EOF Analysis

EOF analysis The empirical orthogonal function (EOF) analysis is a decomposition of a signal or data set in terms of orthogonal base functions which are determined from the data. It is also called principal component analysis. It is different from the spectral analysis which uses triangle functions as bas functions. IDL has math subroutines that are convenient for doing EOF analysis

EOF analysis Assume d is the data time series, its auto-covariance is C=ddT Calculate the singular value decomposition of C: C=UUT Then the columns of U are the empirical orthogonal functions (EOFs), and  gives the weight of each EOF. Y EOF1 EOF2 x

Mesh and shaded surface plots Mesh surface plots surface, z, x, y, shades=bytscl(z,top=255) Shaded surface plots shade_surf, z, x, y

Image display tv, d, x, y tvscl, d, x, y

In-class assignment VIII Data files are stored at: http://lightning.sbs.ohio-state.edu/geo820/data/ Read the netCDF file skt.mon.mean.nc for NCEP sea surface temperature (skt) data. Select 10 years of data for tropical Pacific (120E-280E, 20N-20S) and conduct the EOF analysis of the data. Plot for the first 4 modes the EOF, principal component, and the Fourier spectrum of the principal component. Try use surface plot for the EOF.