Shuaiqi Tang

Associated Processor

School of Atmospheric Sciences, Nanjing University

Email: shuaiqi.tang@nju.edu.cn

Education

Employment

Research Interests

Prof. Shuaiqi Tang’s research focuses on understanding aerosols, clouds, precipitation and their interactions using field campaigns and other observations, as well as diagnosing the performance of these physical processes in earth system models and improving the relative physical parameterizations. These efforts are dedicated to bridging the gap between atmospheric observations and numerical modeling.

Selected Publications

in review:

• Wang, X., Liu, Y., Liu, Y., Tang, S., et al. (2026). “Evaluation of CAM Single-Column Models in Simulating Convectively Coupled Rossby Gravity Waves during TRMM-KWAJEX.” submitted to Journal of Geophysical Research: Atmospheres

2025:

• Tang, Shuaiqi, Tao, C., Xie, S., & Zhang, M. (2025). Long-Term Large-Scale Atmospheric Forcing Data From Three-Dimensional Constrained Variational Analysis for the ARM SGP Site. Journal of Geophysical Research: Atmospheres, 130(22), e2025JD044443. https://doi.org/10.1029/2025JD044443

• Kaul, C. M., P.-L. Ma, K. G. Pressel, ... Tang, S., et al. (2026). “ A Data Library of Liquid Clouds Modelled With a Large Eddy Simulation Framework.” Geoscience Data Journal 13, no. 1: e70049. https://doi.org/10.1002/gdj3.70049.

• Sorooshian, A., Siu, L. W., Butler, K., Brunke, M. A., Cairns, B., ... Tang, S., et al. (2025). The NASA ACTIVATE Mission. Bulletin of the American Meteorological Society, 106(8), E1517–E1538. https://doi.org/10.1175/BAMS-D-24-0136.1.

• Soloff, C., Crosbie, E. C., Diskin, G. S., Gao, L., Kirschler, S., Lenhardt, E. D., ... Tang, S., et al. (2025). Cloud Condensation Nuclei Behavior and Closure Assessment for the Northwest Atlantic Ocean. ACS ES&T Air, 2(11), 2388–2400. https://doi.org/10.1021/acsestair.5c00151

• Meng Huang, Po-Lun Ma, Jerome Fast, ... Tang, S., et al. (2025). Evaluation of E3SM simulated aerosols and aerosol-cloud interactions across GCM and convection-permitting scales. Journal of Advances in Modeling Earth Systems, 17, e2025MS005288. https://doi.org/10.1029/2025MS005288

2024:

• Tang, Shuaiqi, H. Wang, X. Y. Li, J. Chen et al., (2024): Understanding aerosol–cloud interactions using a single-column model for a cold-air outbreak case during the ACTIVATE campaign, Atmos. Chem. Phys., 24, 10073–10092, https://doi.org/10.5194/acp-24-10073-2024.

• Mei, F., Comstock, J. M., Pekour, M. S., Fast, J. D., Schmid, B., Gaustad, K. L., Tang, S., et al. (2024): Atmospheric Radiation Measurement (ARM) airborne field campaign data products between 2013 and 2018, Earth Syst. Sci. Data, 16, 5429–5448, https://doi.org/10.5194/essd-16-5429-2024.

• Ovchinnikov, M., Ma, P.-L., Kaul, C. M., Pressel, K. G., Huang, M., Shpund, J., & Tang, S. (2024). Evaluation of autoconversion representation in E3SMv2 using an ensemble of large-eddy simulations of low-level warm clouds. Journal of Advances in Modeling Earth Systems, 16, e2024MS004280. https://doi.org/10.1029/2024MS004280.

• Zhao, B., Donahue, N.M., Zhang, K., ... Tang, S., et al. (2024). Global variability in atmospheric new particle formation mechanisms. Nature. https://doi.org/10.1038/s41586-024-07547-1.

