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Oceanic emissions represent a highly uncertain term in the natural atmospheric methane (CH 4 ) budget, due to the sparse sampling of dissolved CH 4  in the marine environment. Here we overcome this limitation by training machine-learning models to map the surface distribution of methane disequilibrium (∆CH 4 ). Our approach yields a global diffusive CH 4  flux of 2–6TgCH 4 yr −1  from the ocean to the atmosphere, after propagating uncertainties in ∆CH 4  and gas transfer velocity. Combined with constraints on bubble-driven ebullitive fluxes, we place total oceanic CH 4  emissions between 6–12TgCH 4 yr −1 , narrowing the range adopted by recent atmospheric budgets (5–25TgCH 4 yr −1 ) by a factor of three. The global flux is dominated by shallow near-shore environments, where CH 4  released from the seafloor can escape to the atmosphere before oxidation. In the open ocean, our models reveal a significant relationship between ∆CH 4  and primary production that is consistent with hypothesized pathways of in situ methane production during organic matter cycling.

Global ocean methane emissions dominated by shallow coastal waters