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

• Published in: Ocean science Vol. 5; no. 4; pp. 475 - 485
• Main Authors: Alvera-Azcárate, A., Barth, A., Sirjacobs, D., Beckers, J.-M.
• Format: Journal Article Web Resource
• Language: English
• Published: European Geosciences Union 01.01.2009; Copernicus Publications
• Subjects: Black Sea; Brackish; DINEOF; Earth sciences & physical geography; Filter; Missing data; Physical, chemical, mathematical & earth Sciences; Physique, chimie, mathématiques & sciences de la terre; Sciences de la terre & géographie physique; Sea surface temperature; MED, Black Sea
• ISSN: 1812-0792; 1812-0784; 1812-0792
• DOI: 10.5194/os-5-475-2009

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.