
[1 values with dtype=float64]
```
Lm2CLM
()
float64
...
flag_meanings :
.FALSE. .TRUE.
flag_values :
[0, 1]
long_name :
2D momentum climatology processing switch
```
[1 values with dtype=float64]
```
Lm3CLM
()
float64
...
flag_meanings :
.FALSE. .TRUE.
flag_values :
[0, 1]
long_name :
3D momentum climatology processing switch
```
[1 values with dtype=float64]
```
LnudgeM2CLM
()
float64
...
flag_meanings :
.FALSE. .TRUE.
flag_values :
[0, 1]
long_name :
2D momentum climatology nudging activation switch
```
[1 values with dtype=float64]
```
LnudgeM3CLM
()
float64
...
flag_meanings :
.FALSE. .TRUE.
flag_values :
[0, 1]
long_name :
3D momentum climatology nudging activation switch
```
[1 values with dtype=float64]
```

LnudgeTCLM

(tracer)

float64

dask.array<chunksize=(3,), meta=np.ndarray>

flag_meanings :: .FALSE. .TRUE.
flag_values :: [0, 1]
long_name :: tracer climatology nudging activation switch

	Array	Chunk
Bytes	24 B	24 B
Shape	(3,)	(3,)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

LsshCLM
()
float64
...
flag_meanings :
.FALSE. .TRUE.
flag_values :
[0, 1]
long_name :
sea surface height climatology processing switch
```
[1 values with dtype=float64]
```

LtracerCLM

(tracer)

float64

dask.array<chunksize=(3,), meta=np.ndarray>

flag_meanings :: .FALSE. .TRUE.
flag_values :: [0, 1]
long_name :: tracer climatology processing switch

	Array	Chunk
Bytes	24 B	24 B
Shape	(3,)	(3,)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

LtracerSponge

(tracer)

float64

dask.array<chunksize=(3,), meta=np.ndarray>

flag_meanings :: .FALSE. .TRUE.
flag_values :: [0, 1]
long_name :: horizontal diffusivity sponge activation switch

	Array	Chunk
Bytes	24 B	24 B
Shape	(3,)	(3,)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

LtracerSrc

(tracer)

float64

dask.array<chunksize=(3,), meta=np.ndarray>

flag_meanings :: .FALSE. .TRUE.
flag_values :: [0, 1]
long_name :: tracer point sources and sink activation switch

	Array	Chunk
Bytes	24 B	24 B
Shape	(3,)	(3,)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

LuvSponge
()
float64
...
flag_meanings :
.FALSE. .TRUE.
flag_values :
[0, 1]
long_name :
horizontal viscosity sponge activation switch
```
[1 values with dtype=float64]
```
LuvSrc
()
float64
...
flag_meanings :
.FALSE. .TRUE.
flag_values :
[0, 1]
long_name :
momentum point sources and sink activation switch
```
[1 values with dtype=float64]
```
LwSrc
()
float64
...
flag_meanings :
.FALSE. .TRUE.
