A new methodology is being devised for ensemble ocean forecasting using
distributions of the surface wind field derived from a Bayesian Hierarchical
Model (BHM). The ocean members are forced with samples from the posterior distribution of the wind during the assimilation of satellite and in-situ
ocean data. The initial condition perturbations are then consistent with the
best available knowledge of the ocean state at the beginning of the forecast
and amplify the ocean response to uncertainty only in the forcing.
The ECMWF Ensemble Prediction System (EPS) surface winds are also
used to generate a reference ocean ensemble to evaluate the performance of
the BHM method that proves to be eective in concentrating the forecast
uncertainty at the ocean meso-scale.
An height month experiment of weekly BHM ensemble forecasts was
performed in the framework of the operational Mediterranean Forecasting
System. The statistical properties of the ensemble are compared with model
errors throughout the seasonal cycle proving the existence of a strong relationship between forecast uncertainties due to atmospheric forcing and the
seasonal cycle.
| Identifer | oai:union.ndltd.org:unibo.it/oai:amsdottorato.cib.unibo.it:859 |
| Date | 30 June 2008 |
| Creators | Bonazzi, Alessandro <1979> |
| Contributors | Pinardi, Nadia |
| Publisher | Alma Mater Studiorum - Università di Bologna |
| Source Sets | Università di Bologna |
| Language | English |
| Detected Language | English |
| Type | Doctoral Thesis, PeerReviewed |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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