NOAA GFDL - Geophysical Fluid Dynamics LaboratoryGFDL - Geophysical Fluid Dynamics Laboratory

Total refereed publications (158 papers, H-index: 54, total citation: 10804; based on Web of Science as of 11/10/2024)

Below are selected publications based on areas of research (including citations as of 10/15/2021)

Selected publications on global atmosphere, climate, and Earth system model development

  1. Zhao, Ming, I. M. Held, S-J Lin, and G. A. Vecchi, 2009: Simulations of global hurricane climatology, inter-annual variability, and response to global warming using a 50km resolution GCM. Journal of Climate, 22(24), DOI: 10.1175/2009JCLI3049.1. (Citation: 433 times Web of Science; 609 times Google Scholar; This is the GFDL HiRAM model documentation paper)
  2. Zhao, Ming, J-C Golaz, I. M. Held, and 42 co-authors, 2018a: The GFDL Global Atmosphere and Land Model AM4.0/LM4.0 – Part I: Simulation Characteristics with Prescribed SSTs. Journal of Advances in Modeling Earth Systems. DOI:10.1002/2017MS001208. (Citation: 81 times Web of Science; 100 times Google Scholar)
  3. Zhao, Ming, J-C Golaz, I. M. Held, and 42 co-authors, 2018b: The GFDL Global Atmosphere and Land Model AM4.0/LM4.0 – Part II: Model Description, Sensitivity Studies, and Tuning Strategies. Journal of Advances in Modeling Earth Systems. DOI:10.1002/2017MS001209. (Citation: 97 times Web of Science; 118 times Google Scholar) 
  4. Held, I. M., and co-authors including Ming Zhao, 2019: Structure and Performance of GFDL’s CM4.0 Climate Model. Journal of Advances in Modeling Earth Systems, 11(11), DOI:10.1029/2019MS001829 (Citation: 81 times Web of Science; 107 times Google Scholar) 
  5. Dunne, J. P., and co-authors including Ming Zhao 2020: The GFDL Earth System Model version 4.1 (GFDL-ESM 4.1): Overall coupled model description and simulation characteristics. Journal of Advances in Modeling Earth Systems, 12(11), DOI:10.1029/2019MS002015. (Citation: 48 times Web of Science; 66 times Google Scholar) 
  6. Delworth, T. L., and co-authors including Ming Zhao, 2020: SPEAR – the next generation GFDL modeling system for seasonal to multidecadal prediction and projection. Journal of Advances in Modeling Earth Systems, 12(3), DOI:10.1029/2019MS001895. (Citation: 20 times Web of Science; 25 times Google Scholar)
  7. Horowitz, L. W., and co-authors including Ming Zhao, 2020: The GFDL Global Atmospheric Chemistry-Climate Model AM4.1: Model Description and Simulation Characteristics. Journal of Advances in Modeling Earth Systems, 12(10), DOI:10.1029/2019MS002032. (Citation: 16 times Web of Science; 24 times Google Scholar)
  8. Lin, M, LW Horowitz, Ming Zhao, L Harris, P Ginoux, JP Dunne, S Malyshev, E Shevliakova, H Ahsan, ST Garner, F Paulot, A Pouyaei, SJ Smith, Y Xie, N Zadeh, and L Zhou,  2024: The GFDL variable-resolution global chemistry-climate model for research at the nexus of US climate and air quality extremes. Journal of Advances in Modeling Earth Systems, 16(4), DOI:10.1029/2023MS003984.
    1. Guo, H, Y Ming, S Fan, L Zhou, L Harris, and Ming Zhao, 2021: Two-moment bulk cloud microphysics with prognostic precipitation in GFDL’s Atmosphere Model AM4.0: configuration and performance. Journal of Advances in Modeling Earth Systems, 13(6), DOI:10.1029/2020MS002453.
    2. Chu, W, Y. Lin, and Ming Zhao, 2021: Implementation and evaluation of a double-plume convective parameterization in NCAR CAM5, DOI: https://doi.org/10.1175/JCLI-D-21-0267.1
    3. Donner, Leo J., and  co-authors including Ming Zhao, 2011: The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL Global Coupled Model CM3. Journal of Climate, 24(13), DOI:10.1175/2011JCLI3955.1. (Citation: 684 times Web of Science; 901 times Google Scholar)

