Yunpeng Shan
Assistant Research Scientist - Cloud and aerosol-cloud-climate interactions modeling
Biography
My research is dedicated to advancing the development of the Earth system digital twin, a sophisticated model that mirrors our planet’s dynamic processes. This overarching effort seeks to deepen our understanding of the impact of human activities on Earth’s climate and enhance resilience against climate change. In a more detailed examination, my research mainly focuses on improving the representation of aerosols, clouds, and their interactions within the atmospheric component of Earth system models. This pursuit unfolds in two primary dimensions, offering insights into the diverse facets of my research: gaining a deeper understanding of how clouds and aerosols influence Earth’s climate and contributing to advancements in support of renewable energy generation, specifically solar and wind energy.
Research Interests
- Cloud microphysics, aerosol-cloud-precipitation interaction, atmospheric chemistry
- Numerical model developments: Earth system digital twin, model (parameterization scheme) improvement
- Application: renewable energy, weather and air quality forecast
Education
Ph.D., Atmospheric Sciences, University of Nevada, Reno (UNR); Desert Research Institute (DRI), Reno, NV, 2018
M.S., Atmospheric Physics and Environment, Nanjing University of Information Science & Technology (NUIST), Nanjing, China, 2014
B.S., Atmospheric Science (Weather Modification), Nanjing University of Information Science & Technology (NUIST), Nanjing, China, 2011
Selected publications:
Shan Y., Y. Liu, and X. Zhou. (2025): Comparative Evaluation of the Ability of the MYNN-EDMF PBL Scheme in WRF Model to Reproduce Near Surface Wind Speed Over Different Topographical Types, J. Geophys. Res. -Atmos., https://doi.org/10.1029/2023JD040620
Shan Y., J. Fan, K. Zhang, J. Shpund, G.J. Zhang, X. Song, and X. Liu, et al. (2024): Improving aerosol radiative forcing and climate in E3SM: impacts of new cloud microphysics and improved wet removal treatments. J. Adv. Model. Earth. Syst. https://doi.org/10.1029/2023MS004059
Shan Y., X. Liu, L. Lin, Z. Ke, Z. Lu, S. Tilmes, L. Gao, and P. Yu, (2023): The role of in-cloud wet removal in simulating aerosol vertical profiles and cloud radiative forcing, J. Geophys. Res. -Atmos., https://doi.org/10.1029/2023JD038564
Shan Y., H. Shi, J. Fan, L. Lin, H. Chen, L. Gao, C. He, M. Gao, L. Miao, L. Zhang, X. Xia, H. Chen (2022): Revealing bias of cloud radiative effect in WRF simulation: bias quantification and source attribution, J. Geophys. Res. -Atmos. https://doi.org/10.1029/2021JD036319
Shan, Y., X., Liu, L., Lin, Z., Ke, Z., Lu (2021):An improved representation of in-cloud wet removal processes in a global climate model and impacts on simulated aerosol vertical profiles, J. Geophys. Res.-Atmos, 126, e2020JD034173. https://doi.org/10.1029/2020JD034173.
Shan, Y., E. M. Wilcox, L. Gao, L. Lin, D. L. Mitchell, Y. Yin, T. Zhao, L. Zhang, H. Shi and M. Gao (2020): Evaluating Errors in Gamma-Function Representations of the Raindrop Size Distribution: A Method for Determining the Optimal Parameter Set for Use in Bulk Microphysics Schemes, J. Atmos. Sci. 77 (2), 513-529.
Google Scholar: https://scholar.google.com/citations?user=O4PVjIQAAAAJ&hl=en&oi=ao