xarray.Dataset

Dimensions:
- ny: 329
- nx: 553
- ocean_time: 48
- Depth: 1

Coordinates: (4)

Latitude

(ny, nx)

float64

37.41 37.41 37.41 ... 38.23 38.23

long_name :: Latitude in common grid
standard_name :: latitude
units :: degrees_north

array([[37.41  , 37.41  , 37.41  , ..., 37.41  , 37.41  , 37.41  ],
       [37.4125, 37.4125, 37.4125, ..., 37.4125, 37.4125, 37.4125],
       [37.415 , 37.415 , 37.415 , ..., 37.415 , 37.415 , 37.415 ],
       ...,
       [38.225 , 38.225 , 38.225 , ..., 38.225 , 38.225 , 38.225 ],
       [38.2275, 38.2275, 38.2275, ..., 38.2275, 38.2275, 38.2275],
       [38.23  , 38.23  , 38.23  , ..., 38.23  , 38.23  , 38.23  ]])

Longitude

(ny, nx)

float64

-123.0 -123.0 ... -121.7 -121.7

long_name :: Longitude in common grid
standard_name :: longitude
units :: degrees_east

array([[-123.04  , -123.0375, -123.035 , ..., -121.665 , -121.6625,
        -121.66  ],
       [-123.04  , -123.0375, -123.035 , ..., -121.665 , -121.6625,
        -121.66  ],
       [-123.04  , -123.0375, -123.035 , ..., -121.665 , -121.6625,
        -121.66  ],
       ...,
       [-123.04  , -123.0375, -123.035 , ..., -121.665 , -121.6625,
        -121.66  ],
       [-123.04  , -123.0375, -123.035 , ..., -121.665 , -121.6625,
        -121.66  ],
       [-123.04  , -123.0375, -123.035 , ..., -121.665 , -121.6625,
        -121.66  ]])

ocean_time

(ocean_time)

datetime64[ns]

2026-05-23 ... 2026-05-24T23:00:00

long_name :: time since initialization
field :: time, scalar, series
standard_name :: time
cell_methods :: ocean_time: mean

array(['2026-05-23T00:00:00.000000000', '2026-05-23T01:00:00.000000000',
       '2026-05-23T02:00:00.000000000', '2026-05-23T03:00:00.000000000',
       '2026-05-23T04:00:00.000000000', '2026-05-23T05:00:00.000000000',
       '2026-05-23T06:00:00.000000000', '2026-05-23T07:00:00.000000000',
       '2026-05-23T08:00:00.000000000', '2026-05-23T09:00:00.000000000',
       '2026-05-23T10:00:00.000000000', '2026-05-23T11:00:00.000000000',
       '2026-05-23T12:00:00.000000000', '2026-05-23T13:00:00.000000000',
       '2026-05-23T14:00:00.000000000', '2026-05-23T15:00:00.000000000',
       '2026-05-23T16:00:00.000000000', '2026-05-23T17:00:00.000000000',
       '2026-05-23T18:00:00.000000000', '2026-05-23T19:00:00.000000000',
       '2026-05-23T20:00:00.000000000', '2026-05-23T21:00:00.000000000',
       '2026-05-23T22:00:00.000000000', '2026-05-23T23:00:00.000000000',
       '2026-05-24T00:00:00.000000000', '2026-05-24T01:00:00.000000000',
       '2026-05-24T02:00:00.000000000', '2026-05-24T03:00:00.000000000',
       '2026-05-24T04:00:00.000000000', '2026-05-24T05:00:00.000000000',
       '2026-05-24T06:00:00.000000000', '2026-05-24T07:00:00.000000000',
       '2026-05-24T08:00:00.000000000', '2026-05-24T09:00:00.000000000',
       '2026-05-24T10:00:00.000000000', '2026-05-24T11:00:00.000000000',
       '2026-05-24T12:00:00.000000000', '2026-05-24T13:00:00.000000000',
       '2026-05-24T14:00:00.000000000', '2026-05-24T15:00:00.000000000',
       '2026-05-24T16:00:00.000000000', '2026-05-24T17:00:00.000000000',
       '2026-05-24T18:00:00.000000000', '2026-05-24T19:00:00.000000000',
       '2026-05-24T20:00:00.000000000', '2026-05-24T21:00:00.000000000',
       '2026-05-24T22:00:00.000000000', '2026-05-24T23:00:00.000000000'],
      dtype='datetime64[ns]')