        Selected publications on tropical cyclones and large-scale environmental connections

        1. Zhao, Ming, and I. M. Held, 2012: TC-permitting GCM simulations of hurricane frequency response to sea surface temperature anomalies projected for the late 21st century. Journal of Climate, 25(8), DOI: 10.1175/JCLI-D-11-00313.1. (Citation: 87 times Web of Science; 113 times Google Scholar)
        2. Zhao, Ming, I. M. Held, and S-J Lin, 2012: Some counter-intuitive dependencies of tropical cyclone frequency on parameters in a GCM. Journal of the Atmospheric Sciences, 69(7), DOI: 10.1175/JAS-D-11-0238.1. (Citation: 75 times Web of Science; 95 times Google Scholar)
        3. Zhao, Ming, I. M. Held, and G. A. Vecchi, 2010: Retrospective forecasts of the hurricane season using a global atmospheric model assuming persistence of SST anomalies. Monthly Weather Review, 138(10), DOI:10.1175/2010MWR3366.1. (Citation: 70 times Web of Science; 110 times Google Scholar)
        4. Zhao, Ming, and I. M. Held, 2010: An analysis of the effect of global warming on the intensity of Atlantic hurricanes using a GCM with statistical refinement. Journal of Climate, 23(23), DOI: 10.1175/2010JCLI3837.1. (Citation: 62 times Web of Science; 82 times Google Scholar)
        5. Zhao, Ming, I. M. Held, S-J Lin, and G. A. Vecchi, 2009: Simulations of global hurricane climatology, inter-annual variability, and response to global warming using a 50km resolution GCM. Journal of Climate, 22(24), DOI: 10.1175/2009JCLI3049.1. (Citation: 433 times Web of Science; 609 times Google Scholar)
        6. Held, I. M. and Ming Zhao, 2011: The response of tropical cyclone statistics to an increase in CO2 with fixed sea surface temperatures. Journal of Climate, 24(20), DOI:10.1175/JCLI-D-11-00050.1. (Citation: 83 times Web of Science; 127 times Google Scholar)
        7. Lin, Y., Ming Zhao, and M. Zhang, 2015: Tropical cyclone rainfall area controlled by relative sea surface temperature. Nature Communications, 6, 6591, DOI:10.1038/ncomms7591. (Citation:76 times Web of Science; 99 times Google Scholar)
        8. Murakami, H., T. L. Delworth, W. F. Cooke, Ming Zhao, B. Xiang, and P-C Hsu, 2020: Detected climatic change in global distribution of tropical cyclones. Proceedings of the National Academy of Sciences, 117(20), DOI:10.1073/pnas.1922500117. (Citation: 24 times Web of Science, 38 times Google Scholar)
        9. Walsh, Kevin J., and  co-authors including Ming Zhao, 2015: Hurricanes and climate: the U.S. CLIVAR working group on hurricanes. Bulletin of the American Meteorological Society, 96(6), DOI:10.1175/BAMS-D-13-00242.1. (Citation: 107 times Web of Science; 145 times Google Scholar)
        10. Vecchi, G. A., Ming Zhao, H. Wang, G. Villarini, A. Rosati, A. Kumar, I. M. Held, and R. G. Gudgel,  2011: Statistical-dynamical predictions of seasonal North Atlantic hurricane activity. Monthly Weather Review, 139(4), DOI:10.1175/2010MWR3499.1. (Citation: 106 times Web of Science; 143 times Google Scholar)
