Ocean reanalysis is a method of combining historical

ocean observations The following are considered ocean essential climate variables (ECVs) by the Ocean Observations Panel for Climate (OOPC) that are currently feasible with current observational systems . Ocean climate variables Atmosphere surface * Air Temper ...

with a general ocean model (typically a

computational model A computational model uses computer programs to simulate and study complex systems using an algorithmic or mechanistic approach and is widely used in a diverse range of fields spanning from physics, chemistry and biology to economics, psychology, ...

) driven by historical estimates of surface winds, heat, and freshwater, by way of a

data assimilation Data assimilation is a mathematical discipline that seeks to optimally combine theory (usually in the form of a numerical model) with observations. There may be a number of different goals sought – for example, to determine the optimal state es ...

algorithm In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing ...

to reconstruct historical changes in the state of the ocean. Historical observations are sparse and insufficient for understanding the history of the ocean and its circulation. By utilizing data assimilation techniques in combination with advanced computational models of the global ocean, researchers are able to

interpolate In the mathematical field of numerical analysis, interpolation is a type of estimation, a method of constructing (finding) new data points based on the range of a discrete set of known data points. In engineering and science, one often has a n ...

the historical observations to all points in the ocean. This process has an analog in the construction of atmospheric reanalysis and is closely related to ocean state estimation.

Current projects

A number of efforts have been initiated in recent years to apply data assimilation to estimate the physical state of the ocean, including

temperature Temperature is a physical quantity that expresses quantitatively the perceptions of hotness and coldness. Temperature is measured with a thermometer. Thermometers are calibrated in various temperature scales that historically have relied on ...

salinity Salinity () is the saltiness or amount of salt dissolved in a body of water, called saline water (see also soil salinity). It is usually measured in g/L or g/kg (grams of salt per liter/kilogram of water; the latter is dimensionless and equal ...

, currents, and

sea level Mean sea level (MSL, often shortened to sea level) is an average surface level of one or more among Earth's coastal bodies of water from which heights such as elevation may be measured. The global MSL is a type of vertical datuma standardise ...

, in recent years.Carton, J.A., and A. Santorelli, 2008: Global upper ocean heat content as viewed in nine analyses, J. Clim., 21, 6015–6035. There are three alternative state estimation approaches. The first approach is used by the ‘no-model’ analyses, for which temperature or salinity observations update a first guess provided by

climatological Climatology (from Greek , ''klima'', "place, zone"; and , ''-logia'') or climate science is the scientific study of Earth's climate, typically defined as weather conditions averaged over a period of at least 30 years. This modern field of study ...

monthly estimates. The second approach is that of the sequential data assimilation analyses, which move forward in time from a previous analysis using a numerical simulation of the evolving temperature and other variables produced by an

ocean general circulation model Ocean general circulation models (OGCMs) are a particular kind of general circulation model to describe physical and thermodynamical processes in oceans. The oceanic general circulation is defined as the horizontal space scale and time scale large ...

. The simulation provides the first guess of the state of the ocean at the next analysis time, while corrections are made to this first guess based on observations of variables such as temperature, salinity, or sea level. The third approach is 4D-Var, which in the implementation described uses the initial conditions and surface forcing as control variables to be modified in order to be consistent with the observations as well as a numerical representation of the equations of motion through iterative solution of a giant optimization problem.

Methodologies

No-model approach

ISHII and LEVITUS begin with a first guess of the climatological monthly upper-ocean temperature based on climatologies produced by the

NOAA The National Oceanic and Atmospheric Administration (abbreviated as NOAA ) is an United States scientific and regulatory agency within the United States Department of Commerce that forecasts weather, monitors oceanic and atmospheric conditio ...

National Oceanographic Data Center The National Oceanographic Data Center (NODC) was one of the national environmental data centers operated by the National Oceanic and Atmospheric Administration (NOAA) of the U.S. Department of Commerce. The main NODC facility was located in Sil ...

. The innovations are mapped onto the analysis levels. ISHII uses and alternative 3DVAR approach to do an objective mapping with a smaller decorrelation scale in midlatitudes (300 km) that elongates in the zonal direction by a factor of 3 at equatorial latitudes. LEVITUS begins similarly to ISHII, but uses the technique of Cressman and Barnes with a homogeneous scale of 555 km to objectively map the temperature innovation onto a uniform grid.

Sequential approaches

The sequential approaches can be further divided into those using Optimal Interpolation and its more sophisticated cousin the

Kalman Filter For statistics and control theory, Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, and produces estima ...

, and those using 3D-Var. Among those mentioned above, INGV and SODA use versions of Optimal Interpolation. CERFACS, GODAS, and GFDL all use 3DVar. "To date we are unaware of any attempt to use Kalman Filter for multi-decadal ocean reanalyses." The 4-Dimensional Local Ensemble Transform Kalman Filter (4D-LETKF) has been applied to the

Geophysical Fluid Dynamics Laboratory The Geophysical Fluid Dynamics Laboratory (GFDL) is a laboratory in the National Oceanic and Atmospheric Administration (NOAA) Office of Oceanic and Atmospheric Research (OAR). The current director is Dr. Venkatachalam Ramaswamy. It is one of s ...

's (GFDL) Modular Ocean Model (MOM2) for a 7-year ocean reanalysis from January 1997 – 2004.Hunt, B.R., Kostelich E.J., Szunyogh, I. Efficient Data Assimilation for Spatiotemporal Chaos: A Local Ensemble Transform Kalman Filter. arXiv:physics/0511236 v1 28 Nov 2005. Dated May 24, 2006.

Variational (4D-Var) approach

One innovative attempt by GECCO has been made to apply 4D-Var to the decadal ocean estimation problem. This approach faces daunting computational challenges, but provides some interesting benefits including satisfying some conservation laws and the construction of the ocean model adjoint.

References

External links

List of existing ocean syntheses at ICDC

SODA - Simple Oceanic Data Assimilation - Oceanographic Variables reanalysis dataset 1958-2001

Historical Ocean Subsurface Temperature Analysis with Error Estimates
{{DEFAULTSORT:Ocean Reanalysis Oceanography