Abstract
This study investigated the cloud microphysical processes and atmospheric water budget during the extreme precipitation event on 20 July 2021 in Zhengzhou of Henan Province, China, based on observations, reanalysis data, and the results from the high-resolution large-eddy simulation nested in the Weather Research and Forecasting (WRF) model with assimilation of satellite and radar observations. The results show that the abundant and persistent southeasterly supply of water vapor, induced by Typhoons In-Fa and Cempaka, under a particular synoptic pattern featured with abnormal northwestward displacement of the western Pacific subtropical high, was conducive to warm rain processes through a high vapor condensation rate of cloud water and an efficient collision–coalescence process of cloud water to rainwater. Such conditions were favorable for the formation and maintenance of the quasi-stationary warm-sector heavy rainfall. Precipitation formation through the collision–coalescence process of cloud water to rainwater accounted for approximately 70% of the total, while the melting of snow and graupel accounted for only approximately 30%, indicating that warm cloud processes played a dominant role in this extreme rainfall event. However, enhancement of cold cloud processes promoted by latent heat release also exerted positive effect on rainfall during the period of most intense hourly rainfall. It was also found that rainwater advection from outside of Zhengzhou City played an important role in maintaining the extreme precipitation event.
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References
Bao, J.-W., S. A. Michelson, and E. D. Grell, 2019: Microphysical process comparison of three microphysics parameterization schemes in the WRF model for an idealized squall-line case study. Mon. Wea. Rev., 147, 3093–3120, doi: https://doi.org/10.1175/MWR-D-18-0249.1.
Chang, W.-Y., W.-C. Lee, and Y.-C. Liou, 2015: The kinematic and microphysical characteristics and associated precipitation efficiency of subtropical convection during SoWMEX/TiM-REX. Mon. Wea. Rev., 143, 317–340, doi: https://doi.org/10.1175/MWR-D-14-00081.1.
Chen, B. J., H. Y. Wu, and M. J. Zeng, 2005: Modeling study of cloud and precipitation physical processes of the 5 July 2003 heavy rainfall in Nan**g. Scientia Meteor. Sinica, 25, 26–31, doi: https://doi.org/10.3969/j.issn.1009-0827.2005.01.004. (in Chinese)
Chen, F., and J. Dudhia, 2001: Coupling an advanced land surface-hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569–585, doi: https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2.
Chen, Y. H., F. **, S. W. Zhou, et al., 2021: Influence of microphysical processes on the initiation of the mesoscale convective system of a rainstorm over Bei**g. Atmos. Res., 254, 105518, doi: https://doi.org/10.1016/j.atmosres.2021.105518.
Chyi, D., L. F. He, X. M. Wang, et al., 2022: Fine observation characteristics and thermodynamic mechanisms of extreme heavy rainfall in Henan on 20 July 2021. J. Appl. Meteor. Sci., 33, 1–15, doi: https://doi.org/10.11988/1001-3313.02200101. (in Chinese)
De Meij, A., and J. F. Vinuesa, 2014: Impact of SRTM and Corine Land Cover data on meteorological parameters using WRF. Atmos. Res., 143, 351–370, doi: https://doi.org/10.1016/j.atmosres.2014.03.004.
Ding, Y. H., 2015: On the study of the unprecedented heavy rainfall in Henan Province during 4–8 August 1975: Review and assessment. Acta Meteor. Sinica, 73, 411–424, doi: https://doi.org/10.11676/qxxb2015.067. (in Chinese)
Eiserloh, A. J.,Jr., and S. Chiao, 2015: Modeling studies of land-falling atmospheric rivers and orographic precipitation over northern California. Meteor. Atmos. Phys., 127, 1–16, doi: https://doi.org/10.1007/s00703-014-0350-4.
Fan, J. W., R. Y. Zhang, W.-K. Tao, et al., 2008: Effects of aerosol optical properties on deep convective clouds and radiative forcing. J. Geophys. Res. Atmos., 113, D08209, doi: https://doi.org/10.1029/2007JD009257.
