Dissolved inorganic Carbon (DIC) acts as an important sink of atmospheric CO2 in the form of carbonates and bicarbonates in the ocean. The estimation of dissolved inorganic carbon (DIC) in global surface ocean waters is crucial for better understanding of air-sea CO2 flux rates, ocean acidification and climate change.

This study addresses the challenge of estimating Dissolved Inorganic Carbon (DIC) in ocean surface waters. It highlights the limitations of in-situ data due to dynamic variations and regional applicability of ocean color remote sensing. To overcome this, the study proposes an empirical regression approach using sea surface temperature (SST), sea surface salinity (SSS), and chlorophyll-a concentration (Chla) as predictors, based on data collected from major oceans. Multiple regression equations were developed and validated, showing accurate global DIC estimates. The approach offers high-resolution, cost-effective DIC estimates and reveals seasonal and inter-annual variations. This Multi-Parametric Regression (MPR) approach is more robust and provides continuous, accurate coverage of DIC fields, enhancing monitoring of ocean acidification and climate change.

Fig. Inter-annual variability of surface ocean DIC fields for the period 2012–2021

Fig. Rate of change of DIC fields for the period 2012–2021