Publications


Zhang, Z., & Zhang, G. J. (2022). Dependence of Convective Cloud Properties and Their Transport on Cloud Fraction and GCM Resolution Diagnosed from a Cloud-Resolving Model Simulation. Journal of Marine Science and Engineering, 10(9), 1318. https://doi.org/10.3390/jmse10091318
Lin, J., Qian, T., Bechtold, P., Grell, G., Zhang, G. J., Zhu, P., Freitas, S. R., Barnes, H., & Han, J. (2022). Atmospheric Convection. Atmosphere-Ocean, 1–55. https://doi.org/10.1080/07055900.2022.2082915
Xia, W. W., Wang, Y., Zhang, G. J., Cui, Z. Y., Wang, B., He, Y. J., & Wang, X. (2022). Unexpected Changes of Aerosol Burdens With Decreased Convection in the Context of Scale-Aware Convection Schemes. Geophysical Research Letters, 49(11). https://doi.org/10.1029/2022gl099008
Wang, X., Han, Y. L., Xue, W., Yang, G. W., & Zhang, G. J. (2022). Stable climate simulations using a realistic general circulation model with neural network parameterizations for atmospheric moist physics and radiation processes. Geoscientific Model Development, 15(9), 3923–3940. https://doi.org/10.5194/gmd-15-3923-2022
Zou, Q. Y., Zhu, L., Lu, C. S., Zhang, G. J., Xu, X. Q., Chen, Q., & Li, D. (2022). Parameterizations of different hydrometeor spectral relative dispersion in the convective clouds. Atmospheric and Oceanic Science Letters, 15(3). https://doi.org/10.1016/j.aosl.2021.100141
Ben, Y., Wang, M. H., Zhang, G. J., Guo, Z., Wang, Y., Xu, X., Dai, G. Q., Huang, A. N., Zhang, Y. C., & Qian, Y. (2022). Parameterizing Convective Organization Effects With a Moisture-PDF Approach in Climate Models: Concept and a Regional Case Simulation. Journal of Advances in Modeling Earth Systems, 14(5). https://doi.org/10.1029/2021ms002942
Wang, Y., Xia, W. W., Zhang, G. J., Wang, B., & Lin, G. X. (2022). Impacts of Suppressing Excessive Light Rain on Aerosol Radiative Effects and Health Risks. Journal of Geophysical Research-Atmospheres, 127(9). https://doi.org/10.1029/2021jd036204
Liu, S., Wang, Y., Zhang, G. J., Wei, L. Y., Wang, B., & Yu, L. (2022). Contrasting influences of biogeophysical and biogeochemical impacts of historical land use on global economic inequality. Nature Communications, 13(1), 14. https://doi.org/10.1038/s41467-022-30145-6
Lin, J. L., Qian, T. T., Bluestein, H. B., Ditlevsen, P., Lin, H., Seiki, T., Tochimoto, E., Barnes, H., Bechtold, P., Carr, F. H., Freitas, S. R., Goodman, S. J., Grell, G., Han, J., Klotzbach, P., Roh, W., Satoh, M., Schubert, S., Zhang, G., & Zhu, P. (2022). Current Challenges in Climate and Weather Research and Future Directions. Atmosphere-Ocean. https://doi.org/10.1080/07055900.2022.2079473
Wang, X., Zhang, G. J., & Suhas, E. (2022). Assessing free tropospheric quasi-equilibrium for different GCM resolutions using a cloud-resolving model simulation of tropical convection. Climate Dynamics, 16. https://doi.org/10.1007/s00382-022-06232-1
Cui, Z. Y., Wang, Y., Zhang, G. J., Yang, M. M., Liu, J., & Wei, L. Y. (2022). Effects of improved simulation of precipitation on evapotranspiration and its partitioning over land. Geophysical Research Letters, 49(5), 10. https://doi.org/10.1029/2021gl097353
Song, F. F., Zhang, G. J., Ramanathan, V., & Leung, L. R. (2022). Trends in surface equivalent potential temperature: A more comprehensive metric for global warming and weather extremes. Proceedings of the National Academy of Sciences of the United States of America, 119(6), 7. https://doi.org/10.1073/pnas.2117832119