Depth
(Depth)
float64
0.0
long_name :
Depths of Standard Layer
standard_name :
depth
units :
m
positive :
down
axis :
Z
```
array([0.])
```

Data variables: (8)

(ny, nx)

float64

nan nan nan nan ... nan nan nan nan

long_name :: bathymetry
units :: meter
positive :: down
grid :: grid
location :: face
field :: bath, scaler
standard_name :: sea_floor_depth_below_geoid
coverage_content_type :: modelResult

array([[nan, nan, nan, ..., nan, nan, nan],
       [nan, nan, nan, ..., nan, nan, nan],
       [nan, nan, nan, ..., nan, nan, nan],
       ...,
       [nan, nan, nan, ..., nan, nan, nan],
       [nan, nan, nan, ..., nan, nan, nan],
       [nan, nan, nan, ..., nan, nan, nan]])

mask

(ny, nx)

float64

0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

long_name :: mask
standard_name :: sea_binary_mask
flag_values :: [0. 1.]
flag_meanings :: land, water
grid :: grid
location :: face

array([[0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.],
       ...,
       [0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.]])

salt

(ocean_time, Depth, ny, nx)

float32

dask.array<chunksize=(24, 1, 165, 277), meta=np.ndarray>

long_name :: Salinity
standard_name :: sea_water_salinity
grid :: grid
location :: face
field :: salinity, scalar, series
units :: 1e-3
coverage_content_type :: modelResult
time :: ocean_time
cell_methods :: ocean_time: mean

	Array	Chunk
Bytes	33.31 MiB	4.18 MiB
Shape	(48, 1, 329, 553)	(24, 1, 165, 277)
Dask graph	8 chunks in 8 graph layers
Data type	float32 numpy.ndarray

temp

(ocean_time, Depth, ny, nx)

float32

dask.array<chunksize=(24, 1, 165, 277), meta=np.ndarray>

long_name :: Sea Water Temperature
grid :: grid
location :: face
field :: temperature, scalar, series
units :: degree_Celsius
standard_name :: sea_water_potential_temperature
coverage_content_type :: modelResult
time :: ocean_time
cell_methods :: ocean_time: mean

	Array	Chunk
Bytes	33.31 MiB	4.18 MiB
Shape	(48, 1, 329, 553)	(24, 1, 165, 277)
Dask graph	8 chunks in 8 graph layers
Data type	float32 numpy.ndarray

u_eastward

(ocean_time, Depth, ny, nx)

float32

dask.array<chunksize=(24, 1, 165, 277), meta=np.ndarray>

long_name :: eastward momentum component
standard_name :: eastward_sea_water_velocity
grid :: grid
location :: face
field :: u_eastward, scalar, series
units :: m.s-1
coverage_content_type :: modelResult
time :: ocean_time
cell_methods :: ocean_time: mean

	Array	Chunk
Bytes	33.31 MiB	4.18 MiB
Shape	(48, 1, 329, 553)	(24, 1, 165, 277)
Dask graph	8 chunks in 8 graph layers
Data type	float32 numpy.ndarray

v_northward

(ocean_time, Depth, ny, nx)

float32

dask.array<chunksize=(24, 1, 165, 277), meta=np.ndarray>

long_name :: northward momentum component
standard_name :: northward_sea_water_velocity
grid :: grid
location :: face
field :: v_northward, scalar, series
units :: m.s-1
coverage_content_type :: modelResult
time :: ocean_time
cell_methods :: ocean_time: mean

	Array	Chunk
Bytes	33.31 MiB	4.18 MiB
Shape	(48, 1, 329, 553)	(24, 1, 165, 277)
Dask graph	8 chunks in 8 graph layers
Data type	float32 numpy.ndarray

zeta

(ocean_time, ny, nx)

float32

dask.array<chunksize=(24, 165, 277), meta=np.ndarray>

long_name :: free-surface referenced to mean sea level
units :: meters
grid :: grid
location :: face
field :: free-surface, scalar, series
coverage_content_type :: modelResult
standard_name :: sea_surface_height_above_geoid
time :: ocean_time
cell_methods :: ocean_time: mean