Fowler, L. D., M. C. Barth, and K. Alapaty, 2020: Impact of scale-aware deep convection on the cloud liquid and ice water paths and precipitation using the Model for Prediction Across Scales (MPAS-v5.2). Geosci. Model Dev., 13, 2851–2877, doi: https://doi.org/10.5194/gmd-13-2851-2020.
Franklin, C. N., G. J. Holland, and P. T. May, 2005: Sensitivity of tropical cyclone rainbands to ice-phase microphysics. Mon. Wea. Rev., 133, 2473–2493, doi: https://doi.org/10.1175/MWR2989.1.
Fu, D. H., and X. L. Guo, 2007: The role of cumulus merger in a severe mesoscale convective system. Chinese J. Atmos. Sci., 31, 635–644, doi: https://doi.org/10.3878/j.sssn.1006-9895.2007.04.08. (in Chinese)
Fu, D. H., and X. L. Guo, 2012: A cloud-resolving simulation study on the merging processes and effects of topography and environmental winds. J. Atmos. Sci., 69, 1232–1249, doi: https://doi.org/10.1175/JAS-D-11-049.1.
Fu, Q., Y. T. Zhang, T. X. Li, et al., 2018: Spatiotemporal complexity analysis of daily precipitation in a changing environment in Heilongjiang Province, China. J. Hydrol. Eng., 23, 04018045, doi: https://doi.org/10.1061/(ASCE)HE.1943-5584.0001703.
Fu, S.-M., Y.-C. Zhang, H.-J. Wang, et al., 2022: On the evolution of a long-lived mesoscale convective vortex that acted as a crucial condition for the extremely strong hourly precipitation in Zhengzhou. J. Geophys. Res. Atmos., 127, e2021JD0 36233, doi: https://doi.org/10.1029/2021JD036233.
Gao, S. T., X. P. Cui, Y. S. Zhou, et al., 2005: Surface rainfall processes as simulated in a cloud-resolving model. J. Geophys. Res. Atmos., 110, D10202, doi: https://doi.org/10.1029/2004JD005467.
Gao, W. H., L. P. Liu, J. Li, et al., 2018: The microphysical properties of convective precipitation over the Tibetan Plateau by a subkilometer resolution cloud-resolving simulation. J. Geophys. Res. Atmos., 123, 3212–3227, doi: https://doi.org/10.1002/2017JD027812.
Guo, C. W., H. **ao, H. L. Yang, et al., 2015: Observation and modeling analyses of the macro- and microphysical characteristics of a heavy rain storm in Bei**g. Atmos. Res., 156, 125–141, doi: https://doi.org/10.1016/j.atmosres.2015.01.007.
Guo, C. W., H. **ao, H. L. Yang, et al., 2019: Effects of cloud microphysical latent heat on a heavy rainstorm in Bei**g. Asia-Pac. J. Atmos. Sci., 55, 477–492, doi: https://doi.org/10.1007/s13143-018-0095-y.
Guo, C. W., H. **ao, W. Wen, et al., 2020: Effect of melting processes on the structure and precipitation of a heavy rainstorm in Bei**g. Atmos. Sci. Lett., 21, e963, doi: https://doi.org/10.1002/asl.963.
He, J., M. Chen, J. Q. Zhong, et al., 2019: A study of three-dimensional radar reflectivity mosaic assimilation in the regional forecasting model for North China. Acta Meteor. Sinica, 77, 210–232, doi: https://doi.org/10.11676/qxxb2019.005. (in Chinese)
Heath, N. K., H. E. Fuelberg, S. Tanelli, et al., 2017: WRF nested large-eddy simulations of deep convection during SEAC4RS. J. Geophys. Res. Atmos., 122, 3953–3974, doi: https://doi.org/10.1002/2016JD025465.
Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 2318–2341, doi: https://doi.org/10.1175/MWR3199.1.
Huang, Y. J., and X. P. Cui, 2015: Dominant cloud microphysical processes of a torrential rainfall event in Sichuan, China. Adv. Atmos. Sci., 32, 389–400, doi: https://doi.org/10.1007/s00376-014-4066-7.
