Bayesian Hierarchical Models to Augment the Mediterranean Forecast System

Abstract

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.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2010
Accession Number
ADA597815

Entities

People

  • Christopher K. Wikle
  • Emanuele Di Lorenzo
  • L. M. Berliner
  • Ralph F. Milliff

Organizations

  • Northwest Research Associates

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Applied Mathematics
  • Assimilation
  • Atmospheric Sciences
  • Bayesian Networks
  • Climate Change
  • Computational Science
  • Covariance
  • Mediterranean Sea
  • Models
  • Oceanography
  • Oceans
  • Operations Research
  • Physical Oceanography
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Statistics

Fields of Study

  • Environmental science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers

Technology Areas

  • AI & ML