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arXiv · 2605.25436

Lagged sea-surface-temperature precursors of the leading PM2.5 mode in China

Yuan Chen·Dan Zhao·Xu Li
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Abstract

Fine particulate matter(PM2.5) pollution in China is strongly modulated bymeteorological variability, yet its seasonal predictability from oceanic signals remains unclear. Here we identify the leading PM2.5 variability mode over China and show that it is preceded by coherent sea-surface-temperature anomaly clusters by more than one season. These oceanic precursors influence summer PM2.5 mainly by altering precipitation and lowlevel ventilation, and winter PM2.5 by modulating boundary-layer height and near-surface stagnation. Using the four largest precursor regions, a simple regression model achieves significant independent prediction skill for both summer and winter PM2.5 variability. Our results reveal a physical pathway linking sea-surface-temperature memory to regional aerosol pollution and provide a basis for seasonal air-quality risk assessment.

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Yuan Chen, Dan Zhao, Xu Li. 2026-05-25. Lagged sea-surface-temperature precursors of the leading PM2.5 mode in China. https://arxiv.org/abs/2605.25436

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