Wang, X., Zhang, G. J., & Wang, Y. (2022). Evaluating and improving scale-awareness of a convective parameterization closure using cloud-resolving model simulations of convection. Journal of Geophysical Research-Atmospheres, 127(2), 13. https://doi.org/10.1029/2021jd035729
Xia, W. W., Wang, Y., Chen, S. Y., Huang, J. P., Wang, B., Zhang, G. J., Zhang, Y., Liu, X. H., Ma, J. M., Gong, P., Jiang, Y. Q., Wu, M. X., Xue, J. K., Wei, L. Y., & Zhang, T. H. (2021). Double trouble of air pollution by anthropogenic dust. Environmental Science & Technology, 9. https://doi.org/10.1021/acs.est.1c04779
Wei, L. Y., Wang, Y., Liu, S., Zhang, G., & Wang, B. (2021). Distinct roles of land cover in regulating spatial variabilities of temperature responses to radiative effects of aerosols and clouds. Environmental Research Letters, 16(12), 10. https://doi.org/10.1088/1748-9326/ac3f04
Wang, Y., Xia, W. W., & Zhang, G. J. (2021). What rainfall rates are most important to wet removal of different aerosol types? Atmospheric Chemistry and Physics, 21(22), 16797–16816. https://doi.org/10.5194/acp-21-16797-2021
Wang, Y., Zhang, G. J., Gong, P., Dickinson, R. E., Fu, R., Li, X. C., Yang, J., Liu, S., He, Y. J., Li, L. J., Wang, B., & Xu, B. (2021). Winter Warming in North America Induced by Urbanization in China. Geophysical Research Letters, 48(22), 10. https://doi.org/10.1029/2021gl095465
Cui, Z., Zhang, G. J., Wang, Y., & Xie, S. (2021). Understanding the roles of convective trigger functions in the diurnal cycle of precipitation in the NCAR CAM5. Journal of Climate, 34(15), 6473–6489. https://doi.org/10.1175/jcli-d-20-0699.1
Zhu, L., Lu, C. S., Yan, S. Q., Liu, Y. G., Zhang, G. J., Mei, F., Zhu, B., Fast, J. D., Matthews, A., & Pekour, M. S. (2021). A new approach for simultaneous estimation of entrainment and detrainment rates in non-precipitating shallow cumulus. Geophysical Research Letters, 48(15), 12. https://doi.org/10.1029/2021gl093817
Xu, X. Q., Sun, C., Lu, C. S., Liu, Y. G., Zhang, G. J., & Chen, Q. (2021). Factors affecting entrainment rate in deep convective clouds and parameterizations. Journal of Geophysical Research-Atmospheres, 126(15), 16. https://doi.org/10.1029/2021jd034881
Ben, Y., Wang, M. H., Zhang, G., Guo, Z., Huang, A. N., Zhang, Y. C., & Qian, Y. (2021). Linking deep and shallow convective mass fluxes via an assumed entrainment distribution in CAM5-CLUBB: Parameterization and simulated precipitation variability. Journal of Advances in Modeling Earth Systems, 13(5), 23. https://doi.org/10.1029/2020ms002357
Cao, Z. H., Cai, H. Q., & Zhang, G. J. (2021). Geographic shift and environment change of U.S. tornado activities in a warming climate. Atmosphere, 12(5), 17. https://doi.org/10.3390/atmos12050567
Wang, Y., Zhang, G. J., Xie, S. C., Lin, W. Y., Craig, G. C., Tang, Q., & Ma, H. Y. (2021). Effects of coupling a stochastic convective parameterization with the Zhang-McFarlane scheme on precipitation simulation in the DOE E3SMv1.0 atmosphere model. Geoscientific Model Development, 14(3), 1575–1593. https://doi.org/10.5194/gmd-14-1575-2021
Wang, J. Y., Fan, J. W., Houze, R. A., Brodzik, S. R., Zhang, K., Zhang, G. J., & Ma, P. L. (2021). Using radar observations to evaluate 3-D radar echo structure simulated by the Energy Exascale Earth System Model (E3SM) version 1. Geoscientific Model Development, 14(2), 719–734. https://doi.org/10.5194/gmd-14-719-2021