flag_values :
[0, 1]
long_name :
mass point sources and sink activation switch
```
[1 values with dtype=float64]
```

M2nudg

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: 2D momentum nudging/relaxation inverse time scale
units :: day-1

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

M2obc_in

(boundary)

float64

dask.array<chunksize=(4,), meta=np.ndarray>

long_name :: 2D momentum inflow, nudging inverse time scale
units :: second-1

	Array	Chunk
Bytes	32 B	32 B
Shape	(4,)	(4,)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

M2obc_out

(boundary)

float64

dask.array<chunksize=(4,), meta=np.ndarray>

long_name :: 2D momentum outflow, nudging inverse time scale
units :: second-1

	Array	Chunk
Bytes	32 B	32 B
Shape	(4,)	(4,)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

M3nudg

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: 3D momentum nudging/relaxation inverse time scale
units :: day-1

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

M3obc_in

(boundary)

float64

dask.array<chunksize=(4,), meta=np.ndarray>

long_name :: 3D momentum inflow, nudging inverse time scale
units :: second-1

	Array	Chunk
Bytes	32 B	32 B
Shape	(4,)	(4,)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

M3obc_out

(boundary)

float64

dask.array<chunksize=(4,), meta=np.ndarray>

long_name :: 3D momentum outflow, nudging inverse time scale
units :: second-1

	Array	Chunk
Bytes	32 B	32 B
Shape	(4,)	(4,)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

Pair

(ocean_time, eta_rho, xi_rho)

float32

dask.array<chunksize=(0, 291, 332), meta=np.ndarray>

cell_methods :: ocean_time: point
field :: surface air pressure
grid :: grid
location :: face
long_name :: surface air pressure
standard_name :: surface_air_pressure
time :: ocean_time
units :: millibar

	Array	Chunk
Bytes	0 B	0 B
Shape	(0, 291, 332)	(0, 291, 332)
Dask graph	1 chunks in 3 graph layers
Data type	float32 numpy.ndarray

ResRate

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: total biological respiration rate
units :: day-1

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

Tcline
()
float64
...
long_name :
S-coordinate surface/bottom layer width
units :
meter
```
[1 values with dtype=float64]
```

Tnudg

(ocean_time, tracer)

float64

dask.array<chunksize=(0, 3), meta=np.ndarray>

long_name :: Tracers nudging/relaxation inverse time scale
units :: day-1

	Array	Chunk
Bytes	0 B	0 B
Shape	(0, 3)	(0, 3)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

Tobc_in

(boundary, tracer)

float64

dask.array<chunksize=(4, 3), meta=np.ndarray>

long_name :: tracers inflow, nudging inverse time scale
units :: second-1

	Array	Chunk
Bytes	96 B	96 B
Shape	(4, 3)	(4, 3)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

Tobc_out

(boundary, tracer)

float64

dask.array<chunksize=(4, 3), meta=np.ndarray>

long_name :: tracers outflow, nudging inverse time scale
units :: second-1

	Array	Chunk
Bytes	96 B	96 B
Shape	(4, 3)	(4, 3)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

Uwind

(ocean_time, eta_rho, xi_rho)

float32

dask.array<chunksize=(0, 291, 332), meta=np.ndarray>

cell_methods :: ocean_time: point
field :: u-wind
grid :: grid
location :: face
long_name :: surface u-wind component
standard_name :: surface_x_wind
time :: ocean_time
units :: meter second-1

	Array	Chunk
Bytes	0 B	0 B
Shape	(0, 291, 332)	(0, 291, 332)
Dask graph	1 chunks in 3 graph layers
Data type	float32 numpy.ndarray

Vstretching
()
float64
...
long_name :
vertical terrain-following stretching function
```
[1 values with dtype=float64]
```
Vtransform
()
float64
...
long_name :
vertical terrain-following transformation equation
```
[1 values with dtype=float64]
```

Vwind

(ocean_time, eta_rho, xi_rho)

float32

dask.array<chunksize=(0, 291, 332), meta=np.ndarray>

cell_methods :: ocean_time: point
field :: v-wind
grid :: grid
location :: face
long_name :: surface v-wind component
standard_name :: surface_y_wind
time :: ocean_time
units :: meter second-1

	Array	Chunk
Bytes	0 B	0 B
Shape	(0, 291, 332)	(0, 291, 332)
Dask graph	1 chunks in 3 graph layers
Data type	float32 numpy.ndarray

Znudg

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: free-surface nudging/relaxation inverse time scale
units :: day-1

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

Zob
()
float64
...
long_name :
bottom roughness
units :
meter
```
[1 values with dtype=float64]
```
Zos
()
float64
...
