Relating an archive of in situ vertical chlorophyll-a profiles to concurrent remotely sensed surface data

Master Thesis


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University of Cape Town

Knowledge of the vertical distribution of phytoplankton in the upper ocean is essential for accurate estimates of primary production. Satellite remote sensing has given scientists an unprecedented view of near-surface chlorophyll distribution and other surface conditions, including sea surface temperature and wind data, from regional to global scales but little information on the dynamics below the surface. As a result estimates of global production tend to use regional profile averages but these methods oversimplify the smaller scale dynamics, particularly in coastal regions where productivity is highly variable on time scales of weeks. A pilot study by computer science honours students in 2006 showed the viability of using a Dynamic Bayesian Network (DBN) in predicting a representative profile per pixel of a satellite map based on a database of time series satellite surface data. In this study, 5813 in situ profiles were obtained from the highly dynamic upwelling region around the southwestern coastline of southern Africa. The samples were collected between 1988 and 2006 between the coast and the continental slope. The region was divided into three sub-regions according to biophysical processes: the west Coast; the west Agulhas Bank; and the east Agulhas Bank. Of the 5813 profiles, 5557 were included in the sub-regions. Two consecutive processes were then applied to the profile database. First, the profiles were clustered using a k-means clustering program which produced 16 representative clusters.

Includes bibliographical references (leaves 56-67).