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 Knio

Research output: Contribution to journalArticlepeer-review

47 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)757-778
Number of pages22
JournalComputational Geosciences
Volume16
Issue number3
DOIs
StatePublished - Jun 1 2012

Keywords

  • Ocean circulation model
  • Parametric uncertainty
  • Polynomial chaos
  • Sensitivity analysis
  • Sparse quadrature

ASJC Scopus subject areas

  • Computer Science Applications
  • Computers in Earth Sciences
  • Computational Theory and Mathematics
  • Computational Mathematics

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