The ROMS IAS Data Assimilation and Prediction System: Quantifying Uncertainty

Abstract

The main objectives of this project were: (i) to assess the impact of observations on ocean state estimates and the ensuing forecasts; (ii) to quantify the expected errors in 4-dimensional variational (4D-Var) ocean circulation estimates: and (iii) to develop multimodel ensemble and superensemble methods for ocean models. The primary tool used in this project was the Regional Ocean Modeling System (ROMS). To address the aforementioned goals and objectives, we used a recently developed suite of tools that utilize the tangent linear , adjoint, and finite-amplitude tangent linear versions of the ROMS code. Three 4D-Var data assimilation systems have been developed for ROMS, one based on the primal formulation and two based on the dual formulation. During the project we completed the following tasks: (I) observation impact, (2) observation sensitivity, (3) Analysis and forecast error estimates based on adjoint 4D-Var, (4) Graduate student and post-doc training and mentoring, (5) a 4D-Var training workshop, and (6) preparation and publication of five manuscripts.

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Document Details

Document Type
Technical Report
Publication Date
Sep 13, 2011
Accession Number
ADA550400

Entities

People

  • Andrew M. Moore
  • Brian Powell

Organizations

  • University of California, Santa Cruz

Tags

Communities of Interest

  • Advanced Electronics

DTIC Thesaurus Topics

  • Abstracts
  • Amplitude
  • Assimilation
  • California
  • Classification
  • Mentoring
  • Observation
  • Ocean Currents
  • Oceanography
  • Oceans
  • Sensitivity
  • Students
  • Training
  • Uncertainty
  • Universities
  • Workshops

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Research Science/Academic Research