long_name :
surface roughness
units :
meter
```
[1 values with dtype=float64]
```

Zos_hsig_alpha

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: wave amplitude factor for surface roughness

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

angle

(eta_rho, xi_rho)

float64

dask.array<chunksize=(291, 332), meta=np.ndarray>

field :: angle
grid :: grid
location :: face
long_name :: angle between XI-axis and EAST
standard_name :: grid_angle_of_rotation_from_east_to_y
units :: radians

	Array	Chunk
Bytes	754.78 kiB	754.78 kiB
Shape	(291, 332)	(291, 332)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: size of long time-steps
units :: second

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

dtfast

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: size of short time-steps
units :: second

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

el
()
float64
...
long_name :
domain length in the ETA-direction
units :
meter
```
[1 values with dtype=float64]
```

(eta_rho, xi_rho)

float64

dask.array<chunksize=(291, 332), meta=np.ndarray>

field :: coriolis
grid :: grid
location :: face
long_name :: Coriolis parameter
standard_name :: coriolis_parameter
units :: second-1

	Array	Chunk
Bytes	754.78 kiB	754.78 kiB
Shape	(291, 332)	(291, 332)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

gamma2
()
float64
...
long_name :
slipperiness parameter
```
[1 values with dtype=float64]
```

gls_Kmin

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: minimum value of specific turbulent kinetic energy

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

gls_Pmin

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: minimum Value of dissipation

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

gls_c1

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: shear production coefficient

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

gls_c2

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: dissipation coefficient

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

gls_c3m

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: buoyancy production coefficient (minus)

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

gls_c3p

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: buoyancy production coefficient (plus)

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

gls_cmu0

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: stability coefficient

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

gls_m

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: turbulent kinetic energy exponent

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

gls_n

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: turbulent length scale exponent

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

gls_p

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: stability exponent

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

gls_sigk

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: constant Schmidt number for TKE

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

gls_sigp

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: constant Schmidt number for PSI

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

grid
()
float64
...
cf_role :
grid_topology
edge1_coordinates :
lon_u lat_u
edge1_dimensions :
xi_u: xi_psi eta_u: eta_psi (padding: both)
edge2_coordinates :
lon_v lat_v
edge2_dimensions :
xi_v: xi_psi (padding: both) eta_v: eta_psi
face_coordinates :
lon_rho lat_rho
face_dimensions :
xi_rho: xi_psi (padding: both) eta_rho: eta_psi (padding: both)
node_coordinates :
lon_psi lat_psi
node_dimensions :
xi_psi eta_psi
topology_dimension :
2
vertical_dimensions :
s_rho: s_w (padding: none)
```
[1 values with dtype=float64]
```

(eta_rho, xi_rho)

float64

dask.array<chunksize=(291, 332), meta=np.ndarray>

field :: bathymetry
grid :: grid
location :: face
long_name :: time-independent bathymetry
standard_name :: sea_floor_depth
units :: meter

	Array	Chunk
Bytes	754.78 kiB	754.78 kiB
Shape	(291, 332)	(291, 332)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

hc
()
float64
...
