3:00 PM-5:00 PM Magpie A & B - Level B
The high degree of low-frequency variability characteristic of most geophysical systems is very important for long-time predictions. Such naturally occurring systems are usually exceedingly complex. However, highly simplified models of such systems also show a remarkable degree of low-frequency variability. Thus, while an understanding of low-frequency variability in oceanic and atmospheric flows is of crucial importance to understanding the climate of our planet, it is possible to address this issue in the context of a simple but prototypical oceanic flow---the problem of adiabatic double-gyre circulation. The short and noisy nature of the numerical simulations of even such highly simplified models necessitates the use of modern dynamical system tools and sophisticated spectral estimation procedures to enhance our understanding of these systems. Further, this is a necessary step to put forward phenomenological explanations of the variability. Good estimates of low-frequency variability in geophysical systems using the available short and noisy time series is a difficult problem. Traditional methods are mostly based on ideas of Fourier Transforms, etc., and their usage tends to be very restrictive for short and noisy time series. Therefore this very important aspect, with direct implications for long-time prediction, has not received the attention it deserves. The more recent usage of data-adaptive bases and filters, maximum-entropy methods, singular-spectrum analysis, etc., may be more suitable in this context.
Organizers: Balu T. Nadiga and Darryl D. Holm
Los Alamos National laboratory
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