Improving Prediction Skill of Imperfect Turbulent Models Through Statistical Response and Information Theory

@article{Majda2016ImprovingPS,
  title={Improving Prediction Skill of Imperfect Turbulent Models Through Statistical Response and Information Theory},
  author={Andrew J. Majda and Di Qi},
  journal={J. Nonlinear Science},
  year={2016},
  volume={26},
  pages={233-285}
}
Turbulent dynamical systems with a large phase space and a high degree of instabilities are ubiquitous in climate science and engineering applications. Statistical uncertainty quantification (UQ) to the response to the change in forcing or uncertain initial data in such complex turbulent systems requires the use of imperfect models due to both the lack of physical understanding and the overwhelming computational demands of Monte Carlo simulation with a large dimensional phase space. Thus, the… CONTINUE READING