Analysis of Time Series Generated by Low-Order Models of Atmospheric Dynamics

• Activity Number: 505
• Type: Contributed
• Date/Time: Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): Alexander Gluhovsky*+
• Companies: Purdue University
• Keywords: time series ; dynamical systems ; subsampling

Abstract

Time series analysis plays an important role in atmospheric and climate studies. However, observed and modeled series are often prohibitively short, only one realization is typically available, and models borrowed from common time series analysis are frequently inadequate. Another way to deal with formidable difficulties posed by the governing equations of atmospheric dynamics is to approximate them with finite systems of ordinary differential equations, the so-called low-order models (LOMs). LOMs in the form of coupled classical mechanical systems known as the Volterra gyrostats (gyrostatic LOMs) proved particularly advantageous for modeling atmospheric dynamics (based on my earlier finding that the simplest one is equivalent to the celebrated Lorenz model). Gyrostatic LOMs provide a bridge between the Lorenz model and the original governing equations whose fundamental properties they