Dr. Yang joined Nanjing University in 2012 and currently is an associate professor at School of Atmospheric Sciences. He received his B.S. and Ph.D. in atmospheric sciences from Nanjing University. He was studying as a visiting scholar in the Pacific Northwest National Laboratory (PNNL) for two years when he was a Ph.D. candidate. Dr. Yang’s research passion has been the development of cloud and precipitation parameterizations and uncertainty quantification in climate modeling. He has established a new scheme that can represent transitions from shallow to deep and to organized convection, which improves the physical consistency of cloud dynamics across different convective regimes and the consistency between macro- and micro-physics of convection. Meanwhile, he has developed the uncertainty quantification method andauto-tuning approachfor climate models that usually have numerous physical parameters. He has also been working on the interactions among cloud/precipitation processes, radiation, and circulation as well as their climatic impacts. Dr. Yang has published more than 50 scientific papers and received many prestigious awards. His scheme has been implemented in the Earth system models of China Meteorological Administration (CMA) and Tsinghua University. His research findings have provided key physical parameters for model development in the climate model community, for the planning of new field studies jointly organized by the U.S. Department of Energy and other institutions, and for the designment of ensemble strategy for climate prediction operated by CMA.
2012, Ph.D. in Atmospheric Sciences, Nanjing University
2007, B.Sc. in Atmospheric Sciences, Nanjing University
2015-present, Associate Professor, Nanjing University
2012-2015, Assistant Research Fellow, Nanjing University
Cloud and precipitation parameterizations
Uncertainty quantification in climate modeling
Precipitation response to climate change
Numerical modeling in atmospheric sciences
Yang, B., Wang, M., Zhang, G. J., Guo, Z., Wang, Y., Xu, X., et al. (2022). Parameterizing convective organization effects with a moisture-PDF approach in climate models: Concept and a regional case simulation. Journal of Advances in Modeling Earth Systems, 14, e2021MS002942.
Yang, B., Wang, M., Zhang, G. J., Guo, Z., Huang, A., Zhang, Y., & Qian, Y. (2021): Linking deep and shallow convective mass fluxes via an assumed entrainment distribution in CAM5-CLUBB: Parameterization and simulated precipitation variability. Journal of Advances in Modeling Earth Systems, 13, e2020MS002357.
Liang, Y., Yang, B., Wang, M., Tang, J., Sakaguchi, K., Leung, L. R., & Xu, X. (2021). Multiscale simulation of precipitation over East Asia by variable resolution CAM-MPAS. Journal of Advances in Modeling Earth Systems, 13, e2021MS002656.
Yang, B., Wang, M., Zhang, G. J., Guo, Z., Qian, Y., Huang, A., & Zhang, Y. (2020): Simulated precipitation diurnal variation with a deep convective closure subject to shallow convection in Community Atmosphere Model version 5 coupled with CLUBB. Journal of Advances in Modeling Earth Systems, 11, e2020MS002050.
Yang, B., Zhang, Y., Qian, Y., et al. (2019): Better monsoon precipitation in coupled climate models due to bias compensation. npj Climate and Atmospheric Science, 2, 43.
Yang, B., Berg, L. K., Qian, Y., et al. (2019): Parametric and structural sensitivities of turbine-height wind speeds in the boundary layer parameterizations in the Weather Research and Forecasting model. Journal of Geophysical Research: Atmospheres, 124, 5951– 5969.
Yang, B., Zhang, Y., Qian, Y., Wu, T., Huang, A., & Fang, Y. (2015): Parametric sensitivity analysis for the Asian summer monsoon precipitation simulation in the Beijing Climate Center AGCM version 2.1, Journal of Climate, 28(14): 5622–5644.
Yang, B., Zhang, Y., Qian, Y., Huang, A., & Yan, H. (2015): Calibration of a convective parameterization scheme in the WRF model and its impact on the simulation of East Asian Summer Monsoon precipitation, Climate Dynamics, 44, 1661-1684.
Yang, B., Qian, Y., Lin, G., et al., (2013): Uncertainty quantification and parameter tuning in the CAM5 Zhang-McFarlane convection scheme and impact of improved convection on the global circulation and climate, Journal of Geophysical Research: Atmospheres, 118, 395-415.
Yang, B., Qian, Y., Lin, G., Leung, R., & Zhang, Y. (2012): Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model, Atmospheric Chemistry and Physics, 12, 2409-2427.
2022, Wiley China Open Science Excellent Author Program
2022, Tsinghua University-Inspur Group Computational GeosciencesYoung Talent Award
2021, Jiangsu Meteorological Society Scientific and Technical Award