Synoptic-Eddy Feedbacks and Circulation Regime Analysis

A method to incorporate synoptic eddies into the diagnosis of circulation regimes using cluster analysis is illustrated using boreal winter reanalyses of the National Centers of Environmental Prediction (hereafter observations) over the Pacific–North American region. The motivation is to include the...

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Veröffentlicht in:Monthly weather review 2010-11, Vol.138 (11), p.4026-4034
1. Verfasser: STRAUS, David M
Format: Artikel
Sprache:eng
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Zusammenfassung:A method to incorporate synoptic eddies into the diagnosis of circulation regimes using cluster analysis is illustrated using boreal winter reanalyses of the National Centers of Environmental Prediction (hereafter observations) over the Pacific–North American region. The motivation is to include the configuration of the high-frequency (periods less than 10 days) transients as well as the low-frequency (periods greater than 10 days) flow explicitly into the definition of the regimes. Principle component analysis is applied to the low-frequency 200-hPa height field, and also to the low-frequency “envelope” modulations of the rms of high-frequency meridional velocity at 200 hPa. A maximum covariance analysis of the height and envelope fields, carried out using the appropriate principal components, defines three modes as explaining most of the covariance. This defines the minimum dimensionality of the space in which to apply k-means cluster analysis to the covariance coefficients. Clusters found using this method agree with results of the previous work. Significance is assessed by comparing cluster analyses with results from synthetic datasets that have the same spectral amplitudes (but random phases) of seasonal means and, separately, intraseasonal fluctuations as do the original observed time series. This procedure ensures that the synthetic series have similar autocovariance structures to the observations. Building on earlier work, the clusters obtained are newly tested to be highly significant without the need for quasi-stationary prefiltering.
ISSN:0027-0644
1520-0493
DOI:10.1175/2010MWR3333.1