A novel ratio algorithm for estimation of pCO2 fields in the Northern Indian ocean region using satellite oceanographic data

Estimating pCO₂ (partial pressure of carbon dioxide) is crucial for comprehending the global carbon cycle. However, conventional methods relying on in-situ measurements face challenges due to their time-consuming and expensive nature. Remote sensing is a promising alternative, offers high-resolution spatiotemporal data across large areas. In the Northern Indian Ocean (NIO) region, governed by the monsoon system, accurate pCO₂ modelling is hindered by improper parameter selection and limited in-situ data availability. To address these challenges, we propose a novel ratio algorithm for estimating pCO₂ fields in the NIO. This approach utilizes ratios derived from in-situ measurements of Sea Surface Temperature (SST), Sea Surface Salinity (SSS), and Chlorophyll-a (Chl-a) concentration. Through analysis of trends and ratios from in-situ datasets, our algorithm establishes a robust framework for pCO₂ estimation. This ratio-based approach offers a feasible alternative for accurate pCO₂ estimation in the NIO, overcoming the limitations of traditional methods and sparse in-situ measurements.