AI
REACT: Physically and Chemically Consistent Reconstruction of Marine Active Tracers
Publication: cs.AI updates on arXiv.org
Author: Wenbin Dai, Hao Zheng, Shiyu Liang, Chaofan Sun, Xueying Zhang, Hanbo Huang, Xuan Gong, Yiran Zhang, Enhui Liao
Source published: 06/10/2026, 04:00:00 UTC
Briefing created: 06/10/2026, 04:48:16 UTC
Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 06/10/2026, 04:18:23 UTC.
Briefings
REACT is a carbon-first framework for reconstructing marine pH from sparse observations, addressing the mismatch between active pH prediction and conserved carbon inventory. The system decouples transport, active correction, and chemical decoding to enforce carbonate closure. On simulation data, REACT reduced pH NRMSE by 14.7% and chemical consistency error by 24.0% compared to the best baseline. Cross-temporal evaluations show robustness against error accumulation from coarse to fine scales, while ablation studies validate individual component effectiveness.
Key points
- REACT decouples transport, active correction, and chemical decoding to enforce carbonate closure while keeping pH as the target variable.
- On simulation data, REACT reduced pH NRMSE by 14.7% and chemical consistency error by 24.0% compared to the best baseline.
Context and limitations
Results are limited to simulation data; cross-temporal evaluations and ablation studies validate component effectiveness but do not include field observations.
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