Data Publications

SODA Project: SODA3 Ensemble Means and Standard Deviations

  • SODA Project: SODA3 Ensemble Means and Standard Deviations
  • NCAR_DS650.0
  • Carton, James A., Gennady A. Chepurin, and Ligang Chen, 2018: SODA3: A New Ocean Climate Reanalysis. J. Climate, 31, 6967-6983 (DOI: 10.1175/JCLI-D-18-0149.1), URL:
  • 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, an objective is to support 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 0.25 degree by 0.25 degree by 50 level resolution (28 kilometers at the Equator down to less than 10 kilometers 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. One of the focuses for SODA3 has been to identify, quantify, and limit sources of bias. A major source of bias is in the forward model that predicts the evolution of the flow. A major (but not the only) source of model bias, in turn, is introduced through bias in the meteorological fluxes (heat, freshwater, and momentum). To address this problem SODA3 is an 'ensemble' reanalysis, the spread of whose members provides information about sensitivity to errors in surface forcing. Many of these ensemble members are driven by fluxes that have been bias-corrected.
GCMD Sciencekeywords describing the dataset. Click on Keyword to find similar datasets