Bayesian Hierarchical Models to Augment the Mediterranean Forecast System Consolidating Results and Quantifying Impacts
Abstract
The long term goal of this interdisciplinary research program continues to be the demonstration of Bayesian Hierarchical Model (BHM) utility in several aspects of operational ocean forecasting. The specific goals in the current phase of the research are: 1) publications of results from ensemble ocean forecast experiments driven by the surface vector wind (SVW) BHM; b) consolidating impacts results in MFS reforecast experiments for the time-dependent error-covariance BHM; and c) running the first multi-model and multi-parameter super-ensemble BHM experiments. Research objectives leading to the publication of manuscripts regarding SVW-BHM include: 1) constructing 3 appendices for Milliff et al (2009) to: a) demonstrate a systematic approach to (future) process model development; b) document, in probability model notation, the complete SVW-BHM, as well as expressions for the full conditional distributions; and c) document the SVW-BHM hyperprior specifications; 2) Re-writing the text and updating figures for Bonazzi et al. (2009); and 3) incorporating co-author final edits for Milliff et al. (2009) and Bonazzi et al. (2009). Research objectives leading to consolidation of results for the time-dependent error-covariance BHM include: 1) supplying an anomaly-only data stage version of the error-covariance BHM to MFS for reforecast experiments; and 2) interpreting reforecast results, and iterating with MFS for future reforecast experimental design.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 2009
- Accession Number
- ADA603034
Entities
People
- Christopher K. Wikle
- Emanuele Di Lorenzo
- L. M. Berliner
- Ralph F. Milliff
Organizations
- Ohio State University