AbstractDecadal variability of carbonate chemistry variables has been studied for the open ocean using observations and models, but less is known about the variations in the coastal ocean due to observational gaps and the more complex environments. In this work, we use a Bayesian‐neural‐network approach to reconstruct surface carbonate chemistry variables for the Mid‐Atlantic Bight (MAB) and the South Atlantic Bight (SAB) along the North American East Coast from 1982 to 2015. The reconstructed monthly time series data suggest that the rate of fCO2 increase in the MAB (18 ± 1 μatm per decade) is faster than those in the SAB (14 ± 1 μatm per decade) and the open ocean (14 ± 1 μatm per decade). Correspondingly, pH decreases faster in the MAB. The observed stagnation in the aragonite saturation state, Ωarag decrease during 2005–2015 in the MAB, is attributed to the intrusion of water from southern and offshore regions with high Ωarag, which offsets the decrease expected from anthropogenic CO2 uptake. Furthermore, seasonal asymmetry in the evolution of long‐term change leads to the faster change in the amplitudes of the seasonal cycle in carbonate chemistry variables in coastal waters than those in the open ocean. In particular, the increase in the seasonal‐cycle amplitude of dissolved inorganic carbon in the MAB is 2.9 times larger than that of the open ocean. This leads to the faster increase in the season‐cycle amplitude of Ωarag and earlier occurrence of undersaturation in coastal waters as acidification continues.
