王勇

2006-2010，南京信息工程大學大氣科學專業 本科

2010-2015，中國科學院大氣物理研究所氣象學專業 博士

2012-2013，美國能源部西北太平洋國家實驗室 訪問學者

2013-2014，美國懷俄明大學 訪問學者

2015-2018，清華大學地球系統科學系 博士后

2018-2021.7 清華大學地球系統科學系 助理教授

2021.7- 清華大學地球系統科學系 准聘副教授

● ● 發展了一套基於經典冰晶異質核化理論的沙塵和黑碳混合雲冰晶異質核化參數化方案，該方案已經被美國國家大氣研究中心（NCAR）下一代地球系統模式中大氣分量模式（CESM2-CAM6）、美國能源部氣候模式（E3SM）以及挪威的氣候模式（NorESM）採用；

● ● 在著名的Zhang-McFarlane對流參數化方案中考慮對流隨機性，改進后的該方案被清華大學地球系統科學系的CIESM地球系統模式採用；

● ● 主持國家自然科學基金面上和青年項目各一項，參與科技部重點研發項目。

2020

● ● Wang, Y., Xia, W., Liu, X., … & Zhang, G. J. (2020). Disproportionate Control on Aerosol Burden by Light Rain. Nature Geoscience.

● ● Sun, W., Wang, B., Wang, Y.* … Yang, M. (2020). Parameterizing Subgrid Variations of Land Surface Heat Fluxes to the Atmosphere Improves Boreal Summer Land Precipitation Simulation with the NCAR CESM1.2. Geophys. Res. Lett.

● ● 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.

2019

● ● 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.

2018

● ● 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.

2017

● ● 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.

2016

● ● 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.

2015

● ● 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.

2014

● ● 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.

● ● 城市化及其氣候影響

● ● 土地利用及其土地覆蓋變化的氣候影響

● ● 人為排放氣溶膠及其氣候影響

● ● 陸面蒸散發及其在全球變暖背景下變化

● ● 沙塵氣溶膠及其全球變暖背景下變化

● ● 野火及其氣候效應 對流-雲-降水-氣溶膠

● ● 積雲對流及其參數化

● ● 雲微物理及其參數化

● ● 對流-雲-降水-氣溶膠相互作用，陸氣相互作用

2021年11月，王勇榮獲2021年度“謝義炳青年氣象科技獎”。