This web-page presents infomation about and output
from our ocean state estimate for the California Current System. We use
a 4-dimensional variational approach.
Our assimilation procedure currently runs over 4-day cycles.
Every day, a data assimilation run is performed for the previous 4 days,
producing an estimate of the physical ocean state in
which the model initial conditions have been modified.
Several physical data sets are assimilated.
AVISO Sea Level Anomalies
and subtidally averaged NOAA tide-guage data
provide information of the sea surface height.
OSTIA Sea Surface Temperature
AQUARIUS Sea Surface Salinity
provide additional sea surface information.
Subsurface hydrography derives from several platforms:
provide subsurface information broadly throughout our domain.
In addition, glider lines in the
central and southern California
regions are supported by
Glider information off the
is supported by
. We are grateful to the agencies and
individuals who have made this data available for use in this ocean state
We note that not all data mentioned above is generally assimilated into
Some platforms (e.g., Argo) do not necessarily collect information within
our domain during every assimilation cycle.
In addition, AQUARIUS data is presently only available in delayed-time mode
and not in real-time. However, this information is useful for
reanalyses, which we run occasionally to update our historical estimates.
present snapshots of surface ocean properties as
produced by a numerical model, the Regional Ocean Modeling System
). The properties shown are (1)
sea surface height (SSH), which varies about 1/2 meter within this
domain; (2) sea surface temperature (SST), which usually shows a strong
gradient between the warm subtropical waters to the southwest and cold
subpolar waters to the north or cold upwelled waters along the coast;
(3) sea surface salinity (SSS), which shows a typical CCS value of about
33 psu (practical salinity units which is close to g/kg), with modest
variation north to south owing to a relative increase in precipitation
to the north and evaporation to the south; and (4) sea surface
chlorophyll-a concentration (SCHL, mg/m^3). Superposed on SST, SSS,
are surface velocity vectors which show the direction and relative
intensity of the instantaneous circulation. Although only surface
features are presented above, the model resolves the full 3-dimensional
structure of the ocean extending from the surface to the ocean bottom as
deep as 5000 m beneath the surface.
The California Current System (CCS)
refers to the multiple
oceanographic features of the northeast Pacific Ocean circulation off
the U.S. west coast. It includes the broad equatorward surface motion
that represents the easternmost portion of the North Pacific subtropical
gyre spanning the breadth of the ocean basin, a narrow subsurface
poleward flow (the California Undercurrent) often found between about
100 and 300 m depth along the continental slope, and occasionally a
narrow surface nearshore countercurrent, seasonally varying in intensity
and often strongest in fall. Superposed on these slowly varying motions
are intense mesoscale eddies of tens to 100 km in scale that vary
position on weekly to monthly time-scales, as well as smaller
submesoscale and smaller motions that fluctuate on still shorter
CCS Physical Model:
The ocean circulation is modeled using the Regional Ocean Modeling System
Our domain extends from midway down the Baja Peninsula to the southern tip
of Vancouver Island at 1/10 degree (roughly 10 km) resolution, with 42
terrain-following levels resolving vertical structure in ocean
properties. The model is forced at the surface by atmospheric fields
produced by the Coupled Ocean
Atmosphere Mesoscale Prediction System
is run in near-real-time by the Naval
. Oceanic fields at the
lateral boundaries are obtained from a larger,
basin-scale data assimilative model,
The model does not include freshwater forcing by rivers, and
it neglects tidal motion. Ocean model fields are stored as daily
snapshots at midnight GMT.
Despite tremendous advances in ocean circulation models
last several decades, many sources of error exist and are in fact
unavoidable when trying to accurately represent or predict the complex
evolution of the true ocean state (i.e., the full physical structure of
temperature, salinity and velocity fields). For example, the initial
ocean state from which a simulation evolves is never known with 100%
accuracy. In addition, ocean models themselves involve approximations
of the true fluid dynamics for many reasons, such as limited resolution
or imperfect representation of unresolved processes like small-scale
turbulence. Finally, forcing fields (such as wind stress or heat flux)
and conditions applied at the lateral (open) boundaries of the regional
ocean model are themselves model solutions also with their own
The solution shown on this page applies the Incremental,
Strong-Constraint 4-D Variational Assimilation (4DVar) method. This
approach finds changes to the initial ocean state during an assimilation
cycle that minimize a cost function representing the sum of squared
model-data differences and squared deviations of a background model
ocean state. This method can also expand the control-space to include
changes in the surface forcing and lateral boundary conditions, though
such changes are not included in the shown solution. This approach is
referred to as incremental as it determines increments to the background
ocean state that are assumed to be small. The phrase strong-constraint
means that errors in ocean dynamics are neglected (i.e., model dynamics
are applied as a strong constraint).