	Array	Chunk
Bytes	33.31 MiB	4.18 MiB
Shape	(48, 329, 553)	(24, 165, 277)
Dask graph	8 chunks in 6 graph layers
Data type	float32 numpy.ndarray

zetatomllw

(ocean_time, ny, nx)

float32

dask.array<chunksize=(24, 165, 277), meta=np.ndarray>

long_name :: free-surface referenced to mean lower low water
units :: meters
grid :: grid
location :: face
field :: free-surface, scalar, series
coverage_content_type :: modelResult
standard_name :: sea_surface_height_above_mean_lower_low_water
vertical_datum :: mean lower low water
time :: ocean_time
cell_methods :: ocean_time: mean

	Array	Chunk
Bytes	33.31 MiB	4.18 MiB
Shape	(48, 329, 553)	(24, 165, 277)
Dask graph	8 chunks in 6 graph layers
Data type	float32 numpy.ndarray

Indexes: (2)

ocean_time

PandasIndex

PandasIndex(DatetimeIndex(['2026-05-23 00:00:00', '2026-05-23 01:00:00',
               '2026-05-23 02:00:00', '2026-05-23 03:00:00',
               '2026-05-23 04:00:00', '2026-05-23 05:00:00',
               '2026-05-23 06:00:00', '2026-05-23 07:00:00',
               '2026-05-23 08:00:00', '2026-05-23 09:00:00',
               '2026-05-23 10:00:00', '2026-05-23 11:00:00',
               '2026-05-23 12:00:00', '2026-05-23 13:00:00',
               '2026-05-23 14:00:00', '2026-05-23 15:00:00',
               '2026-05-23 16:00:00', '2026-05-23 17:00:00',
               '2026-05-23 18:00:00', '2026-05-23 19:00:00',
               '2026-05-23 20:00:00', '2026-05-23 21:00:00',
               '2026-05-23 22:00:00', '2026-05-23 23:00:00',
               '2026-05-24 00:00:00', '2026-05-24 01:00:00',
               '2026-05-24 02:00:00', '2026-05-24 03:00:00',
               '2026-05-24 04:00:00', '2026-05-24 05:00:00',
               '2026-05-24 06:00:00', '2026-05-24 07:00:00',
               '2026-05-24 08:00:00', '2026-05-24 09:00:00',
               '2026-05-24 10:00:00', '2026-05-24 11:00:00',
               '2026-05-24 12:00:00', '2026-05-24 13:00:00',
               '2026-05-24 14:00:00', '2026-05-24 15:00:00',
               '2026-05-24 16:00:00', '2026-05-24 17:00:00',
               '2026-05-24 18:00:00', '2026-05-24 19:00:00',
               '2026-05-24 20:00:00', '2026-05-24 21:00:00',
               '2026-05-24 22:00:00', '2026-05-24 23:00:00'],
              dtype='datetime64[ns]', name='ocean_time', freq=None))

Depth

PandasIndex

PandasIndex(Index([0.0], dtype='float64', name='Depth'))

