Continuous Updating in a 2-Layer Primitive Equation Model of the Gulf Stream

Abstract

An updating scheme for 2-layer, finite depth, primitive equation model of the Gulf Stream region has been developed. The scheme assimilates a regularized field of sea level observations. The difference between the observation and the model solution is used to update the upper layer pressure of the model. Satellite observing systems give only information about the sea surface elevation (the upper layer pressure field of the model). Earlier studies have shown that it is important to be able to transfer this information to the lower layer in order for the model to have a realistic evolution. A statistical inference technique is used to estimate the correction to the lower layer pressure given the correction to the upper layer pressure field. In addition to updating the pressure in the two layers of the model, the velocities are undated by calculating a geostrophic correction from the changes in the pressure fields. The geostrophic correction turns out to be important for the success of the assimilation. Experiments using identical twin data as observations have been performed to determine the optimal time interval over which the observations should be assimilated into the model.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1990
Accession Number
ADA230213

Entities

People

  • D. N. Fox
  • D. W. Blake
  • Ole Martin Smedstad

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Satellites
  • Assimilation
  • Classification
  • Elevation
  • Equations
  • Gulf Stream
  • Intervals
  • Monitoring
  • Naval Warfare
  • Observation
  • Personal Information Managers
  • Sea Level
  • Security
  • Statistical Inference
  • Time Intervals

Fields of Study

  • Environmental science

Readers

  • Calculus or Mathematical Analysis
  • Fluid Dynamics.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Space