Yuying Zhang

Portrait of  Yuying Zhang

  • Email
  • Phone
    (925) 423-8505
  • Organization
    Not Available

Research Interests

  • Assessment of cloud simulations using observational data with simulator approach
  • Cloud effect on the Earth’s energy budget and hydrological cycle
  • Model evaluation with satellite and ground-based measurements


Ph.D., Meteorology, University of Utah, 2006 M.S., Meteorology, University of Utah, 2002 B.S., Atmospheric Science, Peking University, China, 1998

Zhang, Y. et al. (2024). Understanding Changes in Cloud Simulations from E3SM Version 1 to Version 2. GMD, https://doi.org/10.5194/gmd-17-169-2024.

Zheng, X., et al. (including Y. Zhang) (2023). Assessment of CMIP5 and CMIP6 AMIP simulated clouds and surface radiation using ARM observations over different climate regions. J. Climate. https://doi.org/10.1175/JCLI-D-23-0247.1.

Qian, Y., et al. (including Y. Zhang) (2023). Region and cloud regime dependence of parametric sensitivity in E3SM Atmosphere Model. Climate Dynamics. V62, 1517-1533, CLDY-D-23-00064.

Zhang, M., et al. (including Y. Zhang) (2023). Evaluating EAMv2 Simulated High Latitude Clouds Using ARM Measurements in the Northern and Southern Hemispheres. JGR-Atmospheres. 2022JD038364.

Tang, Q., et al. (including Y. Zhang) (2023). The fully coupled regionally refined model of E3SM version 2: overview of the atmosphere, land, and river. GMD, https://doi.org/10.5194/GMD-2022-262.

Golaz, J.C., et al. (including Y. Zhang) (2023). The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation. JAMES. DOI: 10.1029/2022MS003156.

Zhang, C., et al. (including Y. Zhang) (2022). The E3SM diagnostics package (E3SM Diags v2.7): A Python-based diagnostics package for Earth System Models Evaluation. GMD. https://doi.org/10.5194/gmd-15-9031-2022.

Zhang, M., et al (including Y. Zhang) (2022). Cloud Phase Simulation at High Latitudes in EAMv2: Evaluation using CALIPSO Observations and Comparison with EAMv1. JGR-Atmospheres. https://doi.org/10.1029/2022JD037100.

Ma, P.L., et al. (including Y. Zhang) (2021). Better calibration of cloud parameterizations and subgrid effects increases the fidelity of E3SM Atmosphere Model version 1. Geoscientific Model Development (GMD). Doi:10.5194/gmd-15-2881-2022.

Zhang, M., et al. (including Y. Zhang) (2020). Toward understanding the simulated phase partitioning of Arctic single-layer mixed-phase clouds in E3SM. Earth and Space Science, 7, e2020EA001125, https://doi.org/10.1029/2020EA001125.

Caldwell, P. M., et al. (including Y. Zhang) (2019). The DOE E3SM coupled model version 1: Description and results at high resolution. JAMES, https://doi.org/10.1029/2019MS001870.

Rasch, P.J., et al. (including Y. Zhang) (2019). An overview of the atmospheric component of the energy exascale earth system model. JAMES, https://doi.org/10.1029/2019MS001629.

Zhang, Y., et al. (2019). Evaluation of clouds in version 1 of the E3SM Atmosphere Model with Satellite Simulators. JAMES. Doi: 10.1029/2018MS001562.

Golaz, J. C., et al. (including Y. Zhang) (2019). The DOE E3SM Coupled Model Version 1: Overview and Evaluation at Standard Resolution. Doi: 10.1029/2018MS001603.

Tang, Q., et al. (including Y. Zhang) (2019). Regionally refined test bed in E3SM atmosphere model version 1 (EAMv1) and applications for high-resolution modeling. Geoscientific Model Development Doi: 10.5194/gmd-12-2679-2019.

Zhang, Y.S. Xie, et al. (2018). The ARM Cloud Radar Simulator for Global Climate Models Bridging Field Data and Climate Models.  BAMS,  https://doi.org/10.1175/BAMS-D-16-0258.1

Xie, S., et al. (including Y. Zhang) (2018). Understanding Cloud and Convective Characteristics in Version 1 of the E3SM Atmosphere Model. JAMES. Doi: 10.1029/2018MS001350.

Ma, H.-Y., C. C. Chuang, S. A. Klein, M.-H. Lo, Y. Zhang, S. Xie, X. Zheng, P.-L. Ma, Y. Zhang, and T. J. Phillips (2015). An Improved hindcast approach for evaluation and diagnosis of physical processes in global climate models. Journal of Advances in Modeling Earth Systems. Vol 7, issue 4, 1810-1827. DOI: 10.1002/2015MS000490.

Gleckler, P. J., et al. (including Y. Zhang), 2016: A more powerful reality test for climate models, Eos, Transactions, American Geophysical Union, 97, (12). DOI: 10.1029/2016EO051663.