Many people are responsible for various aspects of ROMS and the overall data assimilation code. Major contributors to UCSC data assimilation projects are listed below.
Andrew M. Moore
Christopher A. Edwards
We are grateful to Dan Rudnick (UCSD/SIO) and Craig Lee (UW) for providing
access to their west coast glider data for assimilation.
James Doyle (NRL) has provided considerable assistance in our use
of the COAMPS atmospheric fields.
We are also indebted to Brian Powell (UH) and John Wilkin (Rutgers) who have written and kindly shared outstanding scripts to carry out various ROMS-related operations.
More information on the CCS model, data assimilation system and related studies in the following:
- Veneziani, M., C. A. Edwards, J. D. Doyle, and D. Foley (2009), A central California coastal ocean modeling study: 1. Forward model and the influence of realistic versus climatological forcing, J. Geophys. Res., 114, C04015, doi:10.1029/2008JC004774.
- Veneziani ,M., C. A. Edwards and A. M. Moore (2009). A central California coastal ocean modeling study: 2. Adjoint sensitivities to local and remote forcing mechanisms. J Geophys Res, 114, doi:10.1029/2008JC004775.
- Broquet G., C. A. Edwards, A. M. Moore, B. S. Powell, M. Veneziani and J. D. Doyle, (2009), Application of 4D-Variational data assimilation to the California Current System, Dyn. Atmos. Oceans, doi:10.1016/j.dynatmoce.2009.03.001.
- Broquet G., A. M. Moore, H. G. Arango, C. A. Edwards, and B. S. Powell (2009), Ocean state and surface forcing correction using the ROMS-IS4DVAR data assimilation system, Mercator Ocean Quarterly Newsletter, Mercator Ocean Quarterly Newsletter, 34, pp. 5-13.
- Broquet, G., A. M. Moore, H. G. Arango, and C.A. Edwards (2010), Corrections to ocean surface forcing in the California Current System using 4D variational data assimilation, Ocean Mod. 36, doi:10.1016/j.ocemod.2010.10.005.
- Moore, A.M., Arango, H.G., Broquet, G., Powell, B.S., Zavala-Garay, J., Weaver, A.T., in press-a. The regional ocean modeling system (ROMS) 4-dimensional variational data assimilation systems. I: System overview and formulation. Prog. Oceanogr. doi:10.1016/j.pocean.2011.05.004.
- Moore, A.M., Arango, H.G., Broquet, G., Edwards, C.A., Veneziani, M., Powell, B.S., Foley, D., Doyle, J.D., Costa, D., Robinson, P., in press b. The regional ocean modeling system (ROMS) 4-dimensional variational data assimilation systems. II: Performance and application to the California current system. Prog. Oceanogr.doi:10.1016/j.pocean.2011.05.003.
- Moore, A.M., Arango, H.G., Broquet, G., Edwards, C.A., Veneziani, M., Powell, B.S., Foley, D., Doyle, J.D., Costa, D., Robinson, P., in press-b. The regional ocean modeling system (ROMS) 4-dimensional variational data assimilation systems: III Observation impact and observation sensitivity in the California Current system. Prog. Oceanogr. doi:10.1016/j.pocean.2011.05.005.
This web-page and the near-real-time ocean state estimation system is supported by the National Oceanographic and Atmospheric Administration (NOAA) through a grant from the Central and Northern California Ocean Observing System (CeNCOOS).
We gratefully acknowledge financial support for various elements of this data assimilative system by the National Oceanographic Partnership Program (NOPP) , the Office of Naval Research (ONR), the National Oceanographic and Atmospheric Administration (NOAA) , the National Science Foundation (NSF), and the Gordon and Betty Moore Foundation .