Peters, J. M., Morrison, H., Zhang, G. J., & Powell, S. W. (2021). Improving the physical basis for updraft dynamics in deep convection parameterizations. Journal of Advances in Modeling Earth Systems, 13(2). https://doi.org/10.1029/2020ms002282
Liu, S., Liu, X. X., Yu, L., Wang, Y., Zhang, G. J., Gong, P., Huang, W. Y., Wang, B., Yang, M. M., & Cheng, Y. Q. (2021). Climate response to introduction of the ESA CCI land cover data to the NCAR CESM. Climate Dynamics. https://doi.org/10.1007/s00382-021-05690-3
Sun, W. Q., Wang, B., Wang, Y., Zhang, G. J., Han, Y. L., Wang, X., & Yang, M. M. (2021). Parameterizing subgrid variations of land surface heat fluxes to the atmosphere improves boreal summer land precipitation simulation with the NCAR CESM1.2. Geophysical Research Letters, 48(1). https://doi.org/10.1029/2020gl090715
Wang, Y., Xia, W. W., Liu, X. H., Xie, S. C., Lin, W. Y., Tang, Q., Ma, H. Y., Jiang, Y. Q., Wang, B., & Zhang, G. J. (2021). Disproportionate control on aerosol burden by light rain. Nature Geoscience. https://doi.org/10.1038/s41561-020-00675-z
Song, X. L., & Zhang, G. J. (2020). Role of equatorial cold tongue in central Pacific double-ITCZ bias in the NCAR CESM1.2. Journal of Climate, 33(24), 10407–10418. https://doi.org/10.1175/jcli-d-20-0141.1
Han, Y. L., Zhang, G. J., Huang, X. M., & Wang, Y. (2020). A moist physics parameterization based on deep learning. Journal of Advances in Modeling Earth Systems, 12(9). https://doi.org/10.1029/2020ms002076
Lin, Y. L., Huang, X. M., Liang, Y. S., Qin, Y., Xu, S. M., Huang, W. Y., Xu, F. H., Liu, L., Wang, Y., Peng, Y. R., Wang, L. N., Xue, W., Fu, H. H., Zhang, G. J., Wang, B., Li, R. Z., Zhang, C., Lu, H., Yang, K., … Gong, P. (2020). Community Integrated Earth System Model (CIESM): Description and evaluation. Journal of Advances in Modeling Earth Systems, 12(8). https://doi.org/10.1029/2019ms002036
Yang, B., Wang, M. H., Zhang, G. J., Guo, Z., Qian, Y., Huang, A. N., & Zhang, Y. C. (2020). Simulated Precipitation Diurnal Variation With a Deep Convective Closure Subject to Shallow Convection in Community Atmosphere Model Version 5 Coupled With CLUBB. Journal of Advances in Modeling Earth Systems, 12(7). https://doi.org/10.1029/2020ms002050
Wright, J. S., Sun, X. Y., Konopka, P., Kruger, K., Legras, B., Molod, A. M., Tegtmeier, S., Zhang, G. J., & Zhao, X. (2020). Differences in tropical high clouds among reanalyses: origins and radiative impacts. Atmospheric Chemistry and Physics, 20(14), 8989–9030. https://doi.org/10.5194/acp-20-8989-2020
Song, F. F., & Zhang, G. J. (2020). The impacts of horizontal resolution on the seasonally dependent biases of the northeastern Pacific ITCZ in coupled climate models. Journal of Climate, 33(3), 941–957. https://doi.org/10.1175/jcli-d-19-0399.1
Zhang, G. J., Song, X. L., & Wang, Y. (2019). The double ITCZ syndrome in GCMs: A coupled feedback problem among convection, clouds, atmospheric and ocean circulations. Atmospheric Research, 229, 255–268. https://doi.org/10.1016/j.atmosres.2019.06.023
Huang, J. P., Chen, W., Wen, Z. P., Zhang, G. J., Li, Z. X., Zuo, Z. Y., & Zhao, Q. Y. (2019). Review of Chinese atmospheric science research over the past 70 years: Climate and climate change. Science China-Earth Sciences, 62(10), 1514–1550. https://doi.org/10.1007/s11430-019-9483-5
Song, X. L., & Zhang, G. J. (2019). Culprit of the Eastern Pacific Double-ITCZ Bias in the NCAR CESM1.2. Journal of Climate, 32(19), 6349–6364. https://doi.org/10.1175/jcli-d-18-0580.1
