Quantifying the Amplitude, Structure and Influence of Model Error during Ocean Analysis and Forecast Cycles

Abstract

The long-term scientific goals of this research project are to: 1. Understand and quantify the sources of error in ocean models that fundamentally limit the practical predictability of the coastal ocean circulation. 2. Use information about model error to improve ocean circulation estimates obtained using weak constraint data assimilation methods. The primary objective of the proposed research is to develop a weak constraint, 4-dimensional variational (4D-Var) data assimilation capability for the Regional Ocean Modeling System (ROMS) with application to the California Current System (CCS). The CCS is of considerable socio-economic and strategic significance to the United States, and ROMS CCS is transitioning towards a real-time forecasting system in support of the U.S. west coast components of the Integrated Ocean Observing System (IOOS). This project is therefore very timely given the limiting nature of model errors on coastal ocean prediction.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2010
Accession Number
ADA542487

Entities

People

  • Andrew M. Moore
  • Chris Edwards
  • Ralph F. Milliff

Organizations

  • University of California, Santa Cruz

Tags

Communities of Interest

  • Advanced Electronics
  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Amplitude
  • Applied Mathematics
  • Assimilation
  • Boundary Layer
  • California
  • Computations
  • Information Operations
  • Mathematics
  • Ocean Currents
  • Ocean Observing Systems
  • Oceans
  • Sequences
  • Standards
  • Students
  • United States
  • Workshops

Fields of Study

  • Environmental science

Readers

  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers