Oceanic stochastic parameterizations in a seasonal forecast system

M. Andrejczuk, F. C. Cooper, S. Juricke, T. N. Palmer, A. Weisheimer, Laure Zanna

Research output: Contribution to journalArticlepeer-review


Stochastic parameterization provides a methodology for representing model uncertainty in ensemble forecasts. Here the impact on forecast reliability over seasonal time scales of three existing stochastic parameterizations in the ocean component of a coupled model is studied. The relative impacts of these schemes upon the ocean mean state and ensemble spread are analyzed. The oceanic variability induced by the atmospheric forcing of the coupled system is, in most regions, the major source of ensemble spread. The largest impact on spread and bias came from the stochastically perturbed parameterization tendency (SPPT) scheme, which has proven particularly effective in the atmosphere. The key regions affected are eddy-active regions, namely, the western boundary currents and the Southern Ocean where ensemble spread is increased. However, unlike its impact in the atmosphere, SPPT in the ocean did not result in a significant decrease in forecast error on seasonal time scales. While there are good grounds for implementing stochastic schemes in ocean models, the results suggest that they will have to be more sophisticated. Some suggestions for next-generation stochastic schemes are made.

Original languageEnglish (US)
Pages (from-to)1867-1875
Number of pages9
JournalMonthly Weather Review
Issue number5
StatePublished - May 1 2016


  • Coupled models
  • Forecasting
  • Model errors
  • Models and modeling
  • Parameterization
  • Seasonal forecasting
  • Stochastic models
  • Subgrid-scale processes

ASJC Scopus subject areas

  • Atmospheric Science


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