Stochastic Forcing for Ocean Uncertainty Prediction

Abstract

Our research vision is to develop and transform ocean modeling and data assimilation to quantify regional ocean dynamics on multiple scales. Our group creates and utilizes new models and methods for multiscale modeling, uncertainty quantification, data assimilation and the guidance of autonomous vehicles. We then apply these advances to better understand physical, acoustical and biological interactions. We seek both fundamental and applied contributions to build knowledge and benefit naval operations. A main focus of this research is the role of stochastic forcing on ocean uncertainty and variability predictions. The work includes collaborations with NRL-Stennis to prepare the transfer of a subset of the capabilities and software developed by our Multidisciplinary Simulation, Estimation, and Assimilation Systems (MSEAS) group. The research thrusts of interest to both NRL and MIT, as well as the specific goals of the work, are below.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2012
Accession Number
ADA574631

Entities

People

  • Pierre F. J. Lermusiaux

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Computational Fluid Dynamics
  • Computational Science
  • Data Science
  • Differential Equations
  • Engineering
  • Equations
  • Flow
  • Information Science
  • Monte Carlo Method
  • Quality Control
  • Reynolds Number
  • Simulations
  • Statistical Analysis
  • Surveys
  • Uncertainty
  • Vortex Shedding

Readers

  • Distributed Systems and Data Platform Development
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers

Technology Areas

  • Autonomy
  • Autonomy - Autonomous System Control