long_name :
S-coordinate parameter, critical depth
units :
meter
```
[1 values with dtype=float64]
```

mask_psi

(eta_psi, xi_psi)

float64

dask.array<chunksize=(290, 331), meta=np.ndarray>

flag_meanings :: land water
flag_values :: [0.0, 1.0]
grid :: grid
location :: node
long_name :: mask on PSI-points
standard_name :: land_sea_mask_at_cell_corners

	Array	Chunk
Bytes	749.92 kiB	749.92 kiB
Shape	(290, 331)	(290, 331)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

mask_rho

(eta_rho, xi_rho)

float64

dask.array<chunksize=(291, 332), meta=np.ndarray>

flag_meanings :: land water
flag_values :: [0.0, 1.0]
grid :: grid
location :: face
long_name :: mask on RHO-points
standard_name :: land_sea_mask_at_cell_center

	Array	Chunk
Bytes	754.78 kiB	754.78 kiB
Shape	(291, 332)	(291, 332)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

mask_u

(eta_u, xi_u)

float64

dask.array<chunksize=(291, 331), meta=np.ndarray>

flag_meanings :: land water
flag_values :: [0.0, 1.0]
grid :: grid
location :: edge1
long_name :: mask on U-points
standard_name :: land_sea_mask_at_cell_y_edges

	Array	Chunk
Bytes	752.51 kiB	752.51 kiB
Shape	(291, 331)	(291, 331)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

mask_v

(eta_v, xi_v)

float64

dask.array<chunksize=(290, 332), meta=np.ndarray>

flag_meanings :: land water
flag_values :: [0.0, 1.0]
grid :: grid
location :: edge2
long_name :: mask on V-points
standard_name :: land_sea_mask_at_cell_x_edges

	Array	Chunk
Bytes	752.19 kiB	752.19 kiB
Shape	(290, 332)	(290, 332)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

nHIS
()
float64
...
long_name :
number of time-steps between history records
```
[1 values with dtype=float64]
```
nRST
()
float64
...
cycle :
only latest two records are maintained
long_name :
number of time-steps between restart records
```
[1 values with dtype=float64]
```
nSTA
()
float64
...
long_name :
number of time-steps between stations records
```
[1 values with dtype=float64]
```
ndefHIS
()
float64
...
long_name :
number of time-steps between the creation of history files
```
[1 values with dtype=float64]
```
ndtfast
()
float64
...
long_name :
number of short time-steps
```
[1 values with dtype=float64]
```

nl_tnu2

(tracer)

float64

dask.array<chunksize=(3,), meta=np.ndarray>

long_name :: nonlinear model Laplacian mixing coefficient for tracers
units :: meter2 second-1

	Array	Chunk
Bytes	24 B	24 B
Shape	(3,)	(3,)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

nl_visc2
()
float64
...
long_name :
nonlinear model Laplacian mixing coefficient for momentum
units :
meter2 second-1
```
[1 values with dtype=float64]
```

ntimes

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: number of long time-steps

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

oxygen

(ocean_time, s_rho, eta_rho, xi_rho)

float32

dask.array<chunksize=(0, 20, 291, 332), meta=np.ndarray>

cell_methods :: ocean_time: point
field :: oxygen
grid :: grid
location :: face
long_name :: dissolved oxygen concentration
standard_name :: mole_concentration_of_dissolved_oxygen_in_sea_water
time :: ocean_time
units :: millimole_oxygen meter-3

	Array	Chunk
Bytes	0 B	0 B
Shape	(0, 20, 291, 332)	(0, 20, 291, 332)
Dask graph	1 chunks in 3 graph layers
Data type	float32 numpy.ndarray

(eta_rho, xi_rho)

float64

dask.array<chunksize=(291, 332), meta=np.ndarray>

field :: pm
grid :: grid
location :: face
long_name :: curvilinear coordinate metric in XI
standard_name :: inverse_grid_x_spacing
units :: meter-1

	Array	Chunk
Bytes	754.78 kiB	754.78 kiB
Shape	(291, 332)	(291, 332)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

(eta_rho, xi_rho)

float64

dask.array<chunksize=(291, 332), meta=np.ndarray>

field :: pn
grid :: grid
location :: face
long_name :: curvilinear coordinate metric in ETA
standard_name :: inverse_grid_y_spacing
units :: meter-1

	Array	Chunk
Bytes	754.78 kiB	754.78 kiB
Shape	(291, 332)	(291, 332)
Dask graph	1 chunks in 2 graph layers
Data type	float64 numpy.ndarray

rdrg
()
float64
...
long_name :
linear drag coefficient
units :
meter second-1
```
[1 values with dtype=float64]
```
rdrg2
()
float64
...
long_name :
quadratic drag coefficient
```
[1 values with dtype=float64]
```
rho0
()
float64
...
