Personal Information


Discipline:Atmospheric Sciences

Education Background

B.S., Nanjing University of Information Science & Technology, Nanjing, China. Major: Atmospheric Science, 2006 – 2010.
Ph.D., Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China. Major: Meteorology. 2010 – 2015.
Visiting student, Atmospheric Science & Global Change Division, Pacific Northwest National Laboratory (PNNL), Richland, WA, USA, 2012 – 2013.
Visiting student, Department of Atmospheric Science, University of Wyoming, Laramie, Wyoming, USA, 2013 – 2014.

Work Experience

2015-2018 Department of Earth System Science, Tsinghua University, Postdoctor
2018-2021.7 Assistant Professor,Tsinghua University
2021.7- Associate Professor, Department of Earth System Science Tsinghua University

3: 2021年度“谢义炳青年气象科技奖”

4: 第十届“清华大学-浪潮集团计算地球科学青年人才奖”


1. Yong Wang, Wenwen Xia, Xiaohong Liu, Shaocheng Xie, Wuyin Lin, Qi Tang, Hsi-Yen Ma, Yiquan Jiang, Bin Wang, Guang J. Zhang*, Disproportionate control on aerosol burden by light rain, Nature Geoscience, 14, 72-76, (2021).

2. Wei, L., Lu, Z., Wang, Y.*, Xiaohong Liu*, Weiyi Wang, Chenglai Wu, Xi Zhao, Stefan Rahimi, Wenwen Xia, and Yiquan Jiang, Black carbon-climate interactions regulate dust burdens over India revealed during COVID-19. Nature Communications, 13, 1839, (2022).

3. Shu Liu, Yong Wang*, Guang J. Zhang, Linyi Wei, Bin Wang, Le Yu, Contrasting Influences of Biogeophysical and Biogeochemical Impacts of Historical Land Use on Global Economic Inequality, Nature Communications, (2022).


40. Wei, L., Wang, Y.*, Liu, S., Zhang, G. J., & Wang, B. (2021). Distinct roles of land cover in regulating spatial variabilities of temperature responses to radiative effects of aerosols and clouds. Environmental Research Letters.

39. Xia, W., Wang, Y.*, Chen, S.*, … (2021). Double trouble of air pollution by anthropogenic dust. Environmental Science & Technology.

38. Wang, Y., Xia, W., Liu, X., Xie, S., Lin, W., Tang, Q., ... & Zhang, G. J. (2021). Disproportionate control on aerosol burden by light rain. Nature Geoscience, 1-5.

37. Wang, Y.*, Xia, W., & Zhang, G. J. (2021). What rainfall rates are most important to wet removal of different aerosol types?. Atmospheric Chemistry and Physics, 1-33.

36. Sun, W., Wang, B., Wang, Y.*, Zhang, G. J., Han, Y., Wang, X., & Yang, M. (2021). Parameterizing Subgrid Variations of Land Surface Heat Fluxes to the Atmosphere Improves Boreal Summer Land Precipitation Simulation with the NCAR CESM1. 2. Geophysical Research Letters, e2020GL090715.

35. Liu, S., Liu, X., Yu, L., Wang, Y.*, Zhang, G. J., Gong, P., Huang, W., Wang, B., Yang, M., & Cheng, Y. (2021). Climate response to introduction of the ESA CCI land cover data to the NCAR CESM. Climate Dynamics.

34. Cui, Z., Zhang, G. J., Wang, Y., & Xie, S. (2021). Understanding the Roles of Convective Trigger Functions in the Diurnal Cycle of Precipitation in the NCAR CAM5. Journal of Climate, 34(15), 6473-6489.

33. Wang, Y., Zhang, G. J., Xie, S., Lin, W., Craig, G. C., Tang, Q., & Ma, H. Y. (2021). Effects of coupling a stochastic convective parameterization with the Zhang–McFarlane scheme on precipitation simulation in the DOE E3SMv1.0 atmosphere model. Geoscientific Model Development, 14(3), 1575-1593.

32. Chen, S., Bi, H., Zhang, R., Wang, Y., Guo, J., Zhao, D., ... & Xie, Z. (2021). Impact of dust-cloud-radiation interactions on surface albedo: a case study of" Tiramisu" snow in Urumqi, China. Environmental Research Letters.