        11. Knutson, T. R., J. J. Sirutis, Ming Zhao, R. E. Tuleya, M. A. Bender, G. A. Vecchi, G. Villarini, and D. Chavas, 2015: Global Projections of Intense Tropical Cyclone Activity for the Late Twenty-First Century from Dynamical Downscaling of CMIP5/RCP4.5 Scenarios. Journal of Climate, 28(18), DOI:10.1175/JCLI-D-15-0129.1. (Citation: 197 times Web of Science; 323 times Google Scholar)
        12. Knutson, T. R., J. J. Sirutis, G. A. Vecchi, S. T. Garner, Ming Zhao, H-S Kim, M. A. Bender, R. E Tuleya, I. M. Held, and G. Villarini, 2013: Dynamical downscaling projections of 21st century Atlantic hurricane activity: CMIP3 and CMIP5 model-based scenario. Journal of Climate, 26(17), DOI:10.1175/JCLI-D-12-00539.1. (Citation:202 times Web of Science; 301 times Google Scholar)
        13. Li, T., M. Kwon, and Ming Zhao, 2010: Global warming shifts Pacific tropical cyclone location. Geophysical Research Letters, 37, L21804, DOI:10.1029/2010GL045124. (Citation: 72 times Web of Science; 105 times Google Scholar)
        14. Camargo, S. J., M. K. Tippett, A. Sobel, G. A. Vecchi, and Ming Zhao, 2014: Testing the performance of tropical cyclone genesis indices in future climates using the HIRAM model. Journal of Climate, 27(24), DOI:10.1175/JCLI-D-13-00505.1. (Citation: 78 times Web of Science; 100 times Google Scholar)
        15. Villarini, G., D. A. Lavers, E. Scoccimarro, Ming Zhao, M. F. Wehner, G. A. Vecchi, T. R. Knutson, and K. A. Reed, 2014: Sensitivity of Tropical Cyclone Rainfall to Idealized Global Scale Forcings. Journal of Climate, 27(12), DOI:10.1175/JCLI-D-13-00780.1. (Citation: 69 times Web of Science; 90 times Google Scholar)
        16. Shaevitz, D. and co-authors including Ming Zhao, 2014: Characteristics of tropical cyclones in high-resolution models in the present climate. Journal of Advances in Modeling Earth Systems, 6(4), DOI:10.1002/2014MS000372. (Citation: 79 times Web of Science; 98 times Google Scholar)
        17. Kim, H.-S., G. A. Vecchi, T. R. Knutson, W. G. Anderson, T. L. Delworth, A. Rosati, F. Zeng, and Ming Zhao, 2014: Tropical Cyclone Simulation and Response to CO2 Doubling in the GFDL CM2.5 High-Resolution Coupled Climate Model. Journal of Climate, 27(21), DOI:10.1175/JCLI-D-13-00475.1. (Citation: 81 times Web of Science; 101 times Google Scholar)
        18. Vecchi, G. A., S. Fueglistaler, I. M. Held, T. R. Knutson, and Ming Zhao, 2013: Impacts of atmospheric temperature trends on tropical cyclone activity. Journal of Climate, 26(11), DOI:10.1175/JCLI-D-12-00503.1. (Citation: 67 times Web of Science; 103 times Google Scholar)
        19. Scoccimarro, E., S. Gualdi, G. Villarini, G. A. Vecchi, Ming Zhao, K. Walsh, and A. Navarra 2014: Intense Precipitation Events Associated with Landfalling Tropical Cyclones in response to a Warmer Climate and increased CO2. Journal of Climate, 27(12), DOI:10.1175/JCLI-D-14-00065.1. (Citation: 55 times Web of Science; 79 times Google Scholar)
        20. Horn, M, K. Walsh, Ming Zhao, S. J. Camargo, E. Scoccimarro, H. Murakami, H. Wang, and A. Ballinger, A. Kumar, D. A. Shaevitz, J. A. Jonas, K. Oouchi 2014: Tracking Scheme Dependence of Simulated Tropical Cyclone Response to Idealized Climate Simulations. Journal of Climate, 27(24), DOI:10.1175/JCLI-D-14-00200.1. (Citation: 55 times Web of Science; 70 times Google Scholar)

