This dataset contains a combined globally mapped estimate of the air-sea exchange of carbon dioxide (CO2) based on Surface Ocean CO2 Atlas Database (SOCAT) partial pressure of CO2 (pCO2) and calculated pCO2 from Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) biogeochemistry floats from 1982 to 2017. The pCO2 fields were created using a 2-step neural network technique. In a first step, the global ocean is divided into 16 biogeochemical provinces using a self-organizing map. In a second step, the non-linear relationship between variables known to drive the surface ocean carbon system and gridded observations from the SOCAT dataset (Bakker et al., 2016) starting in 1982 in various combinations with calculated pCO2 from biogeochemical ARGO floats starting in 2014 from the SOCCOM project (Johnson et al., 2017) is reconstructed using a feed-forward neural network within each province separately. The final product is then produced by projecting these driving variables, i.e., surface temperature, chlorophyll, mixed layer depth, and atmospheric CO2 onto oceanic pCO2 using these non-linear relationships. This results in monthly pCO2 fields at 1°x1° resolution covering the entire globe with the exception of the Arctic Ocean and few marginal seas. The air-sea CO2 flux is then computed using a standard bulk formula.