王勇 - 清华大学 - 地球系统科学系

个人简介

教育经历 2006-2010，南京信息工程大学大气科学专业本科 2010-2015，中国科学院大气物理研究所气象学专业博士 2012-2013，美国能源部西北太平洋国家实验室访问学者 2013-2014，美国怀俄明大学访问学者工作经历 2015-2018，清华大学地球系统科学系博士后 2018-2021.7 清华大学地球系统科学系助理教授 2021.7- 清华大学地球系统科学系准聘副教授奖励荣誉发展了一套基于经典冰晶异质核化理论的沙尘和黑碳混合云冰晶异质核化参数化方案，该方案已经被美国国家大气研究中心（NCAR）下一代地球系统模式中大气分量模式（CESM2-CAM6）、美国能源部气候模式（E3SM）以及挪威的气候模式（NorESM）采用在著名的Zhang-McFarlane对流参数化方案中考虑对流随机性，改进后的该方案被清华大学地球系统科学系的CIESM地球系统模式采用 2021年度“谢义炳青年气象科技奖” 第十届“清华大学-浪潮集团计算地球科学青年人才奖”

研究领域

地球系统模式研发（对流、云微物理等参数化方案研发）对流-云-降水-气溶胶相互作用野火及其气候效应人为排放气溶胶及其气候影响沙尘气溶胶及其全球变暖背景下变化土地利用及其土地覆盖变化的气候影响陆面蒸散发及其在全球变暖背景下变化

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

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). 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). 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). 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. Xia, W., Wang, Y.*, Chen, S.*, … (2021). Double trouble of air pollution by anthropogenic dust. Environmental Science & Technology. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. Huang, W., ... Wang, Y., Sun, W., Dong, F. (2014). Variability of atlantic meridional overturning circulation in FGOALS-g2. Advances in Atmospheric Sciences 31(1). 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. 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. 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. 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. 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. 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. 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. 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. 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.