Reconstruction of super-resolution ocean pCO2 and air–sea fluxes of CO2 from satellite imagery in the southeastern Atlantic

[摘要] An accurate quantification of the role of the ocean as source/sink ofgreenhouse gases (GHGs) requires to access the high-resolution of the GHGair–sea flux at the interface. In this paper we present a novel method toreconstruct maps of surface ocean partial pressure of CO₂ ( pCO₂) andair–sea CO₂ fluxes at super resolution (4 km, i.e.,1/32° at these latitudes) using seasurface temperature (SST) and ocean color (OC) data at this resolution, andCarbonTracker CO₂ fluxes data at low resolution (110 km). Inference ofsuper-resolutionpCO₂ and air–sea CO₂ fluxes is performed usingnovel nonlinear signal processing methodologies that prove efficient in thecontext of oceanography. The theoretical background comes from themicrocanonical multifractal formalism which unlocks the geometricaldetermination of cascading properties of physical intensive variables. As aconsequence, a multi-resolution analysis performed on the signal of theso-called singularity exponents allows for the correct and near optimalcross-scale inference of GHG fluxes, as the inference suits the geometricrealization of the cascade. We apply such a methodology to the study offshoreof the Benguela area. The inferred representation of oceanic partial pressureof CO₂ improves and enhances the description provided by CarbonTracker,capturing the small-scale variability. We examine different combinations ofocean color and sea surface temperature products in order to increase thenumber of valid points and the quality of the inferredpCO₂ field. Themethodology is validated using in situ measurements by means of statisticalerrors. We find that mean absolute and relative errors in the inferred valuesofpCO₂ with respect to in situ measurements are smaller than forCarbonTracker.

[学科分类] 地球化学与岩石