31. Li, F., Wang, B., He, Y., Huang, W., Xu, S., Liu, L., ... & Wang, Y. (2021). Improved decadal predictions of East Asian summer monsoon with a weakly coupled data assimilation scheme. International Journal of Climatology.

30. Shi, P., Wang, B., He, Y., Lu, H., Yang, K., Xu, S., ... & Wang, Y. (2021). Contributions of weakly coupled data assimilation-based land initialization to interannual predictability of summer climate over Europe. Journal of Climate, 1-55.

29. Zhang, M., Liu, Y., Sun, W., Xiao, Y., Jiang, C., Wang, Y.*, & Bai, Y.* (2021). Impact of Rainfall on Traffic Speed in Major Cities of China. Sustainability, 13(16), 9074.

28. Zhang, M., Liu, Y., Xiao, Y., Sun, W., Zhang, C., Wang, Y.*, & Bai, Y.* (2021). Vulnerability and Resilience of Urban Traffic to Precipitation in China. Int. J. Environ. Res. Public Health.


3. Han, Y., Zhang, G. J., Huang, X., & Wang, Y. (2020). A moist physics parameterization based on deep learning. Journal of Advances in Modeling Earth Systems, 12(9), e2020MS002076.

26. He, Y., Wang, B., Liu, L., Huang, W., Xu, S., Liu, J., Wang, Y., ... & Lin, Y. (2020). A DRP‐4DVar‐Based Coupled Data Assimilation System With a Simplified Off‐Line Localization Technique for Decadal Predictions. Journal of Advances in Modeling Earth Systems, 12(4), e2019MS001768.

25. He, Y., Wang, B., Huang, W., Xu, S., Wang, Y., Liu, L., Wang, Y., ... & Huang, X. (2020). A new DRP-4DVar-based coupled data assimilation system for decadal predictions using a fast online localization technique. Climate Dynamics, 1-19.

24. Jiang, Y., Yang, X. Q., Liu, X., Qian, Y., Zhang, K., Wang, M., Li F., Wang Y., & Lu, Z. (2020). Impacts of wildfire aerosols on global energy budget and climate: The role of climate feedbacks. Journal of Climate, 33(8), 3351-3366.

23. Lin, Y., Huang, X., Liang, Y., Qin, Y., Xu, S., Huang, W., Xu, F., Liu, L., Wang, Y. ... & Wang, L. (2020). Community Integrated Earth System Model (CIESM): Description and Evaluation. Journal of Advances in Modeling Earth Systems, 12(8), e2019MS002036.


22. Yang, Z., Huang, W., He, X., Wang, Y., Qiu, T., Wright, J. S., & Wang, B. (2019). Synoptic conditions and moisture sources for extreme snowfall events over East China. Journal of Geophysical Research: Atmospheres, 124(2), 601-623.

21. Zhang, G. J., Song, X., & Wang, Y. (2019). The double ITCZ syndrome in GCMs: A coupled feedback problem among convection, clouds, atmospheric and ocean circulations. Atmospheric Research, 229, 255-268.

20. Zhang, M., Liu, X., Diao, M., D'Alessandro, J. J., Wang, Y., Wu, C., ... & Xie, S. (2019). Impacts of representing heterogeneous distribution of cloud liquid and ice on phase partitioning of Arctic mixed‐phase clouds with NCAR CAM5. Journal of Geophysical Research: Atmospheres, 124(23), 13071-13090.


19. Li, S., Wang, M., Bond, N. A., Huang, W., Wang, Y., Xu, S., ... & Bai, Y. (2018). Precursors of September arctic sea-ice extent based on causal effect networks. Atmosphere, 9(11), 437.

18. Wang, Y., G. J. Zhang, and Y. Jiang, (2018). Linking Stochasticity of Convection to Large-Scale Vertical Velocity to Improve Indian Summer Monsoon Simulation in the NCAR CAM5. J. Climate, 31, 6985–7002.

17. Wang, Y., Zhang, D., Liu, X., & Wang, Z. (2018). Distinct contributions of ice nucleation, large-scale environment, and shallow cumulus detrainment to cloud phase partitioning with NCAR CAM5. Journal of Geophysical Research: Atmospheres, 123.