• Li X., H. Wang, J. Chen, S. Tang, S. Kirschler, E. Crosbie, and L.D. Ziemba, et al. (2024). Process Modeling of Aerosol-cloud Interaction in Summertime Precipitating Shallow Cumulus over the Western North Atlantic. Journal of Geophysical Research: Atmospheres. 129, e2023JD039489. https://doi.org/10.1029/2023JD039489

• Tao, C., Xie, S., Ma, H.-Y., Tang, S., et al., (2024). Diurnal cycle of precipitation over the tropics and central United States: intercomparison of general circulation models. Quarterly Journal of the Royal Meteorological Society, 150, 911–936. https://doi.org/10.1002/qj.4629

2023:

• Tang, Shuaiqi, Varble, A. C., Fast, J. D., Zhang, K., Wu, P., Dong, X., Mei, F., Pekour, M., Hardin, J. C. and Ma, P.-L. (2023). Earth System Model Aerosol-Cloud Diagnostics Package (ESMAC Diags) Version 2: Assessments of Aerosols, Clouds and Aerosol-Cloud Interactions Through Field Campaign and Long-Term Observations, Geosci. Model Dev. 16, 6355–6376, https://doi.org/10.5194/gmd-16-6355-2023, 2023.

• Varble, A. C., P.-L. Ma, M. Christensen, J. Mülmenstädt, S. Tang and J. D. Fast (2023). Evaluation of Liquid Cloud Albedo Susceptibility in E3SM Using Coupled Eastern North Atlantic Surface and Satellite Retrievals. Atmos. Chem. Phys. 23, 13523–13553, https://doi.org/10.5194/acp-23-13523-2023, 2023.

• Matsui, T., D. B. Wolff, S. Lang, K. Mohr, M. Zhang, S. Xie, S. Tang, et al. (2023). Systematic Validation of Ensemble Cloud-Process Simulations using Polarimetric Radar Observations and Simulator over the NASA Wallops Flight Facility. Journal of Geophysical Research: Atmospheres, 128, e2022JD038134. https://doi.org/10.1029/2022JD038134.

• Tao, C., Xie, S., Tang, S., Lee, J., Ma, H.-Y., Zhang, C., and Lin, W., (2023): Diurnal cycle of precipitation over global monsoon systems in CMIP6 simulations, Clim Dyn, https://doi.org/10.1007/s00382-022-06546-0.

2022:

• Tang, Shuaiqi, Fast, J. D., Zhang, K., Hardin, J. C., Varble, A. C., Shilling, J. E., Mei, F., Zawadowicz, M. A., and Ma, P.-L. (2022). Earth System Model Aerosol-Cloud Diagnostics Package (ESMAC Diags) Version 1: Assessing E3SM Aerosol Predictions Using Aircraft, Ship, and Surface Measurements, Geosci. Model Dev. 15, 4055–4076, https://doi.org/10.5194/gmd-15-4055-2022

• Tang, Shuaiqi, S. Xie, H-Y. Ma, et al., (2022). Long-Term Single-Column Model Intercomparison on Diurnal Cycle of Precipitation Over Tropical and Mid-Latitude Land. Quarterly Journal of the Royal Meteorological Society, 148, 641– 669. https://doi.org/10.1002/qj.4222

2021:

• Ciesielski, P. E., R. H. Johnson, S. Tang, Y. Zhang, & S. Xie, (2021).  Comparison of Conventional and Constrained Variational Methods for Computing Large-Scale Budgets and Forcing Fields. J Geophys Res-Atmos, 126, e2021JD035183. https://doi.org/10.1029/2021JD035183

• Tang, Shuaiqi, P. J. Gleckler, S. Xie, J-W Lee, C. Covey, C. Zhang et al., (2021). Evaluating Diurnal and Semi-Diurnal Cycle of Precipitation in CMIP6 Models Using Satellite- and Ground-Based Observations. Journal of Climate, 34, 3189-3210, 10.1175/jcli-d-20-0639.1.

• Zhang, C., Xie, S., Tao, C., Tang, S., Emmenegger, T., Neelin, J. D., Schiro, K. A., Lin, W., and Shaheen, Z. (2021): Evaluating Climate Models: The ARM Data-Oriented Metrics and Diagnostics Toolkit, Bulletin of the American Meteorological Society, 102, 347-350, https://doi.org/10.1175/bams-d-20-0282.A.

