Author

Peng Zhan

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#machine learning Preprint Oct 2026

Sensitivity Fidelity Reveals Physical Dependencies Beyond Forecast Accuracy in Deep-Learning Earth-System Models

Deep-learning models increasingly rival numerical simulation in Earth-system forecasting, yet forecast error alone cannot determine whether their learned input-output dependencies are physically consistent. Here we introduce sensitivity fidelity as an additional criterion: alongside prediction error, model responses to...

Qi Chen, Peng Zhan, Hong-Xing Cui et al. · 0 citations

Review Open access Sep 2026

The Arabian Seas: a window into future oceans —physical, biogeochemical, and ecological dynamics in unique marginal environments

ABSTRACT The Arabian Sea provide a sentinel system for understanding how global planetary boundary transgressions manifest through regional ocean processes. Their rapid warming, altered circulation, declining ventilation, deoxygenation, acidification, and ecological reorganization reveal interconnected regional manifes...

Peng Zhan, Guo-Xin Cui, Da-Quan Guo et al. · National Science Review · 0 citations

Sep 2026

High‐resolution ensemble data assimilation and forecasting of mesoscale and submesoscale circulation in the Arabian Gulf

High‐resolution ocean models are increasingly capable of resolving energetic mesoscale and submesoscale dynamics, but integrating data assimilation (DA) into such systems remains challenging. Static background error covariances can limit the effectiveness of assimilating observations, particularly in shallow and semi...

Naila F. Raboudi, S. Sanikommu, Panagiotis Vasou et al. · Quarterly Journal of the Roy... · 0 citations