Yunji Zhang

Yunji Zhang

  • Assistant Professor
  • Assistant Director, Penn State Center for Advanced Data Assimilation and Predictability Techniques
624B Walker Building
University Park, PA 16802


  1. 2010 - 2016: Ph.D. in Meteorology, Peking University, China
  2. 2006 - 2010: B.S. in Atmospheric Sciences, Peking University, China


Link to my CV

Link to my Google Scholar

Research Interests:

  • Severe thunderstorms, mesoscale convective systems, and tropical cyclones
  • Ensemble-based data assimilation and numerical weather prediction
  • Predictability of severe weather events


  • DeHart, J., M. Bell, Y. Zhang, and Y.-L. Chen, 2024: Mechanisms contributing to the heavy rainfall associated with a Mei-yu front near Taiwan. Monthly Weather Review, in review.
  • Comer, C. L., D. J. Stensrud, B. C. Stouffer, Y. Zhang, and M. R. Kumjian, 2024: An automated approach to estimating convective boundary layer depth from dual-polarization WSR-88D radar observations. Journal of Atmospheric and Oceanic Technology, in review.
  • Stouffer, B. C., D. J. Stensrud, C. L. Comer, Y. Zhang, and M. R. Kumjian, 2024: Investigating convective boundary layer depth and entrainment zone properties with dual-polarization radar observations. Journal of Atmospheric and Oceanic Technology, in review.
  • Zhang, Y., X. Chen, D. J. Stensrud, and E. E. Clothiaux, 2024: Enhancing severe weather prediction with all-sky microwave radiance assimilation: The 10 August 2020 Midwest derecho. Geophysical Research Letters, 51, e2023GL106602.
  • Mykolajtchuk, P. D., K. C. Eure, D. J. Stensrud, Y. Zhang, F. Zhang, S. J. Greybush, and M. R. Kumjian, 2023: Diagnosing a missed supercell thunderstorm forecast. Weather and Forecasting, 38, 1935-1951.
  • Zhang, Y., 2023: Sensitivity of intrinsic error growth to large-scale uncertainty structure in a record-breaking summertime rainfall event. Journal of the Atmospheric Sciences, 80, 1415-1432.
  • Zhang, Y., X. Chen, and M. M. Bell, 2023: Improving short-term QPF using geostationary satellite all-sky infrared radiances: Real-time ensemble data assimilation and forecast during the PRECIP field campaign. Weather and Forecasting, 38, 591-609.
  • Eure, K. C., P. D. Mykolajtchuk, Y. Zhang, D. J. Stensrud, F. Zhang, S. J. Greybush, and M. R. Kumjian, 2023: Simultaneous assimilation of radar and satellite observations to improve ensemble forecasts of convection initiation. Monthly Weather Review, 151, 795-813.
  • Zhang, Y., H. Yu, M. Zhang, Y. Yang, and Z. Meng, 2022: Uncertainties and error growth in forecasting the record-breaking rainfall in Zhengzhou, Henan on 19–20 July 2021. Science China: Earth Sciences, 65, 1903–1920.
  • Zhang, Y., E. E. Clothiaux, and D. J. Stensrud, 2022: Correlation structures between satellite all-sky infrared brightness temperatures and the atmospheric states at storm scales. Advances in Atmospheric Sciences, 39, 714–732.
  • Zhang, Y., S. B. Sieron, Y. Lu, X. Chen, R. G. Nystrom, M. Minamide, M.-Y. Chan, C. M. Hartman, Z. Yao, J. H. Ruppert, Jr., A. Okazaki, S. J. Greybush, E. E. Clothiaux, and F. Zhang, 2021: Ensemble-based assimilation of satellite all-sky microwave radiances improves intensity and rainfall predictions of Hurricane Harvey (2017). Geophysical Research Letters, 48, e2021GL096410.
