Abstract
Chlorophyll-a (Chl-a) underestimation by global satellite algorithms in the Southern Ocean has long been reported, reducing their accuracy, and limiting the potential for evaluating phytoplankton biomass. As a result, several regional Chl-a algorithms have been proposed. The present work aims at assessing the performance of both global and regional satellite algorithms that are currently available for the Western Antarctic Peninsula (WAP) and investigate which factors are contributing to the underestimation of Chl-a. Our study indicates that a global algorithm, on average, underestimates in-situ Chl-a by ~59%, although underestimation was only observed for waters with Chl-a > 0.5 mg m−3. In high Chl-a waters (>1 mg m−3), Chl-a underestimation rose to nearly 80%. Contrary to previous studies, no clear link was found between Chl-a underestimation and the pigment packaging effect, nor with the phytoplankton community composition and sea ice contamination. Based on multi-sensor satellite data and the most comprehensive in-situ dataset ever collected from the WAP, a new, more accurate satellite Chl-a algorithm is proposed: the OC4-SO. The OC4-SO has great potential to become an important tool not only for the ocean colour community, but also for an effective monitoring of the phytoplankton communities in a climatically sensitive region where in-situ data are scarce.
Highlights
Introduction published maps and institutional affilThe Southern Ocean, which can cover up to a third of the global ocean’s surface, is responsible for over 30% of the global carbon ocean sequestration [1] and for most of the global heat uptake [2]
The overarching aim of this work is to improve the measurement of Chl-a: log10 (Chl)-a concentrations in the Western Antarctic Peninsula using satellite remote sensing
Satellite-derived Chl-a concentrations for the Western Antarctic Peninsula were extracted from the ESA Ocean Colour–Climate Change Initiative (OC-CCI [22])
Summary
Introduction published maps and institutional affilThe Southern Ocean, which can cover up to a third of the global ocean’s surface, is responsible for over 30% of the global carbon ocean sequestration [1] and for most of the global heat uptake [2]. The use and refinement of methodologies that allow for continuous monitoring with large spatial and temporal coverage, such as ocean colour remote sensing, has become an essential approach for studying such remote and endangered marine systems. For polar regions, satellite ocean colour observations can be highly limited by low-to-non-existent light during the winter months, as well as due to high cloud cover, sea ice, inter alia [5]. This is limiting when studying the Southern Ocean, even iations
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