16. Chen, S., Huang, J., Qian, Y., Zhao, C., Kang, L., Yang, B., Wang, Y., ... & Zhang, G. (2017). An overview of mineral dust modeling over East Asia. Journal of Meteorological Research, 31(4), 633-653.

15. Wang, Y., Zhang, G. J., & He, Y.-J. (2017). Simulation of precipitation extremesusing a stochastic convective parameterization in the NCAR CAM5 under different resolutions. Journal of Geophysical Research: Atmospheres, 122.

14. Yujun He, Bin Wang, Mimi Liu, Li Liu, Yongqiang Yu, Juanjuan Liu, Ruizhe Li, Cheng Zhang, Shiming Xu, Wenyu Huang, Qun Liu, Yong Wang, Feifei Li (2017). Reduction of initial shock in decadal predictions using anew initialization strategy, Geophys. Res.Lett.,44, 8538–8547.


13. Wang, Y.*, G. J. Zhang, and G. C. Craig (2016), Stochastic convective parameterization improves the simulation of tropical precipitation variability in the NCAR CAM5. Geophys. Res. Lett., 43, doi: 10.1002/2016GL069818.

12. Wang, Y., and G. J. Zhang (2016), Global Climate Impacts of Stochastic Deep Convection Parameterization in the NCAR CAM5, Journal of Advances in Modeling Earth Systems, 8, doi:10.1002/2016MS000756.


11. Luo, T., Wang, Z., Zhang, D., Liu, X., Wang, Y., and Yuan, R. (2015). Global dust distribution from improved thin dust layer detection using A‐train satellite lidar observations, Geophysical Research Letters.


10. Huang, W., ... Wang, Y., Sun, W., Dong, F. (2014). Variability of atlantic meridional overturning circulation in FGOALS-g2. Advances in Atmospheric Sciences 31(1).

9. Wang, Y., Liu, X., Hoose, C., and Wang, B.(2014), Different contact angle distributions for heterogeneous ice nucleation in the Community Atmospheric Model version 5, Atmos. Chem. Phys., 14, 10411-10430, doi:10.5194/acp-14-10411-2014.

8. Wang, Y. and Liu, X.(2014), Immersion freezing by natural dust based on a soccer ball model with the Community Atmospheric Model version 5: Climate effects, Environ. Res. Lett., 9, 124020, doi:10.1088/1748-9326/9/12/124020.

7. English, J. M., J. E. Kay, A. Gettelman, X. Liu, Y. Wang, Y. Zhang, and H. Chepfer (2014), Contributions of clouds, surface albedos, and mixed-phase ice nucleation schemes to Arctic radiation biases in CAM5, Journal of Climate, 27, 5174–5197.

6. Komurcu, M., T. Storelvmo, I. Tan, U. Lohmann, Y. Yun, J. E. Penner, Y. Wang, X. Liu, and T. Takemura (2014), Inter-comparison of the cloud water phase among global climate models, Journal of Geophysical Research, 119, doi:10.1002/2013JD021119.

5. Huang, W., Wang, B., Li, L., Dong, L., Lin, P., Yu, Y., ...Wang, Y., Sun, W. & Dong, F. (2014). Variability of atlantic meridional overturning circulation in FGOALS-g2. Advances in Atmospheric Sciences, 31(1), 95-109.


4. Li, L., Wang, B., Dong, L., Liu, L., Shen, S., Hu, N., Sun, W., Wang, Y., ... & Yang, G. (2013). Evaluation of grid-point atmospheric model of IAP LASG version 2 (GAMIL2). Advances in Atmospheric Sciences, 30(3), 855-867.

3. Wang, B., Liu, M., Yu, Y., Li, L., Lin, P., Dong, L., ... Wang, Y., … & Yang, G. (2013). Preliminary evaluations of FGOALS-g2 for decadal predictions. Advances in Atmospheric Sciences, 30(3), 674-683.

2. Liu, X., Wang, Y., & Hoose, C. (2013, May). Implement a classical-theory-based parameterization of heterogeneous ice nucleation in CAM5. In AIP Conference Proceedings (Vol. 1527, No. 1, pp. 763-765). American Institute of Physics.


1. Dong, L., Li, L., Huang, W., Wang, Y., & Wang, B. (2012). Preliminary evaluation of cloud fraction simulations by GAMIL2 using COSP. Atmospheric and Oceanic Science Letters, 5(3), 258-263.