Conditional Nonlinear Optimal Perturbation: A New Approach to the Stability and Sensitivity Studies in Geophysical Fluid Dynamics

Mu, M. and Duan, W. S. (2007). Conditional Nonlinear Optimal Perturbation: A New Approach to the Stability and Sensitivity Studies in Geophysical Fluid Dynamics. In: Peter Jacobs, Tim McIntyre, Matthew Cleary, David Buttsworth, David Mee, Rose Clements, Richard Morgan and Charles Lemckert, 16th Australasian Fluid Mechanics Conference (AFMC). 16th Australasian Fluid Mechanics Conference (AFMC), Gold Coast, Queensland, Australia, (225-232). 3-7 December, 2007.

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Author Mu, M.
Duan, W. S.
Title of paper Conditional Nonlinear Optimal Perturbation: A New Approach to the Stability and Sensitivity Studies in Geophysical Fluid Dynamics
Conference name 16th Australasian Fluid Mechanics Conference (AFMC)
Conference location Gold Coast, Queensland, Australia
Conference dates 3-7 December, 2007
Proceedings title 16th Australasian Fluid Mechanics Conference (AFMC)
Place of Publication Brisbane, Australia
Publisher School of Engineering, The University of Queensland
Publication Year 2007
Year available 2007
Sub-type Fully published paper
ISBN 978-1-864998-94-8
Editor Peter Jacobs
Tim McIntyre
Matthew Cleary
David Buttsworth
David Mee
Rose Clements
Richard Morgan
Charles Lemckert
Start page 225
End page 232
Total pages 8
Collection year 2007
Language eng
Abstract/Summary In the stability, sensitivity and predictability studies in geophysical fluid dynamics, linear singular vector (LSV), which is the fastest growing perturbation of the linearized model, is one of the useful tools. However, the linear approximation has strong limitations on the applicability of LSV, since it ignores the nonlinear processes, such as wave-mean flow interactions. The authors have proposed a new method called CNOPs (Conditional Nonlinear Optimal Perturbations), which generalizes LSV into the fully nonlinear category. CNOP is the initial perturbation whose nonlinear evolution attains the maximum value of the cost function, which is constructed according to the problems of interests with physical constraint conditions. In sensitivity and stability analysis of fluid motions, CNOP describes the most unstable (or most sensitive) initial modes. It can also represent the optimal precursor of certain weather or climate event, or stand for the initial error that has largest effect on the uncertainties at the prediction time. In this review paper, we introduce the concept of CNOPs first. Then we present the results on the stability, sensitivity and predictability obtained by CNOP approach, which includes: the sensitivity and stability of ocean’s thermohaline circulation; predictability of El Nino-Southern Oscillation; nonlinear stability problems of a theoretical grassland ecosystem model. It is shown that CNOPs not only reveal the effect of nonlinearity on the physical problems in which nonlinear process plays an important role, but also demonstrate significant physical characteristics that cannot be shown by LSV. For example, in Zebiak-Cane model, CNOPs, rather than LSVs, act as the initial anomaly patterns that evolve into ENSO events most probably, which shows that nonlinearity enhances the evolution of El Nino. In the theoretical Stommel’s model, a nonlinear asymmetric response of THC to the finite perturbation is revealed by using CNOP approach, which cannot be realized by LSV. Other applications of CNOP, which includes ensemble forecast and target observations, are reviewed too. Prospect and challenge in the future applications of CNOP are also discussed.
Subjects 290200 Aerospace Engineering
299900 Other Engineering and Technology
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Unknown

Document type: Conference Paper
Collection: 16th Australasian Fluid Mechanics Conference
 
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Created: Tue, 18 Dec 2007, 15:44:04 EST by Laura McTaggart on behalf of School of Engineering