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Review Issue
Progress and perspective of convection and cloud parameterizations in numerical models
Acta Meteorologica Sinica 2025, 83(3): 552-565
Published: 28 June 2025
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This article reviews the advances of convection and cloud parameterizations in numerical models, with a focus on the significant contributions of Chinese scientists in this field. It begins by outlining the evolution and development of convection parameterization, including the Kuo scheme, the moist convective adjustment scheme, the widely used mass flux schemes, and the machine learning-based schemes. It details the schemes developed and revised by Chinese scientists, as well as the resulting improvements to the numerical models by these schemes. Following this, this review delves into the progress of cloud parameterization schemes and elaborates on the achievements of Chinese scientists in constructing and improving both cloud macrophysics and microphysics schemes. At the end, the review discusses the possible future avenues in the development of convection and cloud parameterizations, highlighting the pivotal role anticipated for deep learning, and suggests pathways for the advancement of hybrid models and multiscale climate modeling methods.

Review Issue
Progress and Perspective of Convection and Cloud Parameterizations in Numerical Models
Journal of Meteorological Research 2025, 39(3): 593-607
Published: 31 March 2025
Abstract Collect

This article reviews the advances of convection and cloud parameterizations in numerical models, with a focus on the significant contributions of Chinese scientists in this field. It begins by outlining the evolution and development of convection parameterization, including the Kuo scheme, the moist convective adjustment scheme, the widely used mass flux schemes, and the machine learning-based schemes. It details the schemes developed and revised by Chinese scientists, as well as the resulting improvements to the numerical models by these schemes. Following this, this review delves into the progress of cloud parameterization schemes and elaborates on the achievements of Chinese scientists in constructing and improving both cloud macrophysics and microphysics schemes. At the end, the review discusses the possible future avenues in the development of convection and cloud parameterizations, highlighting the pivotal role anticipated for deep learning, and suggests pathways for the advancement of hybrid models and multiscale climate modeling methods.

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