Attributes: (50)
institution :
School for Marine Science and Technology
source :
FVCOM_4.4.7
history :
model started at: 23/05/2026 03:34
references :
http://fvcom.smast.umassd.edu, https://github.com/FVCOM-GitHub/FVCOM
CoordinateSystem :
GeoReferenced
CoordinateProjection :
init=nad83:402
Tidal_Forcing :
Tidal Forcing Time Series Title: sfbofs lateral open boundary netCDF file
River_Forcing :
THERE ARE 9 RIVERS IN THIS MODEL. RIVER INFLOW IS ON THE nodes WHERE TEMPERATURE AND SALINITY ARE calculated IN THE MODEL. THE FOLLOWING RIVER NAMES ARE USED: 11459150 11180700 11458000 11458000 11458000 11458000 11458000 11172175 11169025
GroundWater_Forcing :
GROUND WATER FORCING IS OFF!
Surface_Heat_Forcing :
FVCOM variable surface heat forcing file: FILE NAME:sfbofs.t03z.20260523.hflux.forecast.nc SOURCE:FVCOM grid (unstructured) surface forcing Unknown start date meta data format
Surface_Wind_Forcing :
FVCOM variable surface Wind forcing: FILE NAME:sfbofs.t03z.20260523.met.forecast.nc SOURCE:FVCOM grid (unstructured) surface forcing Unknown start date meta data format
Surface_PrecipEvap_Forcing :
SURFACE PRECIPITATION FORCING IS OFF
acknowledgment :
SFBOFS was jointly developed by the NOAA/National Ocean Service's (NOS) Office of Coast Survey and Center for Operational Oceanographic Products and Services (CO-OPS), and the NOAA/National Weather Service's (NWS) National Centers for Environmental Prediction (NCEP) Central Operations (NCO) and the University of Massachusetts-Dartmouth.
comment :
The model is a finite element model and has higher resolution around the coastline and islands. It is described in detail at: https://tidesandcurrents.noaa.gov/ofs/sfbofs/sfbofs_info.html
Conventions :
CF-1.6,UGRID-1.0,ACDD-1.3
coverage_content_type :
modelResult
creator_email :
nos.co-ops.commsteam@noaa.gov
creator_name :
National Ocean Service, Center for Operational Oceanographic Products and Services.
creator_url :
https://oceanservice.noaa.gov/
date_created :
2026-05-23
date_metadata_modified :
2026-05-23
date_modified :
2026-05-23
geospatial_bounds :
POLYGON ((37.41 -123.04, 38.23 -123.04, 38.23 -121.66, 37.41 -121.66, 37.41 -123.04))
geospatial_bounds_crs :
EPSG:4326
geospatial_lat_max :
38.23
geospatial_lat_min :
37.41
geospatial_lon_max :
-121.66
geospatial_lon_min :
-123.04
geospatial_vertical_max :
100.0
geospatial_vertical_min :
0.0
geospatial_vertical_positive :
down
id :
sfbofs_rgrid
keywords :
OCEANS; SALINITY/DENSITY; SALINITY, OCEANS; OCEAN TEMPERATURE; WATER TEMPERATURE; OCEAN CIRCULATION; OCEAN CURRENTS, OCEANS; BATHYMETRY/SEAFLOOR TOPOGRAPHY; WATER DEPTH;
keywords_vocabulary :
Olsen, L.M., G. Major, K. Shein, J. Scialdone, S. Ritz, T. Stevens, M. Morahan, A. Aleman, R. Vogel, S. Leicester, H. Weir, M. Meaux, S. Grebas, C.Solomon, M. Holland, T. Northcutt, R. A. Restrepo, R. Bilodeau, 2013. NASA/Global Change Master Directory (GCMD) Earth Science Keywords. Version 8.0.0.0.0
license :
Open Data. There are no restrictions on the use of this data.
metadata_link :
https://tidesandcurrents.noaa.gov/ofs/sfbofs/sfbofs_info.html
naming_authority :
gov.noaa.nos.co-ops
processing_level :
downloaded from https://opendap.co-ops.nos.noaa.gov/thredds/catalog/NOAA/SFBOFS/MODELS/catalog.html and enhanced the metadata, put together nowcast and forecast output, prioritizing nowcast over forecast when both available
project :
CeNCOOS
publisher_email :
cencoos_communications@mbari.org
publisher_name :
Central and Northern California Ocean Observing System (CeNCOOS)
publisher_url :
https://www.cencoos.org
standard_name_vocabulary :
CF-v74
summary :
The San Francisco Bay Ocean Forecast System uses the Finite Volume Coastal Ocean Model (FVCOM) to compute oceanic conditions in the San Francisco Bay. The model uses wind data from the National Weather Service and stream flow from USGS.
time_coverage_duration :
PT24H
time_coverage_end :
2026-05-23T23:00:00
time_coverage_resolution :
PT1H
time_coverage_start :
2026-05-23T00:00:00
title :
San Francisco Bay Ocean Forecast System (SFBOFS)
_xpublish_id :
sfbofs_latest