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Ocean Science An interactive open-access journal of the European Geosciences Union
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Volume 5, issue 4
Ocean Sci., 5, 475–485, 2009
https://doi.org/10.5194/os-5-475-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
Ocean Sci., 5, 475–485, 2009
https://doi.org/10.5194/os-5-475-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.

  28 Oct 2009

28 Oct 2009

Enhancing temporal correlations in EOF expansions for the reconstruction of missing data using DINEOF

A. Alvera-Azcárate1,2, A. Barth1,2, D. Sirjacobs3, and J.-M. Beckers1 A. Alvera-Azcárate et al.
  • 1AGO-GHER, University of Liège, Allée du Six Août, 17, Sart Tilman, Liège, 4000, Belgium
  • 2National Fund for Scientific Research, FNRS-FRS, Belgium
  • 3Department of Life Sciences, University of Liège, Sart Tilman, Liège, 4000, Belgium

Abstract. DINEOF (Data Interpolating Empirical Orthogonal Functions) is an EOF-based technique for the reconstruction of missing data in geophysical fields, such as those produced by clouds in sea surface temperature satellite images. A technique to reduce spurious time variability in DINEOF reconstructions is presented. The reconstruction of these images within a long time series using DINEOF can lead to large discontinuities in the reconstruction. Filtering the temporal covariance matrix allows to reduce this spurious variability and therefore more realistic reconstructions are obtained. The approach is tested in a three years sea surface temperature data set over the Black Sea. The effect of the filter in the temporal EOFs is presented, as well as some examples of the improvement achieved with the filtering in the SST reconstruction, both compared to the DINEOF approach without filtering.

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