        Selected publications on clouds, cloud feedbacks, and climate sensitivity

        1. Zhao, Ming, 2024: Cloud radiative effects associated with daily weather regimes. Geophysical Research Letters, 51(10), DOI:10.1029/2024GL109090.
        2. Zhao, Ming, 2022: An investigation of the effective climate sensitivity in GFDL’s new climate models CM4.0 and SPEAR. J. Climate. DOI: https://doi.org/10.1175/JCLI-D-21-0327.1
        3. Zhao, Ming, J-C Golaz, I. M. Held, V. Ramaswamy, S-J Lin, Y. Ming, P. Ginoux, B. Wyman, L. J. Donner, D. Paynter and H. Guo, 2016: Uncertainty in model climate sensitivity traced to representations of cumulus precipitation microphysics. Journal of Climate, 29, 543-560. DOI: 10.1175/JCLI-D-15-0191.1 (Citation: 81 times Web of Science; 99 times Google Scholar, NOAA OAR Outstanding Paper Award)
        4. Zhao, Ming, 2014: An investigation of the connections among convection, clouds, and climate sensitivity in a global climate model. Journal of Climate, 27(5), DOI: 10.1175/JCLI-D-13-00145.1. (Citation: 65 times Web of Science; 83 times Google Scholar)
        5. Zhang, B, Ming Zhao, and Z Tan, 2023: Using a Green’s Function approach to diagnose the pattern effect in GFDL AM4 and CM4. Journal of Climate, 36(4), DOI:10.1175/JCLI-D-22-0024.11105–1124.
        6. Zhang, B, Ming Zhao, H He, B J Soden, Z Tan, B Xiang, and C Wang, 2023: The dependence of climate sensitivity on the meridional distribution of radiative forcing. Geophysical Research Letters, 50(18), DOI:10.1029/2023GL105492.
        7. Bloch-Johnson, J, M  Rugenstein, MJ Alessi, C Proistosescu, Ming Zhao, Bosong Zhang, Andrew I L Williams, Jonathan M Gregory, Jason N S Cole, Yue Dong, Margaret L Duffy, Sarah M Kang, and Chen Zhou, February 2024: The Green’s Function Model Intercomparison Project (GFMIP) protocol. Journal of Advances in Modeling Earth Systems, 16(2), DOI:10.1029/2023MS003700.
        8. N. J. Lutsko, S. C. Sherwood, and Ming Zhao, 2021: Precipitation Efficiency and Climate Sensitivity, a chapter in Clouds and Climate Monograph, Geophysical Monograph Series.
        9. Winton, M., A. Adcroft, J. P. Dunne, I. M. Held, E. Shevliakova, Ming Zhao, H. Guo, W. J. Hurlin, J. P. Krasting, T. R. Knutson, D. J. Paynter, L. G. Silvers, and R. Zhang, 2020: Climate Sensitivity of GFDL’s CM4.0. Journal of Advances in Modeling Earth Systems, 12(1), DOI:10.1029/2019MS001838. (Citation: 10 times Web of Science; 13 times Google Scholar)