Huang, Y. J., X. P. Cui, and X. F. Li, 2016: A three-dimensional WRF-based precipitation equation and its application in the analysis of roles of surface evaporation in a torrential rainfall event. Atmos. Res., 169, 54–64, doi: https://doi.org/10.1016/j.atmosres.2015.09.026.
Huang, Y. J., Y. P. Wang, and X. P. Cui, 2019a: Differences between convective and stratiform precipitation budgets in a torrential rainfall event. Adv. Atmos. Sci., 16, 495–509, doi: https://doi.org/10.1007/s00376-019-8159-1.
Huang, Y. J., Y. B. Liu, Y. W. Liu, et al., 2019b: Mechanisms for a record-breaking rainfall in the coastal metropolitan city of Guangzhou, China: Observation analysis and nested very large eddy simulation with the WRF model. J. Geophys. Res. Atmos., 124, 1370–1391, doi: https://doi.org/10.1029/2018JD029668.
Huang, Y. J., Y. P. Wang, L. L. Xue, et al., 2020: Comparison of three microphysics parameterization schemes in the WRF model for an extreme rainfall event in the coastal metropolitan city of Guangzhou, China. Atmos. Res., 240, 104939, doi: https://doi.org/10.1016/j.atmosres.2020.104939.
Iacono, M. J., J. S. Delamere, E. J. Mlawer, et al., 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res. Atmos., 113, D13103, doi: https://doi.org/10.1029/2008JD009944.
Kain, J. S., 2004: The Kain-Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170–181, doi: https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2.
Kang, S.-L., and G. H. Bryan, 2011: A large-eddy simulation study of moist convection initiation over heterogeneous surface fluxes. Mon. Wea. Rev., 139, 2901–2917, doi: https://doi.org/10.1175/MWR-D-10-05037.1.
Lazarus, S. M., C. M. Ciliberti, J. D. Horel, et al., 2002: Near-realtime applications of a mesoscale analysis system to complex terrain. Wea. Forecasting, 17, 971–1000, doi: https://doi.org/10.1175/1520-0434(2002)017<0971:NRTAOA>2.0.CO;2.
Li, C., Y. Deng, C. G. Cui, et al., 2020: Hydrometeor budget of the Meiyu frontal rainstorms associated with two different atmospheric circulation patterns. J. Geophys. Res. Atmos., 125, e2019JD031955, doi: https://doi.org/10.1029/2019JD031955.
Li, X., Z. X. Pu, and Z. Q. Gao, 2021: Effects of roll vortices on the evolution of Hurricane Harvey during landfall. J. Atmos. Sci., 18, 1847–1867, doi: https://doi.org/10.1175/JAS-D-20-0270.1.
Li, X. R., K. Fan, and E. T. Yu, 2018: A heavy rainfall event in autumn over Bei**g—Atmospheric circulation background and hindcast simulation using WRF. J. Meteor. Res., 32, 503–515, doi: https://doi.org/10.1007/s13351-018-7168-9.
Liao, Y. S., J. Li, X. F. Wang, et al., 2010: A meso-β scale analysis of the torrential rain event in **an in 18 July 2007. Acta Meteor. Sinica, 68, 944–956, doi: https://doi.org/10.11676/qxxb2010.89. (in Chinese)
Lim, K.-S. S., and S.-Y. Hong, 2010: Development of an effective double-moment cloud microphysics scheme with prognostic cloud condensation nuclei (CCN) for weather and climate models. Mon. Wea. Rev., 138, 1587–1612, doi: https://doi.org/10.1175/2009MWR2968.1.
Liu, S. N., and X. P. Cui, 2018: Diagnostic analysis of rate and efficiency of torrential rainfall associated with Bilis (2006). Chinese J. Atmos. Sci., 42, 192–208, doi: https://doi.org/10.3878/j.issn.1006-9895.1704.17148. (in Chinese)
Liu, Y., Z. M. Liang, and Y. P. Li, 2017: Observational and simulative study of a local severe precipitation event caused by a cold vortex over Northeast China. Adv. Meteor., 2017, 2764340, doi: https://doi.org/10.1155/2017/2764340.
