Drivers of coastal sea level variability along the east and south of South Africa

Doctoral Thesis

2019

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Sea level rise and variability is of great concern in the coastal areas where a significant part of the global population is settled. Therefore, understanding regional and local long-term sea level variability as well as its trend is critical. On the other hand, quantifying how the sea level has varied on different timescales and why, is critical for understanding sea level changes, and crucial for improving future global, regional, and local projections. In this study, monthly mean sea level records of seven individual tide gauges, from the east and south coast of South Africa were used to analyse the embedded timescales of variability. These timescales were separated through the Empirical Mode Decomposition (EMD) method. This is the first time that the EMD method has been applied to southern African tide gauge records. The sensitivity of the EMD method when dealing with data gaps was tested on artificially created gaps in monthly mean synthetic altimetry sea level records, representing the seven individual tide gauges under consideration. The missing values were filled by linear interpolation, average value and linear trend value. The results suggested that whichever gap filling method is applied, the separated EMD timescales will display a distorted temporal structure of the continuous time series. As a consequence, monthly mean tide gauge sea level records were optimised by filling the gaps as best as possible using satellite altimetry data and the adjacent tide gauge records where possible, and then the oscillatory timescales of variability were separated using the EMD method with the intent to determine their physical drivers. However, identifying a single driver for each separated timescale is challenging due to our limited knowledge of how sea level is linked to the various forcing mechanisms. Therefore, the timescales of sea level variability extracted using the EMD were grouped into sub-annual and interannual timescales, and their relationship to possible driving mechanisms was investigated. The sub-annual timescale indicates how sea level responds to the mesoscale and synoptic weather systems in the annual cycle, including seasonal and annual large-scale wind and atmospheric pressure pattern changes. The interannual timescale indicates an association with the climate indices including El Niño-Southern Oscillation, Indian Ocean Dipole and Southern Annular Mode through large-scale sea surface temperature patterns and large-scale pressure and wind patterns. In addition, the results have suggested that the studied coastal sea level has an association with the Agulhas Current at both sub-annual and interannual timescale through absolute dynamic topography variations at the Agulhas Current core locations. However, due to limitations in Agulhas Current data, the study was limited to East London and Port Elizabeth and the results suggested that the Agulhas Current contribution is responsible for over 62% of the monthly sea level variability at East London. However, the results were not sufficiently consistent to suggest a firm conclusion at Port Elizabeth.
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