  • Zhang, Y., X. Chen, and Y. Lu, 2021: Structure and dynamics of ensemble correlations for satellite all-sky observations in an FV3-based global-to-regional nested convection-permitting ensemble forecast of Hurricane Harvey. Monthly Weather Review, 149, 2409–2430.
  • Zhang, Y., D. J. Stensrud, and E. E. Clothiaux, 2021: Benefits of the Advanced Baseline Imager (ABI) for ensemble-based analysis and prediction of severe thunderstorms. Monthly Weather Review, 149, 313–332.
  • Meng, Z., F. Zhang, D. Luo, Z. Tan, J. Fang, J. Sun, X. Shen, Y. Zhang, S. Wang, W. Han, K. Zhao, L. Zhu, Y. Hu, H. Xue, Y. Ma, L. Zhang, J. Nie, R. Zhou, S. Li, H. Liu, Y. Zhu, 2019: Review of Chinese atmospheric science research over the past 70 years: Synoptic meteorology. Science China: Earth Sciences, 62, 1946–1991.
  • Zhang, Y., D. J. Stensrud, and F. Zhang, 2019: Simultaneous assimilation of radar and all-sky satellite radiance observations for convection-allowing ensemble analysis and prediction of severe thunderstorms. Monthly Weather Review, 147, 4389–4409.
  • Hayatbini, N., K.-L. Hsu, S. Sorroshian, Y. Zhang, and F. Zhang, 2019: Effective cloud detection and segmentation using a gradient-based algorithm for satellite imagery; Application to improve PERSIANN-CCS. Journal of Hydrometeorology, 20, 901–913.
  • Bai, L., Z. Meng, Y. Huang, Y. Zhang, S. Niu, and T. Su, 2019: Convection initiation resulting from the interaction between a quasi-stationary dryline and intersecting gust fronts: A case study. Journal of Geophysical Research, 124, 2379–2396.
  • Zhang Y., F. Zhang, and D. J. Stensrud, 2018: Assimilating all-sky infrared radiances from GOES-16 ABI using an ensemble Kalman filter for convection-allowing severe thunderstorms prediction. Monthly Weather Review, 146, 3363–3381.
  • Pan, J., D. Teng, F. Zhang, L. Zhou, L. Luo, Y. Weng, and Y. Zhang, 2018: Dynamics of local extreme rainfall of super Typhoon Soudelor (2015) in East China. Science China Earth Sciences, 61, 572–594.
  • Zhang, Y., and F. Zhang, 2018: A review on the ensemble-based data assimilations for severe convective storms. Advances in Meteorological Science and Technology (in Chinese), 8, 38–52.
  • Zhang, Y., F. Zhang, D. J. Stensrud, and Z. Meng, 2016: Intrinsic predictability of the tornadic thunderstorm event in Oklahoma on 20 May 2013 at storm scales. Monthly Weather Review, 144, 1271–1298.
  • Zhu, L., Q. Wan, X. Shen, Z. Meng, F. Zhang, Y. Weng, J. Sippel, Y. Gao, Y. Zhang, and J. Yue, 2016: Prediction and predictability of high-impact western Pacific landfalling tropical cyclone Vicente (2012) through convection-permitting ensemble assimilation of Doppler radar velocity. Monthly Weather Review, 144, 21–43.
  • Zhang, Y., F. Zhang, D. J. Stensrud, and Z. Meng, 2015: Practical predictability of the 20 May 2013 tornadic thunderstorm event in Oklahoma: Sensitivity to synoptic timing and topographical influence. Monthly Weather Review, 143, 2973–2997.
  • Zhang, Y., Z. Meng, F. Zhang, and Y. Weng, 2014: Predictability of tropical cyclone intensity evaluated through 5-yr forecasts with a convection-permitting regional-scale model in the Atlantic Basin. Weather and Forecasting, 29, 1003–1023.
  • Meng, Z., D. Yan, and Y. Zhang, 2013: General features of squall lines in East China. Monthly Weather Review, 141, 1629–1647.
  • Meng, Z., and Y. Zhang, 2012: On the squall lines preceding landfalling tropical cyclones in China. Monthly Weather Review, 140, 445–470.