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<p>Aerosols play a critical role in Earth’s system, significantly influencing air quality, weather, and climate dynamics. Accurately modeling their effects is essential for advancing our understanding of the climate system and improving predictive capabilities for future climate scenarios. Despite significant progress in aerosol modeling, substantial challenges persist in representing their formation, properties, and interactions with climate and weather systems. This review synthesizes recent advances in aerosol formation modeling, with particular emphasis on (1) refined nucleation and growth mechanisms, and (2) the integration of satellite observations with machine learning techniques. Furthermore, it evaluates state-of-the-art representation of aerosol-radiation and aerosol-cloud interactions in global and regional models, while systematically identifying persistent uncertainties and ongoing challenges. The study emphasizes the need for future research that integrates global <i>in-situ</i> measurements with high-resolution satellite data and cutting-edge machine learning and modeling frameworks to enhance simulations of aerosol formation and their interactions with climate and weather systems. Ultimately, these efforts will reduce uncertainties in aerosol modeling and provide more reliable climate projections.</p>

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Modeling the formation of aerosols and their interactions with weather and climate: critical review and future perspectives

  • 期刊论文

  • 发表日期：

    2025年7月30日

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  • Ying Xiong,
  • Qianqian Yang,
  • Yang Gao,
  • Ke Li,
  • Yang Yang,
  • Guangxing Lin,
  • Xiao Lu,
  • Zhili Wang,
  • Hongliang Zhang,
  • Meng Gao

摘要

Aerosols play a critical role in Earth’s system, significantly influencing air quality, weather, and climate dynamics. Accurately modeling their effects is essential for advancing our understanding of the climate system and improving predictive capabilities for future climate scenarios. Despite significant progress in aerosol modeling, substantial challenges persist in representing their formation, properties, and interactions with climate and weather systems. This review synthesizes recent advances in aerosol formation modeling, with particular emphasis on (1) refined nucleation and growth mechanisms, and (2) the integration of satellite observations with machine learning techniques. Furthermore, it evaluates state-of-the-art representation of aerosol-radiation and aerosol-cloud interactions in global and regional models, while systematically identifying persistent uncertainties and ongoing challenges. The study emphasizes the need for future research that integrates global in-situ measurements with high-resolution satellite data and cutting-edge machine learning and modeling frameworks to enhance simulations of aerosol formation and their interactions with climate and weather systems. Ultimately, these efforts will reduce uncertainties in aerosol modeling and provide more reliable climate projections.