Global Trends in Merged Ocean Colour Data and Correction of Inter-Mission Inconsistencies
The main objective of this thesis is to assess global trends over 25 years in ocean colour variables and phytoplankton bloom timings in a changing climate using merged ocean colour data. However, the significant time series inconsistencies that arise from combining ocean colour data from different missions within merged datasets must first be addressed. Although satellite mission calibration bias corrections have been performed on merged data set products, significant inconsistencies between missions remain. These inconsistencies appear as sudden steps in the time series when a satellite mission is added to or removed from the merged data set and are caused by differences in the ability of a sensor to observe certain waters. The “Temporal Gap Detection Method” temporally homogenises the observations per pixel of the time series and consequently minimises the magnitude of the inter-mission inconsistencies. The corrected data set allows the examination of long-term trends and statistics of variables derived from ocean colour data with greater accuracy. Global and local trends of the chlorophyll-a concentration, optical properties, and bloom phenology were inferred from the corrected ocean colour data set. Results show that the bloom dynamics changed substantially in the subtropical gyres and the North Atlantic Ocean. The derived trends indicate a significant increase in chlorophyll-a in the polar waters, a decrease in chlorophyll-a in some equatorial waters, and point to ocean darkening, predominantly in the polar waters, due to an increase in non-phytoplankton absorption. This dissertation contributes to a broader knowledge of global trends of ocean colour variables and their relation to a changing environment, and it is the first to use a consistently covered merged ocean colour data set.
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