Improving estimates of ocean productivity and carbon sequestration through a combination of autonomous observation- and model-based approaches

The ocean is rapidly warming and becoming more stratified, which inhibits the vertical exchange of dissolved nutrients essential for maintaining photosynthetic primary production at the sea surface. Primary production supports the marine food web and plays a major role in regulating Earth's climate as a pathway for sequestering CO2 in the ocean's interior. Accurate quantification of ocean primary production and carbon sequestration, and their response to a warming climate are urgent scientific challenges but are hindered by the relative sparsity of biogeochemical observations. Measurements from research ships, while allowing for the broadest suite of direct measurements, are limited to a few point measurements due to the cost and effort required. Satellites can provide synoptic global coverage at high spatial resolution, but the only biogeochemical property observed is surface chlorophyll. The resulting gaps are hampering our ability to fully recognize changes in ocean biogeochemistry, to understand the underlying processes, and to test and improve models. The recent maturation of autonomous platforms and miniaturized biogeochemical sensors provides an opportunity to overcome the long-standing biogeochemical undersampling of the ocean, enabling us to observe changes by complementing traditional means of observation via satellites and ships. Autonomous platforms allow collection of highly resolved, unbiased, and sustained measurements of many essential biogeochemical ocean properties on the global scale in 3-dimensional space and in a cost-effective manner. Taking advantage of rapidly expanding autonomous ocean observation networks, in particular the biogeochemical (BGC) Argo program, the objectives of this research program are to 1) develop and apply new approaches for estimating ocean productivity and carbon export from autonomous observations, 2) rigorously test and refine ocean biogeochemical models using the newly emerging data to improve model capabilities, and 3) develop and apply statistical methods for blending autonomous biogeochemical observations and models to obtain the best possible estimates of the changing ocean state. A successful demonstration of the proposed approaches for estimating ocean productivity and carbon export will fundamentally transform international efforts to observe these processes, will strengthen the case for a sustained inclusion of autonomous platforms with BGC sensors in the global ocean observing system, and will lay the groundwork for enabling detection of climate-induced changes in the coming decades. A rigorous and systematic assessment of biogeochemical models will reduce uncertainties in global climate projections. Provision of well-constrained data-assimilative model products will directly benefit a variety of stakeholders in the northwest North Atlantic region. All of these outcomes are invaluable for sound mitigation of climate change impacts and effective steps toward net-zero carbon.