Bayesian Hierarchical Models to Augment the Mediterranean Forecast System
Abstract
The overall project goal has been to test the feasibility and practicality of Bayesian Hierarchical Model (BHM) methods in aspects of the Mediterranean Forecast System (MFS); an operational ocean data assimilation and forecast system. Three main objectives have been pursued in support of the project goal. They are: 1. a surface wind BHM (MFS-Wind-BHM) to drive ensemble ocean data assimilation and forecasts in MFS;LONG-TERM GOALS The overall project goal has been to test the feasibility and practicality of Bayesian Hierarchical Model (BHM) methods in aspects of the Mediterranean Forecast System (MFS); an operational ocean data assimilation and forecast system. Three main objectives have been pursued in support of the project goal. They are: 1. a surface wind BHM (MFS-Wind-BHM) to drive ensemble ocean data assimilation and forecasts in MFS; 2. a time- and depth-dependent background error covariance BHM (MFS-Error-BHM) to evolve the background error covariance matrix in 13 sub-regions of the MFS forecast domain; and 3. a BHM to demonstrate super-ensemble forecast capabilities (MFS-SuperEnsemble-BHM) for ocean applications.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 2010
- Accession Number
- ADA542751
Entities
People
- Christopher K. Wikle
- Emanuele Di Lorenzo
- L. M. Berliner
- Ralph F. Milliff