long_name :
mean density used in Boussinesq approximation
units :
kilogram meter-3
```
[1 values with dtype=float64]
```

salt

(ocean_time, s_rho, eta_rho, xi_rho)

float32

dask.array<chunksize=(0, 20, 291, 332), meta=np.ndarray>

cell_methods :: ocean_time: point
field :: salinity
grid :: grid
location :: face
long_name :: salinity
standard_name :: sea_water_practical_salinity
time :: ocean_time

	Array	Chunk
Bytes	0 B	0 B
Shape	(0, 20, 291, 332)	(0, 20, 291, 332)
Dask graph	1 chunks in 3 graph layers
Data type	float32 numpy.ndarray

spherical
()
float64
...
flag_meanings :
Cartesian spherical
flag_values :
[0, 1]
long_name :
grid type logical switch
```
[1 values with dtype=float64]
```

sz_alpha

(ocean_time)

float64

dask.array<chunksize=(0,), meta=np.ndarray>

long_name :: surface flux from wave dissipation

	Array	Chunk
Bytes	0 B	0 B
Shape	(0,)	(0,)
Dask graph	1 chunks in 3 graph layers
Data type	float64 numpy.ndarray

temp

(ocean_time, s_rho, eta_rho, xi_rho)

float32

dask.array<chunksize=(0, 20, 291, 332), meta=np.ndarray>

cell_methods :: ocean_time: point
field :: temperature
grid :: grid
location :: face
long_name :: potential temperature
standard_name :: sea_water_potential_temperature
time :: ocean_time
units :: Celsius

	Array	Chunk
Bytes	0 B	0 B
Shape	(0, 20, 291, 332)	(0, 20, 291, 332)
Dask graph	1 chunks in 3 graph layers
Data type	float32 numpy.ndarray

theta_b
()
float64
...
long_name :
S-coordinate bottom control parameter
```
[1 values with dtype=float64]
```
theta_s
()
float64
...
long_name :
S-coordinate surface control parameter
```
[1 values with dtype=float64]
```

(ocean_time, s_rho, eta_u, xi_u)

float32

dask.array<chunksize=(0, 20, 291, 331), meta=np.ndarray>

cell_methods :: ocean_time: point
field :: u-velocity
grid :: grid
location :: edge1
long_name :: u-momentum component
standard_name :: sea_water_x_velocity
time :: ocean_time
units :: meter second-1

	Array	Chunk
Bytes	0 B	0 B
Shape	(0, 20, 291, 331)	(0, 20, 291, 331)
Dask graph	1 chunks in 3 graph layers
Data type	float32 numpy.ndarray

(ocean_time, s_rho, eta_v, xi_v)

float32

dask.array<chunksize=(0, 20, 290, 332), meta=np.ndarray>

cell_methods :: ocean_time: point
field :: v-velocity
grid :: grid
location :: edge2
long_name :: v-momentum component
standard_name :: sea_water_y_velocity
time :: ocean_time
units :: meter second-1

	Array	Chunk
Bytes	0 B	0 B
Shape	(0, 20, 290, 332)	(0, 20, 290, 332)
Dask graph	1 chunks in 3 graph layers
Data type	float32 numpy.ndarray

(ocean_time, s_w, eta_rho, xi_rho)

float32

dask.array<chunksize=(0, 21, 291, 332), meta=np.ndarray>

cell_methods :: ocean_time: point
field :: w-velocity
grid :: grid
location :: face
long_name :: vertical momentum component
standard_name :: upward_sea_water_velocity
time :: ocean_time
units :: meter second-1

	Array	Chunk
Bytes	0 B	0 B
Shape	(0, 21, 291, 332)	(0, 21, 291, 332)
Dask graph	1 chunks in 3 graph layers
Data type	float32 numpy.ndarray

xl
()
float64
...
