Wenxiang Shen
Postdoctoral Researcher
Email: wenxiang.shen@nju.edu.cn / shenwx@smail.nju.edu.cn
Office: Room B204, School of Atmospheric Sciences, Nanjing University
Education | ||
2020 - 2024 2018 - 2020 2014 - 2018 | Ph.D M.S. B.S. | Nanjing University, China Harbin Institute of Technology, China Harbin Institute of Technology, China |
Work Experience
| 2024 - present | Postdoctoral Researcher | Nanjing University, China |
Research Interests
| · | Development of artificial intelligence (AI)-based emulators for aerosol-cloud physical processes. |
| · | Integration of AI with Earth System Models (ESMs) to develop hybrid physical-AI numerical models. |
| · | Impacts of emission reductions on aerosol-cloud interactions |
Research Projects
4. 2026, 'GeoX' Interdisciplinary Project of Frontiers Science Center for Critical Earth Material Cycling, AI-empowered aerosol microphysical representation and climate warming forecast under carbon neutrality, PI.
3. 2026–2028, National Natural Science Foundation of China (NSFC) Young Scientists Fund: Improving the representation of black carbon mixing state heterogeneity with deep learning in climate models. PI.
2. 2025-2027, China Postdoctoral Science Foundation (CPSF) General Program, Deep learning-based parameterization of aerosol hygroscopicity and cloud condensation nuclei (CCN) activation, PI.
1. 2024, Fundamental Research Funds for the Central Universities, AI & AI for Science Project, PI.
Academic Services
Reviewer for Geoscientific Model Development, Atmospheric Chemistry and Physics, Journal of Geophysical Research: Atmospheres, and Remote Sensing
Publications: Co-first (#)/Corresponding (*) Author
12. Han X.(#), Shen, W.(#), Wang, M.(*), Zhu, Y.(*), Wang, Y., Liu, J., Rosenfeld, D., and Wang, H. Global expansion of the sensitive aerosol-limited marine cloud regime under emission reductions, Sci. Adv., 12, eaef9665, https://doi.org/10.1126/sciadv.aef9665, 2026. (Media coverage: https://mp.weixin.qq.com/s/766Rn1Xn-7kH4uL1Z0dKIw)
11. Shen, W.(*), Wang, M., Wang, J., Liu, Y., Dong, X., Shao, X., Yue, M., and Liu, Y. Quantifying Global Black Carbon Aging Responses to Emission Reductions Using Machine Learning-based Climate Model, Adv. Atmos. Sci., 43, 361-372, https://doi.org/10.1007/s00376-025-5041-1, 2025. (Editor's Recommendation: https://mp.weixin.qq.com/s/TU6LsqWigFVD3sk5Q2SyHA)
10. Shen, W., Wang, M.(*), and Dong, X. Enhanced Aging of Black Carbon under Recent Clean Air Actions and Future Carbon Neutrality Scenario in China, Environ. Sci. Technol., 58(31), 13697-13706, https://doi.org/10.1021/acs.est.4c02030, 2024.
9. Shen, W., Wang, M.(*), Riemer, N., Zheng, Z., Liu, Y., and Dong, X. Improving BC mixing state and CCN activity representation with machine learning in the Community Atmosphere Model Version 6 (CAM6), J. Adv. Model. Earth Syst., 16(1), e2023MS003889, https://doi.org/10.1029/2023MS003889, 2024. (Outstanding Contribution Award from the Wiley China Excellent Author Program, Media coverage: /e6/c9/c11323a648905/page.htm)
8. Shen, W., Wang, M.(*), Liu, Y., Dong, X., Zhao, D., Yue, M., Tian, P., and Ding, D. Evaluating BC aging processes in the community atmosphere model version 6 (CAM6), J. Geophys. Res. Atmos., 128(3), e2022JD037427, https://doi.org/10.1029/2022JD037427, 2023.
7. Shao, X., Liu, Y., Dong, X.(*), Wang, M.(*), Xu, R., Thornton, J. A., Jo, D. S., Yue, M., Shen, W., Shrivastava, M., Arnold, S. R., and Carslaw, K. S. A modeling study of global distribution and formation pathways of highly oxygenated organic molecules (HOMs) from monoterpenes, Atmos. Chem. Phys., 26, 6427-6448, https://doi.org/10.5194/acp-26-6427-2026, 2026.
6. Shao, X., Wang, M.(*), Dong, X.(*), Liu, Y., Arnold, S. R., Regayre, L. A., Jo, D. S., Shen, W., Wang, H., Yue, M., Wang, J., Zhang, W., and Carslaw, K. S. The effect of organic nucleation on the indirect radiative forcing with a semi-explicit chemical mechanism for highly oxygenated organic molecules (HOMs), Atmos. Chem. Phys., 26, 4439-4451, https://doi.org/10.5194/acp-26-4439-2026, 2026.
5. Shao, X., Wang, M.(*), Dong, X.(*), Liu, Y., Shen, W., Arnold, S. R., Regayre, L. A., Andreae, M. O., Pöhlker, M. L., Jo, D. S., Yue, M., and Carslaw, K. S. Global modeling of aerosol nucleation with a semi-explicit chemical mechanism for highly oxygenated organic molecules (HOMs), Atmos. Chem. Phys., 24(19), 11365-11389, https://doi.org/10.5194/acp-24-11365-2024, 2024.
4. Dong, L., Wang, M.(*), Rosenfeld, D., Zhu, Y., Wang, Y., Dong, X., Liu, Z., Wang, H., Zeng, Y., Cao, Y., Lu, X., Liu, J., and Shen, W. Effects of smoke on marine low clouds and radiation during 2020 western United States wildfires, Atmos. Res., 302, 107295, https://doi.org/10.1016/j.atmosres.2024.107295, 2024.
3. Liu, J., Shen, W., Yuan, Y.(*), and Dong, S. Optical characteristics and radiative properties of aerosols in Harbin, Heilongjiang Province during 2017, Atmosphere, 12(4), 463, https://doi.org/10.3390/atmos12040463, 2021.
2. Chen, Q., Shen, W., Yuan, Y.(*), Xie, M., and Tan, H. Inferring fine-mode and coarse-mode aerosol complex refractive indices from AERONET inversion products over China, Atmosphere, 10(3), 158, https://doi.org/10.3390/atmos10030158, 2019.
1. Chen, Q., Shen, W., Yuan, Y.(*), and Tan, H. Verification of aerosol classification methods through satellite and ground-based measurements over Harbin, Northeast China, Atmos. Res., 216, 167-175, https://doi.org/10.1016/j.atmosres.2018.09.022, 2019.