Computational Geosciences

, Volume 16, Issue 3, pp 757–778

Global sensitivity analysis in an ocean general circulation model: a sparse spectral projection approach

  • Alen Alexanderian
  • Justin Winokur
  • Ihab Sraj
  • Ashwanth Srinivasan
  • Mohamed Iskandarani
  • William C. Thacker
  • Omar M. Knio
Original Paper

DOI: 10.1007/s10596-012-9286-2

Cite this article as:
Alexanderian, A., Winokur, J., Sraj, I. et al. Comput Geosci (2012) 16: 757. doi:10.1007/s10596-012-9286-2

Abstract

Polynomial chaos (PC) expansions are used to propagate parametric uncertainties in ocean global circulation model. The computations focus on short-time, high-resolution simulations of the Gulf of Mexico, using the hybrid coordinate ocean model, with wind stresses corresponding to hurricane Ivan. A sparse quadrature approach is used to determine the PC coefficients which provides a detailed representation of the stochastic model response. The quality of the PC representation is first examined through a systematic refinement of the number of resolution levels. The PC representation of the stochastic model response is then utilized to compute distributions of quantities of interest (QoIs) and to analyze the local and global sensitivity of these QoIs to uncertain parameters. Conclusions are finally drawn regarding limitations of local perturbations and variance-based assessment and concerning potential application of the present methodology to inverse problems and to uncertainty management.

Keywords

Ocean circulation modelParametric uncertaintySensitivity analysisPolynomial chaosSparse quadrature

Mathematics Subject Classifications (2000)

86A0565D3260-0860H35

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Alen Alexanderian
    • 1
  • Justin Winokur
    • 1
  • Ihab Sraj
    • 1
  • Ashwanth Srinivasan
    • 2
    • 3
  • Mohamed Iskandarani
    • 2
  • William C. Thacker
    • 4
    • 5
  • Omar M. Knio
    • 1
    • 6
  1. 1.Department of Mechanical EngineeringJohns Hopkins UniversityBaltimoreUSA
  2. 2.Rosenstiel School of Marine and Atmospheric ScienceUniversity of MiamiMiamiUSA
  3. 3.Center for Computational ScienceUniversity of MiamiMiamiUSA
  4. 4.Cooperative Institute for Marine and Atmospheric StudiesUniversity of MiamiMiamiUSA
  5. 5.Atlantic Oceanographic and Meteorological LaboratoryMiamiUSA
  6. 6.Department of Mechanical Engineering and Materials ScienceDuke UniversityDurhamUSA