        10. Paulot, F., D. J. Paynter, M. Winton, P. Ginoux, Ming Zhao, and L. W. Horowitz, 2020: Revisiting the impact of sea salt on climate sensitivity. Geophysical Research Letters, 47(3), DOI:10.1029/2019GL085601. (Citation: 6 times Web of Science; 6 times Google Scholar)
        11. Naud, C. M., J. F. Booth, J. Jeyaratnam, L. J. Donner, C. J. Seman, Ming Zhao, H. Guo, and Y. Ming,  2019: Extratropical Cyclone Clouds in the GFDL climate model: diagnosing biases and the associated causes. Journal of Climate, 32(20), DOI:10.1175/JCLI-D-19-0421.1.  (Citation: 4 times Web of Science; 4 times Google Scholar)
        12. Silvers, L. G., D. J. Paynter, and Ming Zhao, 2018: The Diversity of Cloud Responses to Twentieth Century Sea Surface Temperatures. Geophysical Research Letters, 45(1), DOI:10.1002/2017GL075583. (Citation: 15 times Web of Science; 15 times Google Scholar)
        13. Xiang, B., Ming Zhao, I. M. Held, and J.-C. Golaz, 2017: Predicting the severity of spurious “double ITCZ” problem in CMIP5 coupled models from AMIP simulations. Geophysical Research Letters, 44(3), DOI:10.1002/2016GL071992. (Citation: 43 times Web of Science; 57 times Google Scholar)
        14. Webb, M J., and co-authors including Ming Zhao, 2015: The impact of parametrized convection on cloud feedback. Philosophical Transactions of the Royal Society of London, A, 373, DOI:10.1098/rsta.2014.0414. (Citation: 51 times Web of Science; 57 times Google Scholar)
        15. Zhang, M, and co-authors including  Ming Zhao, 2013: CGILS: Results from the first phase of an international project to understand the physical mechanisms of low cloud feedbacks in single column models. Journal of Advances in Modeling Earth Systems, 5(4), DOI:10.1002/2013MS000246. (Citation: 88 times Web of Science; 103 times Google Scholar)
        16. Teixeira, J. and co-authors including Ming Zhao, 2011: Tropical and sub-tropical cloud transitions in weather and climate prediction models: the GCSS/WGNE Pacific Crosssection Intercomparison (GPCI). Journal of Climate, 24(20), DOI:10.1175/2011JCLI3672.1. (Citation: 88 times Web of Science; 115 times Google Scholar)
        17. Golaz, J.-C., M. Salzmann, L. J. Donner, L. W. Horowitz, Y. Ming, and Ming Zhao, 2011: Sensitivity of the aerosol indirect effect to subgrid variability in the cloud parameterization of the GFDL Atmosphere General Circulation Model AM3. Journal of Climate, 24(13), DOI:10.1175/2010JCLI3945.1. (Citation: 78 times Web of Science; 109 times Google Scholar)