long_name :
domain length in the XI-direction
units :
meter
```
[1 values with dtype=float64]
```

zeta

(ocean_time, eta_rho, xi_rho)

float32

dask.array<chunksize=(0, 291, 332), meta=np.ndarray>

cell_methods :: ocean_time: point
field :: free-surface
grid :: grid
location :: face
long_name :: free-surface
standard_name :: sea_surface_height_above_geopotential_datum
time :: ocean_time
units :: meter

	Array	Chunk
Bytes	0 B	0 B
Shape	(0, 291, 332)	(0, 291, 332)
Dask graph	1 chunks in 3 graph layers
Data type	float32 numpy.ndarray

zeta_mllw

(ocean_time, eta_rho, xi_rho)

float64

dask.array<chunksize=(0, 291, 332), meta=np.ndarray>

cell_methods :: ocean_time: point
field :: free-surface
grid :: grid
location :: face
long_name :: free-surface
standard_name :: sea_surface_height_above_geopotential_datum
time :: ocean_time
units :: meter
datum :: mllw

	Array	Chunk
Bytes	0 B	0 B
Shape	(0, 291, 332)	(0, 291, 332)
Dask graph	1 chunks in 5 graph layers
Data type	float64 numpy.ndarray

u_rotated

(ocean_time, s_rho, eta_rho, xi_rho)

float64

dask.array<chunksize=(0, 20, 291, 332), meta=np.ndarray>

cell_methods :: ocean_time: point
field :: u-velocity
grid :: grid
location :: edge1
long_name :: u velocity rotated from ROMS grid
standard_name :: sea_water_x_velocity
time :: ocean_time
units :: meter second-1

	Array	Chunk
Bytes	0 B	0 B
Shape	(0, 20, 291, 332)	(0, 20, 291, 332)
Dask graph	1 chunks in 43 graph layers
Data type	float64 numpy.ndarray

v_rotated

(ocean_time, s_rho, eta_rho, xi_rho)

float64

dask.array<chunksize=(0, 20, 291, 332), meta=np.ndarray>

cell_methods :: ocean_time: point
field :: v-velocity
grid :: grid
location :: edge2
long_name :: v velocity rotated from ROMS grid
standard_name :: sea_water_y_velocity
time :: ocean_time
units :: meter second-1

	Array	Chunk
Bytes	0 B	0 B
Shape	(0, 20, 291, 332)	(0, 20, 291, 332)
Dask graph	1 chunks in 43 graph layers
Data type	float64 numpy.ndarray

Indexes: (3)

ocean_time

PandasIndex

PandasIndex(DatetimeIndex([], dtype='datetime64[ns]', name='ocean_time', freq=None))

s_rho

PandasIndex

PandasIndex(Index([ -0.9750000000000001,               -0.925,               -0.875,
        -0.8250000000000001,               -0.775,  -0.7250000000000001,
                     -0.675,               -0.625,  -0.5750000000000001,
                     -0.525, -0.47500000000000003, -0.42500000000000004,
                     -0.375,               -0.325,               -0.275,
                     -0.225, -0.17500000000000002,               -0.125,
       -0.07500000000000001,               -0.025],
      dtype='float64', name='s_rho'))

s_w

PandasIndex

PandasIndex(Index([                -1.0,  -0.9500000000000001,                 -0.9,
        -0.8500000000000001,                 -0.8,                -0.75,
        -0.7000000000000001,                -0.65,  -0.6000000000000001,
                      -0.55,                 -0.5,                -0.45,
