||Subspace Projections of Climate Related Geodata
||Vestergaard, Jacob Schack (Informatics and Mathematical Modeling, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
||Nielsen, Allan Aasbjerg (Geodesy, Danish National Space Center, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
||Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark
||The motivation for using subspace projection on climate related data is to generate
- or confirm existing - hypotheses about changes in the global climate.
When working with high dimensional data sets, it is necessary to simplify interpretation
or reduce dimensions of the data, such that interesting features are
In this bachelor thesis a Sea Surface Height (SSH) anomaly data set from 1992-
2009 is analysed. The methods applied are Empirical Orthogonal Functions
(EOF), Maximum Autocorrelation Factor (MAF), and the Infomax variant of
Independent Component Analysis (ICA). These analyses are used to find descriptive
subspaces, where different aspects of the data set are accentuated.
There are two primary results from this exploratory data analysis. The first is
that the waters south of Greenland are rising with a higher rate than the global
average. The second is that the Kuroshio Current moves south in the buildup
phase of the 1997-1998 El Ni~no. These results are brought to attention by
interpretation of temporal MAF analysis and ICA respectively. These results
can make base of new hypotheses about the rising waters, and the behaviour of
the El Nino Southern Oscillation (ENSO).
Creation date: 2009-07-01
Update date: 2011-10-10