• Cheng Tao, Y. Zhang, Q. Tang, H-Y. Ma, V. P. Ghate, S. Tang, S. Xie and J. A. Santanello (2021). Land–Atmosphere Coupling at the U.S. Southern Great Plains: A Comparison on Local Convective Regimes between ARM Observations, Reanalysis, and Climate Model Simulations, Journal of Hydrometeorology, 22(2), 463-481, https://doi.org/10.1175/jhm-d-20-0078.1.

• Hsi-Yen Ma, K. Zhang, S. Tang, S. Xie and R. Fu (2021). Evaluation of the causes of wet-season dry biases over Amazonia in CAM5. Journal of Geophysical Research: Atmospheres, 126, e2020JD033859. https://doi.org/10.1029/2020JD033859

Other Selected Publications

• Tang, Shuaiqi, S. Xie, M. Zhang and S. Endo, (2020). The Impact of Terrain-Following Coordinate to the Large-Scale Forcing and Shallow-Cumulus Simulations at the ARM SGP site. Journal of Geophysical Research: Atmospheres, 125, e2020JD032492. https://doi.org/10.1029/2020JD032492

• Peter A. Bogenschutz, S. Tang, P. M. Caldwall, S. Xie, W. Lin and Y. Chen. (2020). The E3SM version 1 Single Column Model. Geosci. Model Dev., 13, 4443–4458, https://doi.org/10.5194/gmd-13-4443-2020

• Tang, Shuaiqi, Xie, S., Zhang, M., Tang, Q., Zhang, Y., Klein, S. A., et al. (2019). Differences in eddy‐correlation and energy‐balance surface turbulent heat flux measurements and their impacts on the large‐scale forcing fields at the ARM SGP site. Journal of Geophysical Research: Atmospheres. 124, 3301– 3318. https://doi.org/10.1029/2018JD029689

• Tang, Shuaiqi, M. Zhang, and S. Xie, 2017: Investigating the Dependence of SCM Simulated Precipitation and Clouds on the Spatial Scale of Large-Scale Forcing at SGP. J. Geophys. Res. Atmos., 122, doi:10.1002/2017JD026565

• Tang, Shuaiqi, et al., 2016: Large-Scale Vertical Velocity, Diabatic Heating and Drying Profiles Associated with Seasonal and Diurnal Variations of Convective Systems Observed in the GoAmazon2014/5 Experiment, Atmos. Chem. Phys., 16(22), 14249-14264, doi: 10.5194/acp-16-14249-2016.

• Tang, Shuaiqi, M. Zhang, and S. Xie, 2016: An ensemble constrained variational analysis of atmospheric forcing data and its application to evaluate clouds in CAM5, Journal of Geophysical Research: Atmospheres, 121(1), 33-48, doi: 10.1002/2015JD024167.

• Tang, Shuaiqi, and M. Zhang, 2015: Three-dimensional constrained variational analysis: Approach and application to analysis of atmospheric diabatic heating and derivative fields during an ARM SGP intensive observational period, Journal of Geophysical Research: Atmospheres, 120(15), 7283-7299, doi: 10.1002/2015JD023621.

Awards, honors, positions and services

  Group Achievement Award to ACTIVATE Earth Venture Sub-orbital Mission, NASA, 2023
  Physical and Life Sciences Directorate Award for improving our ability to model one of climate’s most challenging aspects: precipitation. LLNL, April 16, 2020
  Deputy Director for Science and Technology Excellence in Publication Award, LLNL, 2019
  Physical and Life Sciences Directorate Award for improving our understanding of the role of clouds, radiation, and precipitation processes in contributing to surface temperature biases. LLNL, August 15, 2018

Additional Information

Developed value-added data products and tools:
  ARM large-scale forcing from the constrained variational analysis (VARANAL)
  Three-dimensional large-scale forcing data from the 3D constrained variational analysis (VARANAL3D)
  Quality-controlled eddy-correlation flux measurements (QCECOR)
  ARM best estimate data (ARMBE)
  Earth system model aerosol-cloud diagnostics package (ESMAC Diags) (github, paper1, paper2)