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EOF ANALYSIS Means of examining variations in beach profiles in a compact fashion Describes data variability in terms of orthogonal functions or statistical modes No direct physical or mathematical relationship necessarily exists between EOFs and actual processes
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EOF ANALYSIS Eigenfunctions found from Total variance is Importance of each ordered eigenfunction is found from Where A is the data correlation matrix normalized by the dimensions of the data, e are eigenvectors and λ’s are eigenvalues (a standard eigenvalue problem) Where C are the coefficients, I and K are dimensions of the data matrix and σ 2 is the variance squared
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EOF ANALYSIS BY WINANT ET AL From Dean and Dalrymple; original source, Winant et al, 1975, JGR.
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EXAMPLE AT DUCK, NC; SEPT/OCT, 1994 Data provided by the FRF and gridded by Nathaniel Plant
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EXAMPLE AT DUCK, NC; SEPT/OCT, 1994 Data provided by the FRF and gridded by Nathaniel Plant
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PERFORM EOF ANALYSIS ON DUCK DATA 2 nd eigenfunction 3 rd eigenfunction -110 -109.5 -110.5 10 5 0 -5 Temporal Variation in Coefficients 1 st 2 nd 3 rd λ1 ~ 99.9 % λ 2 ~ 0.08 % λ 3 ~ 0.008 %
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