Research Area

Global warming poses significant challenges to the ecosystem and human society. However, the Earth's atmosphere is governed by complex nonlinear dynamics and projecting its change due to anthropogenic warming is a difficult task.  The current generation of global climate models can predict how large-scale features of the atmosphere respond to warming, but regarding to regional-scale response, they are too coarse to resolve these features. Prof. Shi research experience involves a wide range of topics in atmospheric dynamics, including mountain meteorology, extreme precipitation, and tropical circulation. At HKUST, his group aims to develop new computational tools and theories to understand the interaction between large-scale circulation features and regional-scale atmospheric phenomena, such as severe convection, atmospheric boundary layer, and tropical cyclones. His group will apply machine learning to facilitate high-resolution climate modeling and aim to achieve a reliable and insightful estimation of future climate state in tropical and subtropical areas.

• Atmospheric boundary layer
• Extreme weather
• Mountain meteorology
• Regional climate change

Research Interests

• Atmospheric boundary layer
• Climate Dynamics
• Cloud Dynamics
• Extreme Precipitation
• Mountain Meteorology
• Numerical Modeling

Recent Publications

• Wang, Y., Z. Zhang, W.S. Chow, Z. Wang, J.Z. Yu, J. C.-H. Fung, and X. Shi, (2023). Investigating the Effect of Aerosol Uncertainty on Convective Precipitation Forecasting in South China’s Coastal Area. Journal of Geophysical Research: Atmospheres, 128, e2023JD038694. https://doi.org/10.1029/2023JD038694.
• Qu, Y., & Shi, X., 2022: Can a Machine-Learning-Enabled Numerical Model Help Extend Effective Forecast Range through Consistently Trained Subgrid-Scale Models?, Artificial Intelligence for the Earth Systems (published online ahead of print 2022). Retrieved Jan 3, 2023, https://doi.org/10.1175/AIES-D-22-0050.1
• Shi, X. and Y. Wang, 2022: Impacts of Cumulus Convection and Turbulence Parameterizations on the Convective-Permitting Simulation of Typhoon Precipitation, Monthly Weather Review, 150(11). 2977-2997. https://doi.org/10.1175/MWR-D-22-0057.1 
• Wang, Y., X. Shi, L. Lei, and J. C. Fung, 2022: Deep-Learning Augmented Data Assimilation: Reconstructing Missing Information with Convolutional Autoencoders, Monthly Weather Review, 150(8), 1977-1991. https://doi.org/10.1175/MWR-D-21-0288.1
• Fan, Y., Y. T. Cheung, X. Shi, 2021: The Essential Role of Cloud-Radiation Interaction in Nonrotating Convective Self-Aggregation, Geophys. Res. Lett., 48, e2021GL095102. https://doi.org/10.1029/2021GL095102.
• Shi, X, and Y. Fan, 2021: Modulation of the Bifurcation in Radiative-Convective Equilibrium by Gray-Zone Cloud and Turbulence Parameterizations, J. Adv. Model. Earth Syst., 13, e2021MS002632. https://doi.org/10.1029/2021MS002632.
• Lestari, D. V., and X. Shi, 2021: Sensitivity of the Short-Range Precipitation Forecast in SouthChina Region to Sea Surface Temperature Variations, Atmosphere, 12(9), 1138. https://doi.org/10.3390/atmos12091138.
• Shi, X., 2020: Enabling Smart Dynamical Downscaling of Extreme Precipitation Events with Machine Learning, Geophys. Res. Lett., 47, e2020GL090309. https://doi.org/10.1029/2020GL090309
• FK Chow, JS Simon, X. Shi, RL Street, 2019: The Dynamic Reconstruction Model in the Turbulent Gray Zone, AGUFM 2019, A31D-01
• Shi, X., R. M. Enriquez, R. L. Street, G. H. Bryan, and F. K. Chow, 2019: An Implicit Algebraic Turbulence Closure Scheme for Atmospheric Boundary Layer Simulation, J. Atmos. Sci., 76, 3367–3386.
• Shi, X., F. K. Chow, R. L. Street and G. H. Bryan, 2019: Key Elements of Turbulence Closures for Simulating Deep Convection at Kilometer-Scale Resolution, J. Adv. Model. Earth Syst., 11. https://doi.org/10.1029/2018MS001446.
• Su, L., J. Li, X. Shi, and J. C. H. Fung, 2019: Spatiotemporal variation in pre-summer precipitation over South China from 1979 to 2015 and its relationship with urbanization , J. Geophys. Res., 124. https://doi.org/10.1029/2019JD030751.
• Chow, F. K, C. Schar, N. Ban, K. Lundquist, L. Schlemmer and X. Shi, 2019: Crossing multiple gray zones in the transition from mesoscale to microscale simulation over complex terrain, Atmosphere , 10, 274; doi:10.3390/atmos10050274. 
• Shi, X., F. K. Chow, R. L. Street and G. H. Bryan, 2018: An Evaluation of LES Turbulence Models for Scalar Mixing in the Stratocumulus-Capped Boundary Layer, J. Atmos. Sci., 75, 1499-1507​
• Shi, X., H. L. Hagen, F. K. Chow, G. H. Bryan and R. L. Street, 2018: Large-Eddy Simulation of the Stratocumulus-Capped Boundary Layer with Explicit Filtering and Reconstruction Turbulence Modeling, J. Atmos. Sci., 75, 611-637.
• Shi, X. and D. R. Durran, 2016: Sensitivities of Extreme Precipitation to Global Warming Are Lower over Mountains than over Oceans and Plains, J. Climate, 29, 4779-4791.