Inhomogeneous and Nonstationary Feature Analysis: Melding of Oceanic Variability and Structure (INFAMOVS)

Abstract

LONG-TERM GOALS. One of the primary research goals at RSMAS is real-time forecasting of both Eulerian fields, such as temperature and velocity, and Lagrangian trajectories. The five primary components are (i) MICOM, the Miami Isopycnal Coordinate Ocean Model, (ii) satellite-derived sea surface temperature and height fields and data from Lagrangian drifters, (iii) an Extended Kalman Filter (EKF) with a second-order Gauss-Markov Random Field (GMRF) model for spatial covariances, (iv) a random flight turbulence model for Lagrangian trajectory prediction, and (v) contour-based parameter estimation and assimilation techniques. OBJECTIVES. Documenting, understanding, and predicting ocean variability through the use of new data analysis and assimilation techniques. APPROACH. Our data analysis and assimilation approaches are based on motion-compensated space-time interpolation algorithms, state space reduction techniques, hodography, and multi-scale field decomposition.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 1997
Accession Number
ADA634987

Entities

People

  • Arthur J. Mariano
  • Toshio M. Chin

Organizations

  • University of Miami

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Assimilation
  • Computational Fluid Dynamics
  • Data Analysis
  • Data Sets
  • Filters
  • Flow
  • Fluid Flow
  • Gulf Stream
  • Kalman Filters
  • Ocean Currents
  • Oceanography
  • Oceans
  • Physical Oceanography
  • Sea Surface Temperature
  • Surface Temperature
  • Trajectories

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

  • Space