Pragmatic aspects of uncertainty propagation: A conceptual review

W. Carlisle Thacker, Mohamed Iskandarani, Rafael C. Gonçalves, Ashwanth Srinivasan, Omar M. Knio

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


When quantifying the uncertainty of the response of a computationally costly oceanographic or meteorological model stemming from the uncertainty of its inputs, practicality demands getting the most information using the fewest simulations. It is widely recognized that, by interpolating the results of a small number of simulations, results of additional simulations can be inexpensively approximated to provide a useful estimate of the variability of the response. Even so, as computing the simulations to be interpolated remains the biggest expense, the choice of these simulations deserves attention. When making this choice, two requirement should be considered: (i) the nature of the interpolation and (ii) the available information about input uncertainty. Examples comparing polynomial interpolation and Gaussian process interpolation are presented for three different views of input uncertainty.

Original languageEnglish (US)
Pages (from-to)25-36
Number of pages12
JournalOcean Modelling
StatePublished - Nov 1 2015


  • Error propagation
  • Gaussian process
  • Ocean modeling
  • Optimal interpolation
  • Polynomial chaos
  • Uncertainty quantification

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Oceanography
  • Geotechnical Engineering and Engineering Geology
  • Atmospheric Science


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