        Selected publications on high-impact weather, precipitation, MJO, intraseasonal variability and predictions

        1. Zhao, Ming, and T R Knutson, 2024: Crucial role of sea surface temperature warming patterns in near-term high-impact weather and climate projection. npj Climate and Atmospheric Science, 7, 130, DOI:10.1038/s41612-024-00681-7.
        2. Zhao, Ming, 2021: A study of AR, TC, and MCS associated precipitation and extreme precipitation in present and warmer climates. J.  Climate.  DOI:10.1175/JCLI-D-21-0145.1
        3. Zhao, Ming, 2020: Simulations of atmospheric rivers, their variability and response to global warming using GFDL’s new high resolution general circulation model. Journal of Climate, 33(23), DOI:10.1175/JCLI-D-20-0241.1. (Citation: 4 times Web of Science; 8 times Google Scholar)
        4. Dong, W, Ming Zhao, Z Tan, and V Ramaswamy, 2024: Atmospheric rivers over eastern US affected by Pacific/North America pattern. Science Advances, 10(4), DOI:10.1126/sciadv.adj3325.
        5. Liang, W, Ming Zhao, Z Tan, T R Knutson, W Dong, and B Zhang, 2024: The direct radiative effect of CO2 increase on summer precipitation in North America. Geophysical Research Letters, 51(14), DOI:10.1029/2024GL109202.
        6. Dong, W, Ming Zhao, Yi Ming, JP Krasting, and V Ramaswamy, 2023: Simulation of United States mesoscale convective systems using GFDL’s new high-resolution general circulation model. Journal of Climate, 36(19), DOI:10.1175/JCLI-D-22-0529.16967-6990.
        7. Emanuele, GS, Ming Zhao, and K Hodges, 2023: Poleward intensification of midlatitude extreme winds under warmer climate. npj Climate and Atmospheric Science, 6, 219, DOI:10.1038/s41612-023-00540-x.
        8. Dong, W., Ming Zhao, Y. Ming, and V. Ramaswamy, 2021: Representation of tropical mesoscale convective systems in a general circulation model: Climatology and response to global warming. Journal of Climate, 34(14), DOI:10.1175/JCLI-D-20-0535.1.
        9. Yin, J. and Ming Zhao, 2021: Influence of the Atlantic meridional overturning circulation on the U.S. extreme cold weather. Communications Earth and Environment, 2, 218, DOI:10.1038/s43247-021-00290-9.
        10. Xiang, B., and co-authors including  Ming Zhao, 2021: S2S Prediction in GFDL SPEAR: MJO diversity and teleconnections, Bulletin of the American Meteorological Society.(In press)
        11. Yin, J., S. M. Griffies, M. Winton, Ming Zhao, and L. Zanna, 2020: Response of storm-related extreme sea level along the US Atlantic coast to combined weather and climate forcing. Journal of Climate, 33(9), DOI:10.1175/JCLI-D-19-0551.1. (Citation: 5 times Web of Science; 7 times Google Scholar)
        12. Zhu, Y, T. Li, Ming Zhao, and T. Nasuno, 2019: Interaction between MJO and High Frequency Waves over Maritime Continent in Boreal Winter. Journal of Climate, 32(13), DOI:10.1175/JCLI-D-18-0511.1.  (Citation: 4 times Web of Science; 9 times Google Scholar)
        13. Jiang, X., A. F. Adames, Ming Zhao, D. E. Waliser, and E. Maloney, 2018a: A unified moisture mode framework for seasonality of the Madden-Julian Oscillation. Journal of Climate, 31(11), DOI:10.1175/JCLI-D-17-0671.1. (34 citations Web of Science, 43 times Google Scholar)
        14. Jiang, X., B. Xiang, Ming Zhao, T. Li, S-J Lin, Z. Wang, and J-H Chen, 2018b: Intraseasonal tropical cyclogenesis prediction in a global coupled model system. Journal of Climate, 31(15), DOI:10.1175/JCLI-D-17-0454.1. (13 citations Web of Science, 17 times Google Scholar)
        15. Jiang, X., Ming Zhao, E. D. Maloney, and D. E. Waliser, 2016: Convective moisture adjustment time-scale as a key factor in regulating model amplitude of the Madden-Julian Oscillation. Geophysical Research Letters, 43(19), DOI:10.1002/2016GL070898. (46 citations Web of Science, 35 times Google Scholar)
        16. Xiang, B., Ming Zhao, X. Jiang, S-J Lin, T. Li, X. Fu, and G. A. Vecchi, 2015a: The 3-4 week MJO prediction skill in a GFDL coupled model. Journal of Climate, 28(13), DOI:10.1175/JCLI-D-15-0102.1. (58 citations Web of Science; 76 times Google Scholar)
        17. Xiang, B., S-J Lin, Ming Zhao, G. A. Vecchi, T. Li, X. Jiang, L. Harris, and J-H Chen, 2015b: Beyond weather time scale prediction for hurricane Sandy and super typhoon Haiyan in a global climate model. Monthly Weather Review, 143(2), DOI:10.1175/MWR-D-14-00227.1. (38 citations Web of Science; 52 times Google Scholar)
        18. Jiang, X., Ming Zhao, and D. E. Waliser, 2012: Modulation of tropical cyclones over the eastern Pacific by the intra-seasonal variability simulated in an AGCM. Journal of Climate, 25(19), DOI:10.1175/JCLI-D-11-00531.1. (Citation: 68 times Web of Science; 68 times Google Scholar)

