Key Laboratory of Atmospheric Chemistry of China Meteorological Administration, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing, China
Yaqiang Wang
Key Laboratory of Atmospheric Chemistry of China Meteorological Administration, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing, China
China Meteorological Administration Earth System Modeling and Prediction Centre (CEMC), China Meteorological Administration, Beijing, China
Xueshun Shen
China Meteorological Administration Earth System Modeling and Prediction Centre (CEMC), China Meteorological Administration, Beijing, China
Xiaoye Zhang
Key Laboratory of Atmospheric Chemistry of China Meteorological Administration, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing, China
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Total article views: 1,868 (including HTML, PDF, and XML)
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1,327
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BibTeX: 67
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Total article views: 1,848 (including HTML, PDF, and XML)
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551
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1,848
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Total article views: 3,716 (including HTML, PDF, and XML)
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Total article views: 1,868 (including HTML, PDF, and XML)
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Total article views: 1,848 (including HTML, PDF, and XML)
Thereof 1,804 with geography defined
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to...
