Expectation-maximization analysis of spatial time series
MetadataShow full item record
Expectation maximization (EM) is used to estimate the parameters of a Gaussian Mixture Model for spatial time series data. The method is presented as an alternative and complement to Empirical Orthogonal Function (EOF) analysis. The resulting weights, associating time points with component distributions, are used to distinguish physical regimes. The method is applied to equatorial Pacific sea surface temperature data from the TAO/TRITON mooring time series. Effectively, the EM algorithm partitions the time series into El Nino, La Nina and normal conditions. The EM method leads to a clearer interpretation of the variability associated with each regime than the basic EOF analysis.
© Author(s) 2007. This work is licensed under a Creative Commons License. The definitive version was published in Nonlinear Processes in Geophysics 14 (2007): 73-77, doi: 10.5194/npg-14-73-2007
The following license files are associated with this item:
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 2.5 Generic
Showing items related by title, author, creator and subject.
Ostrovsky, L. A.; Helfrich, Karl R. (Copernicus Publications on behalf of the European Geosciences Union and the American Geophysical Union, 2011-02-14)Strongly nonlinear internal waves in a layer with arbitrary stratification are considered in the hydrostatic approximation. It is shown that "simple waves" having a variable vertical structure can emerge from a wide class ...
Magalhaes, Jorge M.; Araujo, I. B.; da Silva, Jose C. B.; Grimshaw, Roger H. J.; Davis, Kate; Pineda, Jesus (Copernicus Publications on behalf of the European Geosciences Union and the American Geophysical Union, 2011-02-03)The region of the Middle East around the Red Sea (between 32° E and 44° E longitude and 12° N and 28° N latitude) is a currently undocumented hotspot for atmospheric gravity waves (AGWs). Satellite imagery shows evidence ...
Investigating the connection between complexity of isolated trajectories and Lagrangian coherent structures Rypina, Irina I.; Scott, S. E.; Pratt, Lawrence J.; Brown, Michael G. (Copernicus Publications on behalf of the European Geosciences Union and the American Geophysical Union, 2011-12-15)It is argued that the complexity of fluid particle trajectories provides the basis for a new method, referred to as the Complexity Method (CM), for estimation of Lagrangian coherent structures in aperiodic flows that are ...