A reanalysis of
Goal The goal of SODA is to reconstruct the historical physical (and eventually biogeochemical) history of the
ocean since the beginning of the 20th century. As its name implies, the Simple Ocean Data Assimilation ocean/sea ice
reanalysis (SODA) uses a simple architecture based on community standard
codes with resolution chosen to match available data and the scales of motion that are resolvable. Agreement with direct
measurements (to within observational error estimates) as well as unbiased statistics are expected.
While SODA remains a university-based research project, we want to be helpful to potential users by providing a reliable, well-documented, source of seasonal climate time-scale ocean reanalysis
to complement the atmospheric reanalyses available elsewhere (NOAA/EMC, NASA/GMAO, and ECMWF, for example).
SODA3 (SODA Version 3) is the latest
release of SODA. The model has been switched to GFDL MOM5/SIS1 with eddy permitting
1/4°x1/4°x50lev resolution (28km at the Equator down to <10km at
polar latitudes), similar to the ocean component of the
GFDL CM2.5 coupled climate model, and includes the same SIS1 active sea ice model. A number of improvements
have been included in the sequential DA filter, but for many reanalyses SODA3 retains a pre-specified flow-dependent error covariance. A description of SODA3
and its comparison to SODA2 is given in Carton, Chepurin, and Chen (2018a).
Error detection and Bias correction:
One of the focusses for SODA3 has been to identify and quantify error sources, and hopefully correct the systematic component of error, which we call bias. A major source of error is in the forward model that predicts the evolution of the flow.
A major (but not the only) source of model error, in turn, is meteorological forcing (heat, freshwater, and momentum). Identifying and correcting bias introduced through surface forcing is
the subject of Carton et al. (2018b). To provide information about the error in the ocean state that remains after correcting for bias SODA3 is an 'ensemble'
reanalysis, the spread of whose members reflects the uncertainty in the state. A comparison to ORAS5 and ECCO4r3 is provided in Carton et al. (2019).
15 February, 2019
SODA3 is now available through the NCAR Research Data Archive (rda.ucar.edu/datasets/ds650.0/#!description) for 1980-2016 at 5dy
resolution regridded onto the 0.5-deg Mercator grid. In addition to the ensemble mean estimates of a full set of state variables (potential temperature, currents, etc.) the data includes the ensemble
spread of the ensemble members for each variable. Meanwhile, year 2017 is available from this server for two of the current set of ensemble members: soda3.3.2 and soda3.4.2.
Carton, J.A., G.A. Chepurin, and L. Chen, 2018a: SODA3: a new ocean climate reanalysis, J. Clim., 31, 6967-6983, DOI:10.1175/JCLI-D-18-0149.1.
Carton, J.A., G.A. Chepurin, L. Chen, and S. A. Grodsky, 2018b: Improved global net surface heat flux, J. Geophys. Res.-Oceans, 123, 3144-3163, DOI:10.1002/2017JC013137.
Carton, J.A., S.G. Penny, and E. Kalnay, 2019: Temperature and salinity variability in soda3, ECCO4r3, and ORAS5 ocean reanalyses, 1993-2015, J. Clim., accepted.
For additional information or in case of problems send us email:
Gena Chepurin and
Jim Carton. If you don't get a response, we've gotten distracted. Please keep trying!
Join the SODA3 email list
SODA relies on extensive collaborations.
In addition to the National Science Foundation Physical Oceanography Program we owe debts to: NOAA/GFDL, NOAA/NCEP, NOAA/NESDIS (especially
the Laboratory for Satellite Altimetry and NCEI), NASA/GMAO, and the NASA MAP and Physical Oceanography programs. Many individuals have
contributed to SODA including: Tim Boyer, Gil Compo,
Dick Dee, Eric Hackert, Sirpa Hakkinen, Sasha Ignatov, Eugenia Kalnay, Syd Levitus, Matt Maltrud, Julie McClean, Laury Miller,
Steve Penny, R. Raghunath, James Reagan, Tony Santorelli, Mike Steele, and most notably Ben Giese, Xianhe Cao, and Hank Seidel.
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