The Surface Ocean CO₂ Mapping (SOCOM) program
SOCOM is a community-driven initiative that benchmarks the statistical and machine-learning methods used to reconstruct global surface ocean CO₂ fugacity (sfCO₂) and estimate air–sea CO₂ fluxes (FCO₂). Building on its first phase, SOCOMv2 evaluates how well these methods perform under sparse observational sampling and how their biases propagate into FCO₂ and estimates of the global ocean carbon sink.
The ocean plays a central role in the global carbon cycle, taking up about 30% of anthropogenic CO₂ emissions and helping to regulate Earth's climate. Quantifying this ocean carbon sink requires robust global estimates of the air–sea CO₂ flux (FCO₂), the net exchange of CO₂ between the atmosphere and the ocean.
FCO₂ is estimated from measurements of surface ocean CO₂ fugacity (sfCO₂), compiled in the Surface Ocean CO₂ Atlas (SOCAT). Because these measurements do not cover the whole ocean, statistical and machine-learning sfCO₂ reconstruction methods fill the gaps using variables that influence sfCO₂ and are available everywhere, such as temperature, salinity, and chlorophyll-a. The resulting sfCO₂ reconstructions are then used to estimate FCO₂, yielding flux data products.
A major challenge is the sparse and uneven distribution of sfCO₂ observations. Since 1990, SOCAT covers only about 2% of the global ocean grid cells at 1° resolution, with particularly large gaps in the wintertime Southern Ocean and the North Pacific. These gaps limit the skill of sfCO₂ reconstruction methods.
The Global Carbon Budget (GCB) estimates the ocean carbon sink using two complementary approaches: flux data products and global ocean biogeochemical models (GOBMs). It reports persistent discrepancies between the two, particularly in their mean state, spatial patterns, and long-term trends. A key question is to what extent biases in sfCO₂ reconstructions under present-day sampling contribute to these discrepancies.
Initiated in 2013, the Surface Ocean CO₂ Mapping program (SOCOM) brings together the international community developing sfCO₂ reconstruction methods. Its first phase compared 14 sfCO₂ reconstruction methods, focusing on their estimates of the interannual variability of the ocean carbon sink (Rödenbeck et al., 2015).
To address the role of reconstruction biases, SOCOM launched its second phase (SOCOMv2) in 2023. Through coordinated experiments, SOCOMv2 evaluates sfCO₂ reconstruction methods under present-day observational sampling and assesses how their biases propagate into FCO₂, supporting more robust estimates of the global ocean carbon sink.
The ocean takes up about 30% of anthropogenic CO₂ emissions, helping to regulate Earth’s climate.
Since 1990, SOCAT covers only about 2% of the global ocean grid cells at 1° resolution. sfCO₂ reconstruction methods are needed to fill these gaps.
The GCB reports persistent discrepancies between flux data products and GOBMs in the ocean carbon sink.
Through coordinated experiments, SOCOMv2 assesses how biases in sfCO₂ reconstruction methods propagate into FCO₂ and estimates of the ocean carbon sink.
SOCOMv2 — coordinated experiments