                       -0.4, -0.35000000000000003, -0.30000000000000004,
                      -0.25,                 -0.2, -0.15000000000000002,
                       -0.1,                -0.05,                  0.0],
      dtype='float64', name='s_w'))

Attributes: (39)
CPP_options :
mode, ADD_FSOBC, ADD_M2OBC, ANA_BPFLUX, ANA_BSFLUX, ANA_BTFLUX, ANA_RAIN, ANA_SPFLUX, ANA_SSFLUX, ASSUMED_SHAPE, ATM_PRESS, BOUNDARY_ALLREDUCE, BULK_FLUXES, COLLECT_ALLGATHER, CURVGRID, DIFF_GRID, DJ_GRADPS, DOUBLE_PRECISION, EMINUSP, GLS_MIXING, HDF5, HYPOXIA_SRM, LIMIT_STFLX_COOLING, KANTHA_CLAYSON, LONGWAVE_OUT, MASKING, MIX_GEO_TS, MIX_S_UV, MPI, NONLINEAR, NONLIN_EOS, NO_LBC_ATT, N2S2_HORAVG, PERFECT_RESTART, POWER_LAW, PROFILE, K_GSCHEME, RADIATION_2D, REDUCE_ALLREDUCE, !RST_SINGLE, SALINITY, STEP2D_LF_AM3, SOLAR_SOURCE, SOLVE3D, SSH_TIDES, STATIONS, SURFACE_DO_SATURATION, TS_DIF2, UV_ADV, UV_COR, UV_U3HADVECTION, UV_C4VADVECTION, UV_QDRAG, UV_TIDES, UV_VIS2, VAR_RHO_2D, VISC_GRID
Conventions :
CF-1.4, SGRID-0.3
NLM_LBC :
EDGE: WEST SOUTH EAST NORTH zeta: Clo Cha Cha Clo ubar: Clo Fla Fla Clo vbar: Clo Fla Fla Clo u: Clo Rad Rad Clo v: Clo Rad Rad Clo temp: Clo RadNud RadNud Clo salt: Clo RadNud RadNud Clo oxygen: Clo RadNud RadNud Clo tke: Clo Gra Gra Clo
NLM_TADV :
ADVECTION: HORIZONTAL VERTICAL temp: HSIMT HSIMT salt: HSIMT HSIMT oxygen: HSIMT HSIMT
ana_file :
ROMS/Functionals/ana_btflux.h, ROMS/Functionals/ana_rain.h, ROMS/Functionals/ana_stflux.h
bio_file :
ROMS/Nonlinear/Biology/hypoxia_srm.h
bpar_file :
cbofs.bio.in
bry_file_01 :
cbofs.t00z.20260622.obc.nc
code_dir :
/lfs/h1/ops/test/packages/nosofs.v3.6.15/sorc/ROMS.fd
compiler_command :
/opt/cray/pe/craype/2.7.17/bin/ftn
compiler_flags :
-fp-model precise -ip -O3
compiler_system :
ftn-intel
cpu :
x86_64
file :
cbofs.t00z.20260622.fields.forecast_0002.nc
format :
netCDF-4/HDF5 file
frc_file_01 :
cbofs.t00z.20260622.met.forecast.nc
frc_file_02 :
cbofs.respirate.nc
git_rev :
c1e184cd03c2208a7b6924f2ef264d1c9feeb838
git_url :
https://github.com/NOAA-CO-OPS/2024-NOS-Code-Package_v3.6.0
grd_file :
cbofs.romsgrid.nc
header_dir :
/lfs/h1/ops/test/packages/nosofs.v3.6.15/include
header_file :
cbofs.h
his_base :
cbofs.t00z.20260622.fields.forecast
history :
ROMS/TOMS, Version 4.2, Monday - June 22, 2026 - 12:55:41 AM
ini_file :
cbofs.t00z.20260622.rst.nowcast.nc
os :
Linux
river_file :
cbofs.t00z.20260622.river.nc
rst_file :
cbofs.t00z.20260622.rst.forecast.nc
script_file :
./cbofs_ROMS_forecast.in
spos_file :
cbofs.stations.in
sta_file :
cbofs.t00z.20260622.stations.forecast.nc
svn_rev :
1209
svn_url :
https://www.myroms.org/svn/src/trunk
tide_file :
cbofs.roms.tides.nc
tiling :
008x016
title :
cbofs forecast RUN in operational mode
type :
ROMS/TOMS history file
var_info :
varinfo.yaml
_xpublish_id :
subset/cbofs/subset?SubsetQuery(points=None, time=('2025-04-24T17:35:00.000Z', '2025-04-24T21:35:00.000Z'))