Data Sheet 1_Estimating surface pCO2 and its long-term variability in the East China Sea using machine learning with satellite data.pdf

The model maintained robust regime-level generalization (CW: R² = 0.82, RMSE = 15.64 µatm; TW: R² = 0.82, RMSE = 22.01 µatm). The 21-year climatology reveals distinct mean pCO₂ levels for CW (361.2 µatm) and TW (415.1 µatm). While CW exhibits strong summer biological drawdown, TW functions as a highly variable net CO₂ source driven by positive non-thermal anomalies (+28.09 µatm).

Over the 21-year period, the atmospheric CO₂ growth rate (+2.41 µatm yr^-1) significantly outpaced the surface pCO₂ increases in both regimes (CW: +0.66 µatm yr^-1; TW: +1.11 µatm yr^-1). This growing thermodynamic gradient overwhelmingly drives an increasingly negative flux anomaly (−0.182 mmol m^-2 d^-1 yr^-1), statistically intensifying the CW carbon sink.

Crucially, recognizing the TW as a weak net source (+0.50 Tg C yr^-1) rather than a sink reveals that conventional models overestimate ECS carbon uptake by ~46% (~4.04 Tg C yr^-1). Ultimately, this study provides a highly refined long-term carbon budget for the ECS, demonstrating that accounting for spatial heterogeneity is key to accurately assessing coastal carbon dynamics.</p>