Bayesian Hierarchical Model Characterization of Model Error in Ocean Data Assimilation and Forecasts

Abstract

The Bayesian Hierarchical Model (BHM) methodology is exploited to identify, characterize, and model the irreducible model error in ocean data assimilation and forecast systems.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2013
Accession Number
ADA601463

Entities

People

  • Christopher K. Wikle
  • L. M. Berliner
  • Radu Herbei
  • Ralph F. Milliff

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Assimilation
  • Climate
  • Climate Change
  • Coefficients
  • Covariance
  • Dew Point
  • Ecology
  • Mathematics
  • Measurement
  • Mediterranean Sea
  • Monte Carlo Method
  • Ocean Currents
  • Oceanography
  • Oceans
  • Pacific Ocean
  • Random Variables
  • 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