Ma, P.-L., et al. (including Y Zhang) , 2015. "How Does Increasing Horizontal Resolution in a Global Climate Model Improve the Simulation of Aerosol-Cloud Interactions?" Geophysical Research Letters 42(12):5058-5065.  doi:10.1002/2015GL064183.

English, J., J. Kay, A. Gettelman, X. Liu, Y. Wang, Y. Zhang, H. Chepfer (2014). Contributions of clouds, surface albedos, and mixed-phase ice nucleation schemes to Arctic radiation biases in CAM5. J. Climate. 27, 5174-5197.

Lucas, D. D., R. Klein, J. Tannahill, D. Ivanova, S. Brandon, D. Domyancic, and Y. Zhang (2013). Failure analysis of parameter-induced simulation crashes in climate models, Geosci. Model Dev., 6, 1157-1171, doi:10.5194/gmd-6-1157-2013.

Xie, S., X. Liu, C. Zhao, and Y. Zhang (2013). Sensitivity of CAM5 Simulated Arctic Clouds and Radiation to Ice Nucleation, J. Climate. 26, 5981-5999, doi:10.1175/JCLI-D-12-00517.1.

Xie, S., X. Liu, C. Zhao, Y. Zhang, et al. (2013). Impact of Ice Nucleation Parameterizations on CAM5 Simulated Arctic Clouds and Radiation: A Sensitivity Study. Nucleation and Atmospheric Aerosols. Doi: 10.1063/1.4803378.

Ma, H., S. Xie, J. Boyle, S. Klein, and Y. Zhang (2013). Development of Metrics and Diagnostics for CAM Climate Model Short-range Forecasts. J. Climate. 26, 1516-1534. http://dx.doi.org/10.1175/JCLI-D-12-00235.1.

Klein, S., Y. Zhang, M. Zelinka, J. Boyle, P. Gleckler, and R. Pincus (2013). Are climate model simulations of clouds improving? An evaluation using the ISCCP simulator. J. Geophys. Res. Atmos., 118, doi:10.1002/jgrd.50141.

Zhang, Y., S. Xie, C. Covey, D. D. Lucas, P. Gleckler, S. Klein, J. Tannahill, C. Doutriaux,and R. Klein (2012). Regional assessment of the parameter-dependent performance of CAM4 in simulating tropical clouds. Geophys. Res. Lett., 39, L14708, doi:10.1029/2012GL052184.

Kay, J. E., and Coauthors including S. A. Klein, Y. Zhang, and J. Boyle (2012). Exposing global cloud biases in the Community Atmosphere Model (CAM) using satellite observations and their corresponding instrument simulators, J. Clim.., doi: http://dx.doi.org/10.1175/JCLI-D-11-00469.

Xie, S., H. Ma, J. Boyle, S. Klein, and Y. Zhang (2012). On the Correspondence between Short- and Long- Timescale Systematic Errors in CAM4/CAM5 for the Years of Tropical Convection.  J. Clim. 25, 7937–7955. doi: http://dx.doi.org/10.1175/JCLI-D-12-00134.1.

Barton, N. P., et al. (including Y. Zhang) (2012). Arctic synoptic regimes: Comparing domain-wide Arctic cloud observations with CAM4 and CAM5 during similar dynamics.  J. Geophys. Res. Atmos., 10.1029/2012JD017589.

Zhao, C., et al. (including Y. Zhang) (2012). Aerosol first indirect effects on non-precipitating low-level liquid cloud properties as simulated by CAM5 at ARM sites. Geophys. Res. Lett.,  10.1029/2012GL051213.

Bodas-Salcedo, A., and Coauthors including S. A. Klein and Y. Zhang (2011). COSP: A satellite simulation software for model assessment. Bull. Amer. Met. Soc., 92, 1023–1043.

Zhang, Y., S. A. Klein, J. Boyle, and G. G. Mace (2010). Evaluation of tropical cloud and precipitation simulations of CAM3 using CloudSat and CALIPSO data. J. Geophys. Res., 115, D12205, doi:10.1029/2009JD012006.

Zhang, Y., et al. (including Y. Zhang) (2008). On the diurnal cycle of deep convection, high-level cloud, and upper troposphere water vapor in the Multiscale Modeling Framework. J. Geophys. Res.. 113, D16105. Doi:10.1029/2008JD009905.

Zhang, Y., S. A. Klein, G. G. Mace, and J. Boyle (2007). Cluster analysis of tropical clouds using CloudSat data. Geophys. Res. Lett., 34, L12813, doi:10.1029/2007GL029336.

Zhang Y., G. G. Mace (2006). Retrieval of Cirrus Microphysical Properties with a Suite of Algorithms for Airborne and Spaceborne Lidar, Radar, and Radiometer Data. Journal of Applied Meteorology and Climatology, 45, 1665-1689.

Mace, G. G., et al. (including Y. Zhang) (2005). Evaluation of cirrus cloud properties derived from MODIS data using cloud properties derived from ground-based observations collected at the ARM SGP site. J. Applied Meteorology and climatology. https://doi.org/10.1175/JAM2193.1