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Detecting patterns of upwelling variability in Eastern Boundary Upwelling Systems with special emphasis on the Benguela regionAbrahams, Amieroh January 2020 (has links)
Magister Scientiae (Biodiversity and Conservation Biology) / Coastal upwelling is one of the most important oceanographic processes relating to ecosystem function at local and global spatial scales. To better understand how changes in upwelling trends may occur in the face of ongoing anthropogenically induced climate change it is important to quantify historical trends in climatic factors responsible for enabling coastal upwelling. However, a paucity of conclusive knowledge relating to patterns concerning changes in upwelling across the world’s oceans over time makes such analyses difficult. In this study I aimed to quantify these patterns by first identifying when upwelling events occur using a novel method for predictingthe behaviours of coastal upwelling systems over time. By using remotely sensed SST data of differing resolutions as well as several wind variables I was able to identify and quantify upwelling signals at several distances away from the coastline of various upwelling systems. Using this novel method of determining upwelling, I then compared upwelling patterns within all Eastern Boundary Upwelling Systems (EBUS) over a period of 37 years, with the assumption that climate change was likely to have driven variable wind patterns leading to a more intense upwelling over time. Overall, upwelling patterns and wind variables did not intensify overtime. This method of identifying upwelling may allow for the development of predictive capabilities to investigate investigate investigate upwelling trends in the future.
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Coastal marine heatwaves: Understanding extreme forcesSchlegel, Robert William January 2017 (has links)
Philosophiae Doctor - PhD (Biodiversity and Conservation Biology) / Seawater temperature from regional to global scale is central to many measures of biodi-
versity and continues to aid our understanding of the evolution and ecology of biolog-
ical assemblages. Therefore, a clear understanding of the relationship between marine
biodiversity and thermal structures is critical for effective conservation planning. In the an-
thropocene, an epoch characterised by anthropogenic forcing on the climate system, future
patterns in biodiversity and ecological functioning may be estimated from projected climate
scenarios however; absent from many of these scenarios is the inclusion of extreme thermal
events, known as marine heatwaves (MHWs). There is also a conspicuous absence in knowl-
edge of the drivers for all but the most notorious of these events.
Before the drivers of MHWs along the coast of South Africa could be determined, it was first
necessary to validate the 129 in situ coastal seawater temperature time series that could be
used to this end. In doing so it was found that time series created with older (longer), lower
precision (0.5 Degrees Celsius) instruments were more useful than newer (shorter) time series produced
with high precision (0.001 Degrees Celsius) instruments. With the in situ data validated, a history of the
occurrence of MHWs along the coastline (nearshore) was created and compared against
MHWs detected by remotely sensed data (offshore). This comparison showed that the
forcing of offshore temperatures onto the nearshore was much lower than anticipated,
with the rates of co-occurrence for events between the datasets along the coast ranging
from 0.2 to 0.5. To accommodate this lack of consistency between datasets, a much larger
mesoscale area was then taken around southern Africa when attempting to determine
potential mesoscale drivers of MHWs along the coast. Using a self organising-map (SOM), it
was possible to organise the synoptic scale oceanographic and atmospheric states during
coastal MHWs into discernible groupings. It was found that the most common synoptic
oceanographic pattern during coastal MHWs was Agulhas Leakage, and the most common
atmospheric pattern was anomalously warmoverland air temperatures.With these patterns
known it is now necessary to calculate how often they occur when no MHW has been
detected. This work may then allow for the development of predictive capabilities that could help mitigate the damage caused by MHWs.
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