Highlights
- Developed an MLR model using in-situ and satellite data to estimate Ocean Ωcal.
- Spatiotemporal Ωcal variability driven by physical, chemical, and biological factors.
- Showed strong agreement with low errors between satellite-derived and in-situ Ωcal.
- Emphasized a declining Ωcal trend (2012–2022), indicating accelerating ocean acidification.
Abstract
Calcite saturation (Ωcal) in global surface ocean waters is a crucial parameter for assessing marine ecosystem health. This study presents a multiparametric linear regression (MLR) model integrating satellite and in-situ observations to estimate global surface ocean Ωcal. The model was developed using in-situ measurements of sea surface temperature (SST), sea surface salinity (SSS), total alkalinity (TA), dissolved inorganic carbon (DIC) and Ωcal obtained from the National Center for Environmental Information (NCEI), combined with satellite derived chlorophyll concentrations (Chla). Model validation demonstrated strong agreement with in-situ data, indicating high accuracy of estimation. Satellite derived Ωcal estimates also showed robust correlations with in-situ measurements, confirming the MLR model reliability. Sensitivity analysis highlighted the model resilience to variations in input parameters. This study reveals significant spatiotemporal variability in Ωcal, driven by physical, chemical, and biological processes, including seasonal patterns and climate phenomena like the El Nino Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO). Analysis of interannual trends and the rate of change in Ωcal emphasize the impacts of ocean acidification, revealing a declining trend that poses challenges to marine ecosystems. The proposed approach offers a valuable tool for monitoring global ocean carbonate chemistry, providing insights into the long term impacts of environmental changes on marine health and enabling informed decision making for ecosystem management.
Shaik I., Nagamani P. V., Yadav S. & Manmode Y., 2025. Global surface ocean calcite saturation (Ωcal) estimation using satellite and in-situ observations. Journal of Marine Systems 249: 104054. doi: 10.1016/j.jmarsys.2025.104054. Article (subscription required).
