Using a Lanczos eigensolver in the computation of empirical orthogonal functions

In the framework of physical field studies, EOF analysis allows the scientist to determine the modes that govern the variability of a phenomenon. The analysis requires the resolution of a linear algebra problem. This paper focuses on this part of the EOF analysis, the computation of some singular values, and the associated vectors of the data matrix D. After recalling some fundamentals of this type of problem, the authors compare the usually employed singular value decomposition strategy with a Lanczos eigensolver technique. The latter consists of computing some eigenvalues of a small symmetric matrix. The authors demonstrate its mathematical and numerical stability and discuss its main features. A comparison of the two strategies shows the advantages of the Lanczos technique. Finally, the approach is illustrated with an example based on the study of oceanographic datasets.