Vertical mixing and interannual variability of primary production in the North Atlantic

• Main Author: Gravelle, Andrew
• Format: Thesis
• Language: English
• Published: 2016
• Subjects: North Atlantic
• Online Access: https://eprints.soton.ac.uk/404273/; https://eprints.soton.ac.uk/404273/1/AndrewGravelle_FinalVersion.pdf

It is widely held that as the ocean becomes more intensely stratified with anthropogenic-driven climate change, marine primary productivity (PP) will decline within mid-to-low latitude nutrient-limited waters, and increase within higher latitude light-limited waters. This is consistent with projections from Earth-system models, which predict a decline in global PP over the next century for ‘business-as-usual’ and high-mitigation warming scenarios. However, interannual and longer-term relationships between stratification and PP are more ambiguous in observational studies. Underlying the projected changes in PP are assumptions as to the response of phytoplankton to changes in stratification and vertical mixing at these time scales. This thesis focuses upon the identification and analysis of interannual relationships between phytoplankton biomass and vertical mixing in the North Atlantic. Satellite-derived chlorophyll (Chl) data are divided into regions of similar variability in order to assess the spatial dependence of interannual relationships with vertical mixing. A large-scale bimodal pattern represents the Chl response to the tri-pole pattern of climatic variability associated with the NAO in the North Atlantic. This Chl pattern is related to similar patterns in satellite-derived sea surface temperature (SST), wind speed, and Argo float-derived mixed layer depth (MLD) and stratification. Relationships with these proxies for vertical mixing are found to be spatially heterogeneous. However, it is general to this analysis that relationships are also spatial-scale dependent: localised variability may dominate the local-scale, but tends to cancel-out within regions of similar Chl response to reveal larger-scale relationships that dominate overall variability. Thus, while observational data tend to be noisier at the local-scale, they are consistent with Earth-system models in revealing an overall dependence of phytoplankton upon vertical mixing at larger scales. These large-scale patterns and relationships are in ...