        Selected publications on studies of convection, clouds, and climate using idealized model hierarchy

        1. Zhao, Ming, and P. H. Austin, 2005: Life cycle of numerically simulated shallow cumulus clouds. Part I: Transport. Journal of the Atmospheric Sciences, 62(5), 1269-1290. (Citation: 56 times Web of Science; 75 times Google Scholar)
        2. Zhao, Ming, and P. H. Austin, 2005: Life cycle of numerically simulated shallow cumulus clouds. Part II: Mixing dynamics. Journal of the Atmospheric Sciences, 62(5), 1291-1310. (Citation: 61 times Web of Science; 87 times Google Scholar)
        3. Held, I. M., Ming Zhao, and B. Wyman, 2007: Dynamic radiative-convective equilibria using GCM column physics. Journal of the Atmospheric Sciences, 64(1), 228-238. (Citation: 58 times Web of Science; 77 times Google Scholar)
        4. Held, I. M. and Ming Zhao, 2008: Horizontally homogeneous rotating radiative–convective Equilibria at GCM resolution. Journal of the Atmospheric Sciences, 65(6), DOI:10.1175/2007JAS2604.1. (Citation: 36 times Web of Science; 45 times Google Scholar)
        5. Kang, S. M., I. M. Held, D. M. W. Frierson, and Ming Zhao, 2008: The response of the ITCZ to extratropical thermal forcing: Idealized slab-ocean experiments with a GCM. Journal of Climate, 21(14), DOI:10.1175/2007JCLI2146.1. (Citation: 401 times Web of Science; 530 times Google Scholar)
        6. Merlis, T. M., Ming Zhao, and I. M. Held, 2013: The sensitivity of hurricane frequency to ITCZ changes and radiatively forced warming in aquaplanet simulations. Geophysical Research Letters, 40(15), DOI:10.1002/grl.50680. (Citation: 54 times Web of Science; 79 times Google Scholar)
        7. Merlis, T. M., W. Zhou, I. M. Held, and Ming Zhao, 2016: Surface temperature dependence of tropical cyclone-permitting simulations in a spherical model with uniform thermal forcing. Geophysical Research Letters, 43(6), DOI:10.1002/2016GL067730. (Citation: 26 times Web of Science; 37 times Google Scholar)
        8. Ballinger, A., T. M. Merlis, I. M. Held, and Ming Zhao, 2015: The sensitivity of tropical cyclone activity to off-equatorial thermal forcing in aquaplanet simulations. Journal of the Atmospheric Sciences, 72(6), DOI:10.1175/JAS-D-14-0284.1. (Citation: 21 times Web of Science; 31 times Google Scholar)
        9. Medeiros, B., B. Stevens, I. M. Held, Ming Zhao, D. L. Williamson, J. Olson, and C. S. Bretherton,  2008: Aquaplanets, climate sensitivity, and low clouds. Journal of Climate, 21(19), DOI:10.1175/2008JCLI1995.1. (Citation: 128 times Web of Science; 173 times Google Scholar)
        10. Wyant, M. C. and co-authors including Ming Zhao, 2007: A single-column model intercomparison of a heavily drizzling stratocumulus-topped boundary layer. Journal of Geophysical Research, D24204, DOI:10.1029/2007JD008536. (Citation: 32 times Web of Science; 44 times Google Scholar)
        11. Wing, Allison A., and co-authors including Ming Zhao, 2020: Clouds and Convective Self-Aggregation in a Multi-Model Ensemble of Radiative-Convective Equilibrium Simulations. Journal of Advances in Modeling Earth Systems, 12(9), DOI:10.1029/2020MS002138. (Citation: 12 times Web of Science; 17 times Google Scholar)

        Selected publications on other general topics of significance

        1. Ginoux, P., J. M. Prospero, T. E. Gill, C. Hsu, and Ming Zhao, 2012: Global scale attribution of anthropogenic and natural dust sources and their emission rates based on MODIS Deep Blue aerosol products. Reviews of Geophysics, 50, RG3005, DOI:10.1029/2012RG000388. (Citation: 678 times Web of Science; 984 times Google Scholar)
        2. Sheffield, J, and co-authors including Ming Zhao, 2013: North American Climate in CMIP5 Experiments. Part II: Evaluation of Historical Simulations of Intra-Seasonal to Decadal Variability. Journal of Climate, 26(23), DOI:10.1175/JCLI-D-12-00593.1. (Citation: 94 times Web of Science; 125 times Google Scholar)
        3. Maloney, E. and co-authors including Ming Zhao 2014: North American Climate in CMIP5 Experiments: Part III: Assessment of 21st Century Projections. Journal of Climate, 27(6), DOI:10.1175/JCLI-D-13-00273.1. (Citation: 180 times Web of Science; 272 times Google Scholar)
        4. Hsu, P, T. Li, J.-J. Luo, H. Murakami, A. Kitoh, and Ming Zhao, 2012: Increase of global monsoon area and precipitation under global warming: A robust signal? Geophysical Research Letters, 39, L06701, DOI:10.1029/2012GL051037. (Citation: 82 times Web of Science; 122 times Google Scholar)
        5. Orbe, C, L. V. Roekel, A. F. Adames, A. Dezfuli, J. Fasullo, P. J. Gleckler, J. Lee, W. Li, L. Nazarenko, G. A. Schmidt, K. R. Sperber, and Ming Zhao, 2020: Representation of Modes of Variability in 6 U.S. Climate Models. Journal of Climate, 33(17), DOI:10.1175/JCLI-D-19-0956.1 .(Citation: 7 times Web of Science; 14 times Google Scholar)