Articles | Volume 18, issue 1
https://doi.org/10.5194/gmd-18-117-2025
https://doi.org/10.5194/gmd-18-117-2025
Development and technical paper
 | 
14 Jan 2025
Development and technical paper |  | 14 Jan 2025

AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE

Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang

Related authors

Measurement report: The influence of particle number size distribution and hygroscopicity on the microphysical properties of cloud droplets at a mountain site
Xiaojing Shen, Quan Liu, Junying Sun, Wanlin Kong, Qianli Ma, Bing Qi, Lujie Han, Yangmei Zhang, Linlin Liang, Lei Liu, Shuo Liu, Xinyao Hu, Jiayuan Lu, Aoyuan Yu, Huizheng Che, and Xiaoye Zhang
Atmos. Chem. Phys., 25, 5711–5725, https://doi.org/10.5194/acp-25-5711-2025,https://doi.org/10.5194/acp-25-5711-2025, 2025
Short summary
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025,https://doi.org/10.5194/gmd-18-1947-2025, 2025
Short summary
Size-resolved hygroscopicity and volatility properties of ambient urban aerosol particles measured by a volatility hygroscopicity tandem differential mobility analyzer system in Beijing
Aoyuan Yu, Xiaojing Shen, Qianli Ma, Jiayuan Lu, Xinyao Hu, Yangmei Zhang, Quan Liu, Linlin Liang, Lei Liu, Shuo Liu, Hongfei Tong, Huizheng Che, Xiaoye Zhang, and Junying Sun
Atmos. Chem. Phys., 25, 3389–3412, https://doi.org/10.5194/acp-25-3389-2025,https://doi.org/10.5194/acp-25-3389-2025, 2025
Short summary
Quality assessment of YUNYAO radio occultation data in the neutral atmosphere
Xiaoze Xu, Wei Han, Jincheng Wang, Zhiqiu Gao, Fenghui Li, Yan Cheng, and Naifeng Fu
Atmos. Meas. Tech., 18, 1339–1353, https://doi.org/10.5194/amt-18-1339-2025,https://doi.org/10.5194/amt-18-1339-2025, 2025
Short summary
Characterization of fog microphysics and their relationships with visibility at a mountain site in China
Quan Liu, Xiaojing Shen, Junying Sun, Yangmei Zhang, Bing Qi, Qianli Ma, Lujie Han, Honghui Xu, Xinyao Hu, Jiayuan Lu, Shuo Liu, Aoyuan Yu, Linlin Liang, Qian Gao, Hong Wang, Huizheng Che, and Xiaoye Zhang
Atmos. Chem. Phys., 25, 3253–3267, https://doi.org/10.5194/acp-25-3253-2025,https://doi.org/10.5194/acp-25-3253-2025, 2025
Short summary

Related subject area

Atmospheric sciences
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025,https://doi.org/10.5194/gmd-18-3311-2025, 2025
Short summary
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025,https://doi.org/10.5194/gmd-18-3265-2025, 2025
Short summary
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025,https://doi.org/10.5194/gmd-18-3211-2025, 2025
Short summary
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025,https://doi.org/10.5194/gmd-18-3175-2025, 2025
Short summary
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025,https://doi.org/10.5194/gmd-18-3065-2025, 2025
Short summary

Cited articles

Adachi, K., Chung, S. H., Friedrich, H., and Buseck, P. R.: Fractal parameters of individual soot particles determined using electron tomography: Implications for optical properties, J. Geophys. Res., 112, D14202, https://doi.org/10.1029/2006JD008296, 2007. 
Adachi, K., Chung, S. H., and Buseck, P. R.: Shapes of soot aerosol particles and implications for their effects on climate, J. Geophys. Res., 115, D15206, https://doi.org/10.1029/2009JD012868, 2010. 
Allen, R. J., Amiri-Farahani, A., Lamarque, J.-F., Smith, C., Shindell, D., Hassan, T., and Chung, C. E.: Observationally constrained aerosol–cloud semi-direct effects, npj Clim. Atmos. Sci., 2, 16, https://doi.org/10.1038/s41612-019-0073-9, 2019. 
Andersson, E. and Kahnert, M.: Coupling aerosol optics to the MATCH (v5.5.0) chemical transport model and the SALSA (v1) aerosol microphysics module, Geosci. Model Dev., 9, 1803–1826, https://doi.org/10.5194/gmd-9-1803-2016, 2016. 
Barnard, J. C., Fast, J. D., Paredes-Miranda, G., Arnott, W. P., and Laskin, A.: Technical Note: Evaluation of the WRF-Chem “Aerosol Chemical to Aerosol Optical Properties” Module using data from the MILAGRO campaign, Atmos. Chem. Phys., 10, 7325–7340, https://doi.org/10.5194/acp-10-7325-2010, 2010. 
Download
Short summary
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.
Share