The SONATA project
Southern OceaN: optimal Approach To Assess the carbon state, variability and climatic drivers (SONATA)
SONATA is a project to assess the current state of the sink for atmospheric carbon dioxide in the Southern Ocean. It is a joint project of the Universities of East Anglia, Exeter and Southampton, and the British Antarctic Survey. It is funded by NERC as part of it’s initiative on the Southern Ocean: “Role of the Southern Ocean in the Earth System (RoSES: http://www.nerc.ac.uk/research/funded/programmes/roses/).
The Southern Ocean is the most exciting and extreme region of the world ocean, with the strongest winds, coldest temperatures, and most intense storms. It is believed also to be among the largest ‘sink’ for atmospheric CO2, accounting for about one third of the uptake of CO2 by the global ocean and nearly one tenth of the global emissions of CO2 on average each year. Thus the evolution of the SO carbon sink has the potential to alter the rate and extent of climate change.
In spite of its importance, we don’t know the state, variability, or climatic drivers of the carbon sink there, and there is much controversy over its recent evolution. The climate of the Southern Ocean has been changing over recent decades: in particular, winds have intensified, (attributed in part to the depletion of stratospheric ozone and in part to increasing temperature gradients arising from climate change), ocean acidification is occurring, and there is a long term decline in krill stocks. These effects take place on top of large natural variability and poorly quantified climatic trends.
SONATA will achieve a step change in our understanding of the contemporary Southern Ocean carbon sink by delivering new data and new insights, integrating observations from the ocean, from the atmosphere, and model results. We will develop three complementary streams of research, an ‘Oceanic’, an ‘Atmospheric’, and a ‘Processes and drivers’ view, and will bring them together using advanced mathematical frameworks to provide a single assessment with multiple constraints and reduction of uncertainties.