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Ocean Surface Topography from Space
SCIENCE
Oceanic Climate Change and Sea Level: Causality and Forecasting with Multivariate Singular Spectrum Analysis


Author:

Salem Kahlouche - (Algerian Space Agency, Division of Space Geodesy, Centre of Space Techniques)

Co-Investigator(s):
  Hossein Hassani
Mohamed Faouzi Belbachir
Mohammed Arezki Si Mohammed
Mahdi Haddad
Habib Taibi
(Bournemouth University)
(University of Sciences and Technology of Oran - Mohamed Boudiaf)
(Division of Space Mechanics, Centre of Space Techniques)
(Division of Space Geodesy, Centre of Space Techniques)
(Division of Space Geodesy, Centre of Space Techniques)

Abstract:
Oceanic Climate Change and Sea Level: Causality and Forecasting with Multivariate Singular Spectrum Analysis
Merged MSLA rms (in cm) in the Mediterranean Sea over all the period 1993-2009.

The global mean level of the oceans is one of the most important indicators of climate change. It incorporates the reactions from several different components of the climate system. Precise monitoring of changes in the mean level of the oceans, particularly through the use of altimetry satellites, is vitally important, for understanding not just the climate but also the socioeconomic consequences of any rise in sea level.

Long term sea level variations are primarily determined with two different methods. Over the last century, global sea level change has typically been estimated from tide gauge measurements by long-term averaging. Alternatively, satellite altimeter measurements can be combined with precisely known spacecraft orbits to provide an improved measurement of global sea level change.

In this project we aim to overcome many of these difficulties by implementing a different technique for capturing causality between sea level variability from altimetry data and climatic indices (sea surface temperature, concentration in CO2 in the atmosphere, precipitation,...) using multivariate singular spectrum analysis (SSA).



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