What

Data Interpolating Empirical Orthogonal Functions (DINEOF) is a special innovative technique, developed for the reconstruction of missing spatial data with successful application over satellite images. Since 1950, when Lorentz introduced the geographically weighted Principal Component Analysis (PCA), mostly known as empirical orthogonal functions (EOFs), many geophysical applications benefit of its usage. Specifically, PCA is defined as an orthogonal linear transformation that maps the data to a new coordinate system such that the greatest variance by any projection of the data comes to lie on the first coordinate (called the first principal component), the second greatest variance on the second coordinate, and so on. EOFs can present different physical meanings, like coherent spatial patterns with maximum variance, modes of energy, even just convenient mathematical abstractions, depending on the nature of the problem. For an extended description of DINEOF, and recent developments, the reader is referred to Beckers and Rixen (2003), Beckers et al. (2006), Alvera-Azcarate et al. (2009,2011) and Wang et al. (2014).

DINEOF algorithm application over the Eastern Mediterranean Sea on cloudy sea surface temperature (SST) satellite data first presented during the First International Conference on Remote Sensing and Geoinformation of Environment (Nikolaidis et al.,2013). Current version extends the algorithm coverage over the Black Sea region.

Why
SST is a physical parameter commonly used in most oceanographic and meteorological applications (Giannakopoulos et al., 2004) and among others is a principal factor for relevant arithmetic model calibration, assimilation and initialization (Akylas et al., 2001; 2003; Akylas and Tombrou, 2005). For these reasons, the Environmental Fluid Mechanics Group of the Civil Engineering and Geomatics Department of Cyprus University of Technology, with the cooperation of the Oceanography Center of Cyprus and the Marine and Hydrophysical Institute of Russian Acedemy of Sciences decided to provide a free access to the relevant data to the Scientific Community.
Where
Under the Download section, there are numerous netCDF formatted and gzipped compressed files, containing hourly values. Time-steps can be identified by the file names, following the scheme Year-month-day-SST-hour. View of the contents of these files, along with the initial satellite image condition, included under the Image Gallery section. Depending on the availability of the EUMEDSAT data, both sections are updated daily with the latest seven (7) days data.
Who
The Environmental Fluid Mechanics Group at Cyprus University of Technology (CUT), Department of Civil Engineering and Geomatics was initiated at the end of 2012 in the Department of Civil Engineering and Geoinformatics, Cyprus University of Technology, by Professor Evangelos Akylas.

Selected bibliographical references

Nikolaidis A., Georgiou G., Hadjimitsis D. and E. Akylas Applying DINEOF algorithm on cloudy sea-surface temperature satellite data over the eastern Mediterranean Sea, Proc. SPIE 8795, First International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2013), 87950L, 8-10 April 2013, Paphos, Cyprus, 10.1117/12.2029085

Akylas E., Tombrou M., Lalas D. and S. Zilitinkevich, 2001: Surface fluxes under shear-free convevtion. Q.J.R.Meteorol.Soc., 127, pp. 1183-1197.

Akylas E., Tsakos Y., Tombrou M. and D. Lalas, 2003: Considerations on minimum friction velocity. Q.J.R. Meteorol. Soc., 129, pp. 1929-1943

Akylas E. and Tombrou M., 2005: Reconsidering a generalised interpolation between the Kansas type formulae and free convection forms. Boundary-Layer Met., 115, pp. 381 - 398. DOI: 10.1007/s10546-004-1426-3.

Giannakopoulos C., Good P., Law K. S., Wang K-Y, Akylas E. and Koussis A., 2004: The parameterization of rainfall in an off-line chemical transport model. Atmospheric Science Letters, 5, pp. 82 - 88.

Alvera-Azcarate, A., A. Barth, D. Sirjacobs, and J.-M. Beckers. "Enhancing Temporal Correlations in EOF Expansions for the Reconstruction of Missing Data Using DINEOF." Ocean Science Discussions 6, no. 2 (12 2009): 1547-568. doi:10.5194/osd-6-1547-2009.

Alvera-Azcarate, Aida, Charles Troupin, Alexander Barth, and Jean-Marie Beckers. "Comparison between Satellite and in Situ Sea Surface Temperature Data in the Western Mediterranean Sea." Ocean Dynamics 61, no. 6 (12 2011): 767-78. doi:10.1007/s10236-011-0403-x.

Beckers, J. M., and M. Rixen. "EOF Calculations and Data Filling from Incomplete Oceanographic Datasets*." Journal of Atmospheric and Oceanic Technology 20, no. 12 (12 2003): 1839-856. doi:10.1175/1520-0426(2003)0202.0.CO;2.

Wang, Yueqi, and Dongyan Liu. "Reconstruction of Satellite Chlorophyll-data Using a Modified DINEOF Method: A Case Study in the Bohai and Yellow Seas, China." International Journal of Remote Sensing 35, no. 1 (12, 2014): 204-17. doi:10.1080/01431161.2013.866290.