Coastal ocean carbon cycling is a complex process that is influenced by various physical and biological processes. Sporadic carbonate data challenges our understanding of carbon cycling in coastal areas. We first reviewed the assumptions and routines in developing coastal empirical models, and then built linear regression models with frequently measured seawater properties, such as temperature, salinity, and O2, to estimate the carbonate variables along the U.S. East Coast. The key features of seawater carbonate parameters are captured by the empirical models. The sub-regional differences are reflected in the coefficients of the empirical models. We also found that the effect of anthropogenic carbon dioxide increase on the DIC is limited over 10 years. This study helps to reconstruct seawater carbonate chemistry where data are limited, predict future changes in coastal carbonate chemistry, and enhance our understanding of long-term anthropogenic carbon inputs in the coastal ocean.
Carbonate Parameter Estimation and Its Application in Revealing Temporal and Spatial Variation in the South and Mid-Atlantic Bight, USA
- Author(s): Xinyu Li
- Journal of Geophysical Research: Oceans
- March 22, 2022
Citation: Li, X., Xu, Y. Y., Kirchman, D. L., & Cai, W. J. (2022). Carbonate Parameter Estimation and Its Application in Revealing Temporal and Spatial Variation in the South and Mid‐Atlantic Bight, USA. Journal of Geophysical Research: Oceans, 127(7), e2022JC018811.