PNNL

Dr. Shixuan Zhang conducts research at the intersection of atmospheric science, data assimilation, machine learning, numerical modeling, and high-performance computing. His work focuses on improving the accuracy and interpretability of Earth system processes across spatial and temporal scales in a rapidly evolving environment. By integrating theoretical insights with advanced computational approaches, Dr. Zhang contributes foundational innovations to Earth system science. His interdisciplinary research advances scientific understanding and delivers practical tools with direct societal relevance.

• Computational Earth System Science
• Atmospheric Modeling, Data Assimilation, and Predictability
• Application of Machine Learning in Earth Sciences
• High-Impact Weather Systems
• Earth System Model Evaluation and Development
• Tropical Cyclones and Hurricane Forecasting

• Models: Energy Exascale Earth System Model (E3SM), Weather Research and Forecasting (WRF), Hurricane Weather Research Forecast (HWRF) Model
• Data Assimilation Systems: Data Assimilation Research Testbed (DART), Gridpoint Statistical Interpolation (GSI)
• Programming Languages: Fortran, Python, MATLAB, Shell scripting
• Tools and Frameworks: NCL, GrADS, TempestExtremes

• PhD in Atmospheric Sciences, University of Utah, USA 
• MS in Meteorology, Lanzhou University, China
• BS in Atmospheric Sciences, Lanzhou University, China

• Member, American Geophysical Union (AGU)
• Member, American Meteorological Society (AMS)
• Member, Society for Industrial and Applied Mathematics (SIAM)
• Associate Editor, Weather and Forecasting
• Review Editor, Frontiers in Environmental Science

• E3SM Outstanding Contribution Award (2025)
• PNNL Outstanding Performance Award (2018)
• Best Student Poster Presentation, American Meteorological Society’s 21st Conference on Satellite Meteorology (2016)
• National Scholarship for Graduate Students (2012)
• Undergraduate Honors Thesis (2010)
• National Scholarship for Undergraduate Students (2009)
• China National Innovative Experiment Program for Undergraduates (2009)
• National Encouragement Award (2008)
• Outstanding Undergraduate Student Award (2007-2009)

Visit my Google Scholar Page

2025

• Huo Y., H. Wang, M. Veneziani, D. Comeau, R. Osinski, B.R. Hillman, and E.L. Roesler, et al. 2025. "E3SM-Arctic: Regionally Refined Coupled Model for Advanced Understanding of Arctic Systems Interactions." Journal of Advances in Modeling Earth Systems 17, no. 6:e2024MS004726. PNNL-SA-203932. doi:10.1029/2024MS004726

2024

• Hassan Mozumder M., K. Zhang, J. Li, B. Singh, S. Zhang, H. Wang, and P. Ma. 2024. "Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol-climate model." Geoscientific Model Development 17, no. 8:3507-3532. PNNL-SA-185364. doi:10.5194/gmd-17-3507-2024
• Li J., K. Zhang, M. Hassan Mozumder, S. Zhang, P. Ma, B. Singh, and Q. Yan, et al. 2024. "Assessing the Sensitivity of Aerosol Mass Budget and Effective Radiative Forcing to Horizontal Grid Spacing in E3SMv1 Using A Regional Refinement Approach." Geoscientific Model Development 17, no. 3:1327-1347. PNNL-SA-183690. doi:10.5194/gmd-17-1327-2024
• Shi P., L. Leung, B. Wang, K. Zhang, S.M. Hagos, and S. Zhang. 2024. "The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2." Geoscientific Model Development 17, no. 7:3025-3040. PNNL-SA-186390. doi:10.5194/gmd-17-3025-2024
• Zhang S., B.E. Harrop, L. Leung, A. Charalampopoulos, B. Barthel Sorensen, W. Xu, and T. Sapsis. 2024. "A Machine Learning Bias Correction of Large-scale Environment of High-Impact Weather Systems in E3SM Atmosphere Model." Journal of Advances in Modeling Earth Systems 16, no. 8:e2023MS004138. PNNL-SA-192555. doi:10.1029/2023MS004138

2023

• Zhang S., C.J. Vogl, V.E. Larson, Q.M. Bui, H. Wan, P.J. Rasch, and C. Woodward. 2023. "Removing numerical pathologies in a turbulence parameterization through convergence testing." Journal of Advances in Modeling Earth Systems 15, no. 5:Art. No. e2023MS003633. PNNL-SA-171844. doi:10.1029/2023MS003633

