Researchers develop new methods for tracking marine carbon from space

The ocean plays a major role in cycling carbon dioxide in the atmosphere. To understand the changing climate of the Earth, it is important to determine the amount of carbon trapped in the ocean. However, measuring and monitoring large-scale marine processes poses a challenge for scientists.

Researchers and collaborators at Florida State University have developed new methods for analyzing satellite data to better predict carbon exports. The team recently published their findings in the journal Geophysical Research Letters.

“We are urgently needed tools to monitor marine carbon connections on a global scale. By leveraging diverse datasets, we have identified new paths to improve carbon export estimations from space.”

The ocean and its inhabitants are an important part of the Earth’s carbon cycle. Carbon dioxide dissolves in the ocean, and marine life converts it into organic materials and later sinks into deep seas. Together, these processes can confine or sequester carbon from the ocean-deep atmosphere, a process known as carbon export.

Direct measurements of carbon exports are rare, so scientists need to rely on models and satellite data to understand large-scale patterns of marine carbon connections. Phytoplankton, like small plants in ocean surface waters, converts carbon dioxide to organic carbon through photosynthesis. Scientists can estimate phytoplankton productivity using satellite marine color data. However, existing satellite-based models often do not capture what happens beneath the sea level.

Coastal upwelling in California’s currents, a cool, nutritious current that runs from British Columbia to Baja, California, creates a productivity boom. Ocean currents can transport phytoplankton hundreds of kilometres offshore. Marine life consumes phytoplankton and transports carbon through food webs as food and waste. Dead phytoplankton and carbon-rich waste eventually sink to the depths below, part of a biological pump that can trap carbon in the deep sea for thousands of years.

Mbari’s data integration and interdisciplinary oceanography team works to understand ocean processes by leveraging a diverse set of data from a range of disciplines, from physics to ecosystems.

The team is particularly interested in addressing the processes that drive patterns of biological communities across the water column over time. These relationships are particularly difficult to decipher because they are not necessarily direct. For example, plankton is replaced by currents, so observing at one location could be the result of past conditions several dozens of kilometers apart.

Data Integration and Interdisciplinary Oceanography teams unleash these effects, develop models that explain which processes drive biological communities, which they occur, quantify their effects, and discover which processes they discover.

Mbari deployed a series of advanced technologies at Station M, a research site off the coast of Central California, to monitor the Abyssosal seabed. This mountain of data from the long-term observation deck helped researchers understand how carbon circulates from the surface to the deep sea.

Mbari researchers and collaborators had previously observed pulses of carbon to the deep seabed that cannot be explained by existing satellite-based carbon export algorithms. These algorithms model marine physics and biogeochemistry, but do not consider both time and space delays between phytoplankton productivity at the surface and carbon exports to the deep sea.

A team of researchers and collaborators from Mesche and Mbali have sought to identify new pathways to improve carbon export estimates. The team mapped plankton inheritance and developed a Lagrangian growth suppression satellite-derived model that exports to surface ocean circulation after coastal upwelling. This model was originally designed to track biological hotspots where marine life gathers.

Instead of relying on marine color data to estimate carbon exports, this new approach incorporates offset between production and export, the role of zooplankton, and advection of plankton blooms due to ocean currents. This method was performed similarly to models that rely on long-term monitoring of ocean colours and carbon rain at deep seabeds.

The team’s success shows that exports can be fully represented from the ocean-colorless universe using plankton models and satellite-derived trucks of ocean currents. These results provide new insights into what controls carbon exports, how to represent them from the universe, and their spatial patterns in productive marine regions.

Mbari’s data integration and interdisciplinary oceanography team will leverage this new model to better understand how deep-sea carbon fluxes are connected to surface processes.

Next year, Mbari’s postdoctoral fellow joining in, Théo Picard will work with Messy to explore the unexplained, intense pulse-driven mening that was observed during Mbari’s long-term monitoring at Station M. We investigate the role of biological community composition.

“A complex web of physical and biological factors affects the marine carbon cycle. Using satellite data on wind and currents makes it promising to estimate marine carbon exports, providing a complementary perspective to models using oceans visible from space. The ocean research community hopes that it can better represent complex ocean processes from satellite data.