Journal article
Oceanic stochastic parametrizations in a seasonal forecast system
- Abstract:
- Stochastic parametrization provides a methodology for representing model uncertainty in ensemble forecasts. Here we study the impact of three existing stochastic parametrizations in the ocean component of a coupled model, on forecast reliability over seasonal timescales. 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 Parametrization 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. Whilst there are good grounds for implementing stochastic schemes in ocean models, our results suggest that they will have to be more sophisticated. Some suggestions for next-generation stochastic schemes are made.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.6MB, Terms of use)
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- Publisher copy:
- 10.1175/MWR-D-15-0245.1
Authors
+ European Commission
More from this funder
- Funding agency for:
- Weisheimer, A
- Grant:
- European Commission Seventh Framework Research Programme: SPECS 308378
- Publisher:
- American Meteorological Society
- Journal:
- Monthly Weather Review More from this journal
- Volume:
- 144
- Issue:
- 5
- Pages:
- 1867-1875
- Publication date:
- 2016-04-19
- DOI:
- EISSN:
-
1520-0493
- ISSN:
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0027-0644
- Pubs id:
-
pubs:599071
- UUID:
-
uuid:6d159eef-a26a-47c3-95c6-bd4c2c5c954a
- Local pid:
-
pubs:599071
- Source identifiers:
-
599071
- Deposit date:
-
2016-02-04
Terms of use
- Copyright holder:
- American Meteorological Society
- Copyright date:
- 2016
- Notes:
- © 2016 American Meteorological Society. This article is licensed under a Creative Commons Attribution 4.0 license.
- Licence:
- CC Attribution (CC BY)
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