Cheng, R., & Zhang, G. (2019). Relating convection to GCM grid-scale fields using cloud-resolving model simulation of a squall line observed during MC3E field experiment. Atmosphere, 10(9). https://doi.org/10.3390/atmos10090523
Xie, S. C., Wang, Y. C., Lin, W. Y., Ma, H. Y., Tang, Q., Tang, S. Q., Zheng, X., Golaz, J. C., Zhang, G. J., & Zhang, M. H. (2019). Improved diurnal cycle of precipitation in E3SM with a revised convective triggering function. Journal of Advances in Modeling Earth Systems, 11(7), 2290–2310. https://doi.org/10.1029/2019ms001702
Glotfelty, T., Alapaty, K., He, J., Hawbecker, P., Song, X. L., & Zhang, G. (2019). The Weather Research and Forecasting Model with Aerosol-Cloud Interactions (WRF-ACI): Development, evaluation, and initial application. Monthly Weather Review, 147(5), 1491–1511. https://doi.org/10.1175/mwr-d-18-0267.1
Mitovski, T., Cole, J. N. S., McFarlane, N. A., von Salzen, K., & Zhang, G. J. (2019). Convective response to large-scale forcing in the tropical western Pacific simulated by spCAM5 and CanAM4.3. Geoscientific Model Development, 12(5), 2107–2117. https://doi.org/10.5194/gmd-12-2107-2019
Wang, X., & Zhang, G. J. (2019). Evaluation of the quasi-biweekly oscillation over the South China Sea in early and late summer in CAM5. Journal of Climate, 32(1), 69–84. https://doi.org/10.1175/jcli-d-18-0072.1
Lu, C. S., Sun, C., Liu, Y. G., Zhang, G. J., Lin, Y. L., Gao, W. H., Niu, S. J., Yin, Y., Qiu, Y. J., & Jin, L. J. (2018). Observational relationship between entrainment rate and environmental relative humidity and implications for convection parameterization. Geophysical Research Letters, 45(24), 13495–13504. https://doi.org/10.1029/2018gl080264
Huang, X. M., Hu, C. Q., Huang, X., Chu, Y., Tseng, Y. H., Zhang, G. J., & Lin, Y. L. (2018). A long-term tropical mesoscale convective systems dataset based on a novel objective automatic tracking algorithm. Climate Dynamics, 51(7–8), 3145–3159. https://doi.org/10.1007/s00382-018-4071-0
Song, F. F., & Zhang, G. J. (2018). Understanding and improving the scale dependence of trigger functions for convective parameterization using cloud-resolving model data. Journal of Climate, 31(18), 7385–7399. https://doi.org/10.1175/jcli-d-17-0660.1
Wang, Y., Zhang, G. J., & Jiang, Y. Q. (2018). Linking stochasticity of convection to large-scale vertical velocity to improve Indian Summer Monsoon Simulation in the NCAR CAM5. Journal of Climate, 31(17), 6985–7002. https://doi.org/10.1175/jcli-d-17-0785.1
Yang, M. M., Zhang, G. J., & Sun, D. Z. (2018). Precipitation and moisture in four leading CMIP5 models: Biases across large-scale circulation regimes and their attribution to dynamic and thermodynamic factors. Journal of Climate, 31(13), 5089–5106. https://doi.org/10.1175/jcli-d-17-0718.1
Wang, M. C., & Zhang, G. J. (2018). Improving the simulation of tropical convective cloud-top heights in CAM5 with CloudSat observations. Journal of Climate, 31(13), 5189–5204. https://doi.org/10.1175/jcli-d-18-0027.1
Liu, Y. C., Fan, J. W., Xu, K. M., & Zhang, G. J. (2018). Analysis of cloud-resolving model simulations for scale dependence of convective momentum transport. Journal of the Atmospheric Sciences, 75(7), 2445–2472. https://doi.org/10.1175/jas-d-18-0019.1
Song, X. L., & Zhang, G. J. (2018). The roles of convection parameterization in the formation of double ITCZ Syndrome in the NCAR CESM: I. Atmospheric Processes. Journal of Advances in Modeling Earth Systems, 10(3), 842–866. https://doi.org/10.1002/2017ms001191