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Supermodeling: Synchronization of Alternative Dynamical Models of a Single Objective Process

  • Gregory S. DuaneEmail author
  • Wim Wiegerinck
  • Frank Selten
  • Mao-Lin Shen
  • Noel Keenlyside
Chapter

Abstract

Imperfect models of the same objective process give an improved representation of that process, from which they assimilate data, if they are also coupled to one another. Inter-model coupling, through nudging, or more strongly through averaging of dynamical tendencies, typically gives synchronization or partial synchronization of models and hence formation of consensus. Previous studies of supermodels of interest for weather and climate prediction are here reviewed. The scheme has been applied to a hierarchy of models, ranging from simple systems of ordinary differential equations, to models based on the quasigeostrophic approximation to geophysical fluid dynamics, to primitive-equation fluid dynamical models, and finally to state-of-the-art climate models. Evidence is reviewed to test the claim that, in nonlinear systems, the synchronized-model scheme surpasses the usual procedure of averaging model outputs.

Keywords

Synchronization Data assimilation Supermodel 

Notes

Acknowledgements

Parts of the research reported here were performed under ERC Grant 648982, European Commission Grant 658602, and Dept. of Energy Grant DE-SC0005238

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Gregory S. Duane
    • 1
    • 2
    Email author
  • Wim Wiegerinck
    • 3
    • 4
  • Frank Selten
    • 5
  • Mao-Lin Shen
    • 1
  • Noel Keenlyside
    • 1
  1. 1.Geophysical InstituteUniversity of BergenBergenNorway
  2. 2.Department of Atmospheric and Oceanic SciencesUniversity of ColoradoBoulderUSA
  3. 3.SNN Adaptive IntelligenceNijmegenThe Netherlands
  4. 4.Department of BiophysicsDonders Institute for Brain, Cognition and Behaviour, Radboud UniversityNijmegenThe Netherlands
  5. 5.Royal Netherlands Meteorological Institute (KNMI)De BiltThe Netherlands

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