PIs: Galen McKinley, Jessica Cross, Tim DeVries, Peter Landschützer,
Goulven G. Laruelle, Nicole Lovenduski, Pedro Monteiro, Ray Najjar,
Laure Resplandy, Adrienne Sutton, Rik Wanninkhof, and Nancy Williams
Dates/Venue: May 5-6, 2020 at Lamont-Doherty Earth Observatory
Summary: A number of recent studies have applied novel statistical and machine-learning methods to in situ surface ocean carbon dioxide (CO2) observations to estimate the ocean carbon sink with unprecedented spatio-temporal resolution. These studies suggest that the oceanic CO2 sink is more variable on multiyear timescales than previously estimated from biogeochemical model simulations. This newly identified variability challenges our model-based mechanistic understanding and puts into question our projections of the future ocean carbon sink. These observation-based estimates, however, rely on extensive interpolation of limited observations, and thus their reliability is unclear, particularly in data-sparse regions and seasons. Furthermore, inconsistencies regarding the area covered by open and coastal ocean estimates hampers our ability to constrain CO2 fluxes across the full marine continuum (i.e., all tidal waters). The goal of this working group will be to assess critical uncertainties in existing observation-based products, determine how best to integrate observation-based open-ocean and coastal-ocean CO2 air–sea fluxes, and quantify uncertainties in the natural (pre-industrial) outgassing of CO2. These efforts will lead to better constraints on the contemporary ocean carbon sink and its variability. The results of this OCB Working Group will assist the global carbon community in understanding the state of the global carbon cycle so as to contribute to international efforts to address climate change.