2022

• Brunke M., L. Cutler, R. Urzua, A. Corral, E. Crosbie, J. Hair, and C.A. Hostetler, et al. 2022. "Aircraft Observations of Turbulence in Cloudy and Cloud-Free Boundary Layers Over the Western North Atlantic Ocean From ACTIVATE and Implications for the Earth System Model Evaluation and Development." Journal of Geophysical Research: Atmospheres 127, no. 19:e2022JD036480. PNNL-SA-169729. doi:10.1029/2022JD036480
• Fan J., Y. Zhang, J. Wang, J. Jeong, X. Chen, S. Zhang, and Y. Lin, et al. 2022. "Contrasting Responses of Hailstorms to Anthropogenic Climate Change in Different Synoptic Weather Systems." Earth's Future 10, no. 8:Art. No. e2022EF002768. PNNL-SA-159712. doi:10.1029/2022EF002768
• Fan J., Y. Zhang, J. Wang, J. Jeong, X. Chen, S. Zhang, and Y. Lin, et al. 2022. "Contrasting Responses of Hailstorms to Anthropogenic Climate Change in Different Synoptic Weather Systems." Earth's Future 10, no. 8:Art. No. e2022EF002768. PNNL-SA-170992. doi:10.1029/2022EF002768
• Wan H., K. Zhang, P.J. Rasch, V.E. Larson, X. Zeng, S. Zhang, and R. Dixon. 2022. "CondiDiag 1.0: A flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)." Geoscientific Model Development 15, no. 8:3205-3231. PNNL-SA-167080. doi:10.5194/gmd-15-3205-2022
• Zhang K., W. Zhang, H. Wan, P.J. Rasch, S.J. Ghan, R.C. Easter, and X. Shi, et al. 2022. "Effective radiative forcing of anthropogenic aerosols in E3SM version 1: historical changes, causality, decomposition, and parameterization sensitivities." Atmospheric Chemistry and Physics 22, no. 13:9129-9160. PNNL-SA-169371. doi:10.5194/acp-22-9129-2022
• Zhang S., K. Zhang, H. Wan, and J. Sun. 2022. "Further improvement and evaluation of nudging in the E3SM Atmosphere Model version 1 (EAMv1): simulations of the mean climate, weather events, and anthropogenic aerosol effects." Geoscientific Model Development 15, no. 17:6787-6816. PNNL-SA-169668. doi:10.5194/gmd-15-6787-2022

2021

• Wan H., S. Zhang, P.J. Rasch, V. Larson, X. Zeng, and H. Yan. 2021. "Quantifying and attributing time step sensitivities in present-day climate simulations conducted with EAMv1." Geoscientific Model Development 14, no. 4:1921-1948. PNNL-SA-156407. doi:10.5194/gmd-14-1921-2021

2020

• Vogl C.J., H. Wan, S. Zhang, C. Woodward, and P. Stinis. 2020. "Improving time step convergence in an atmosphere model with simplified physics: using mathematical rigor to avoid nonphysical behavior in a parameterization." Journal of Advances in Modeling Earth Systems 12, no. 10:Article No. e2019MS001974. PNNL-SA-149966. doi:10.1029/2019MS001974
• Wan H., C. Woodward, S. Zhang, C.J. Vogl, P. Stinis, D. Gardner, and P.J. Rasch, et al. 2020. "Improving time step convergence in an atmosphere model with simplified physics: the impacts of closure assumption and process coupling." Journal of Advances in Modeling Earth Systems 12, no. 10:Article No. e2019MS001982. PNNL-SA-149970. doi:10.1029/2019MS001982
• Zhang S., and Z. Pu. 2020. "Evaluation of the Four-dimensional Ensemble-Variational Hybrid Data Assimilation with Self-consistent Regional Background Error Covariance for Improved Hurricane Intensity Forecasts." Atmosphere 11, no. 9:1007. PNNL-SA-156318. doi:10.3390/atmos11091007

2019

• Sun J., K. Zhang, H. Wan, P. Ma, Q. Tang, and S. Zhang. 2019. "Impact of nudging strategy on the climate representativeness and hindcast skill of constrained EAMv1 simulations." Journal of Advances in Modeling Earth Systems 11, no. 12:3911-3933. PNNL-SA-149231. doi:10.1029/2019MS001831
• Zhang S., H. Wan, P.J. Rasch, B. Singh, V.E. Larson, and C. Woodward. 2019. "An objective and efficient method for assessing the impact of reduced-precision calculations on solution correctness." Journal of Advances in Modeling Earth Systems 11, no. 10:3131-3147. PNNL-SA-145080. doi:10.1029/2019MS001817