Spatiotemporal variability of air-sea CO₂ fluxes in the Northern Indian Ocean: Insights from ocean color remote sensing

Quantifying sea surface pCO ₂ (pCO₂ _sw ), atmospheric pCO ₂ (pCO _2air ), and the CO₂ flux between these two media is essential for understanding the global carbon cycle and its interactions with climate change. Satellite based quantification offers a significant advantage in monitoring oceanic CO₂ absorption by providing continuous, widespread, and high-resolution data, thereby overcoming the limitations posed by sparse in-situ measurements particularly in the North Indian Ocean (NIO). This study integrates satellite derived datasets, regression equations, and models to estimate pCO₂ fields and compute air-sea CO ₂ fluxes across the NIO region, including the Andaman Sea, Arabian Sea (AS), Lakshadweep Sea, and Bay of Bengal (BoB). Key input variables include sea surface temperature (SST), sea surface salinity (SSS), chlorophyll-a (Chla), wind speed (WS), atmospheric CO₂ concentration, and sea level pressure (SLP). A multi-parameter regression approach was used to estimate pCO₂ _sw using SST, SSS, and Chla, while pCO₂ _air was derived using atmospheric CO₂ and sea level pressure. CO ₂ flux was then calculated based on ΔpCO₂, solubility coefficients, seawater density, WS, and gas transfer velocity. The results reveal a spatially diverse pattern across the NIO. The AS and Persian Gulf act as CO ₂ sources, whereas the BoB and Andaman Sea serve as sinks. The Lakshadweep Sea exhibits dual characteristics, functioning both as a source and a sink depending on temporal and spatial factors. SST and Chla play significant roles in regulating sea surface pCO₂, while SSS has a minor but notable influence on the direction and magnitude of flux. These insights contribute to improving the accuracy of air-sea CO ₂ flux estimation, understanding regional carbon dynamics, and projecting future trends. They also provide valuable input for shaping effective climate policies and mitigation strategies.