Liu, Y. J., S. G. Miao, F. Hu, et al., 2018: Large eddy simulation of flow field over the **aohaituo Mountain division for the 24th Winter Olympic Games. Plateau Meteor., 37, 1388–1401. (in Chinese)
Lu, T. T., X. P. Cui, Q. L. Zou, et al., 2021: Atmospheric water budget associated with a local heavy precipitation event near the Central Urban Area of Bei**g Metropolitan Region. Atmos. Res., 260, 105600, doi: https://doi.org/10.1016/j.atmosres.2021.105600.
Mao, J. H., F. **, L. Yin, et al., 2018: A study of cloud microphysical processes associated with torrential rainfall event over Bei**g. J. Geophys. Res. Atmos., 123, 8768–8791, doi: https://doi.org/10.1029/2018JD028490.
Mao, Z., Z. P. Zhu, R. Y. Zhang, et al., 2022: The impact of different cloud microphysics parameterization schemes on the simulation of a heavy rainfall event over the Tibetan Plateau. J. Trop. Meteor., 38, 81–90. (in Chinese)
Morrison, H., M. D. Shupe, and J. A. Curry, 2003: Modeling clouds observed at SHEBA using a bulk microphysics parameterization implemented into a single-column model. J. Geophys. Res. Atmos., 108, 4255, doi: https://doi.org/10.1029/2002JD002229.
Morrison, H., G. Thompson, and V. Tatarskii, 2009: Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one-and two-moment schemes. Mon. Wea. Rev., 137, 991–1007, doi: https://doi.org/10.1175/2008MWR2556.1.
Naeger, A. R., B. A. Colle, and A. Molthan, 2017: Evaluation of cloud microphysical schemes for a warm frontal snowband during the GPM Cold Season Precipitation Experiment (GCPEx). Mon. Wea. Rev., 145, 4627–4650, doi: https://doi.org/10.1175/MWR-D-17-0081.1.
Ran, L. K., S. W. Li, Y. S. Zhou, et al., 2021: Observational analysis of the dynamic, thermal, and water vapor characteristics of the “7.20” extreme rainstorm event in Henan Province, 2021. Chinese J. Atmos. Sci., 45, 1366–1383. (in Chinese)
Rao, J., J. **e, Y. Cao, et al., 2022: Record flood-producing rainstorms of July 2021 and August 1975 in Henan of China: Comparative synoptic analysis using ERA5. J. Meteor. Res., 36, 809–823, doi: https://doi.org/10.1007/s13351-022-2066-6.
Rauber, R. M., L. S. Olthoff, M. K. Ramamurthy, et al., 2000: The relative importance of warm rain and melting processes in freezing precipitation events. J. Appl. Meteor. Climatol., 39, 1185–1195, doi: https://doi.org/10.1175/1520-0450(2000)039<1185:TRIOWR>2.0.CO;2.
Rutledge, S. A., and P. V. Hobbs, 1983: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. VIII: A model for the “seeder-feeder” process in warm-frontal rainbands. J. Atmos. Sci., 40, 1185–1206, doi: https://doi.org/10.1175/1520-0469(1983)040<1185:TMAMSA>2.0.CO;2.
Saunders, R. W., 1993: Note on the Advanced Microwave Sounding Unit. Bull. Amer. Meteor. Soc., 74, 2211–2212, doi: https://doi.org/10.1175/1520-0477-74.11.2211.
Shen, X. Y., N. Zhang, and X. F. Li, 2011: Effects of large-scale forcing and ice clouds on pre-summer heavy rainfall over southern China in June 2008: A partitioning analysis based on surface rainfall budget. Atmos. Res., 101, 155–163, doi: https://doi.org/10.1016/j.atmosres.2011.02.001.
Shi, R. L., Y. Yin, Q. Chen, et al., 2021: Numerical simulation of aerosol effects on the physical processes of hail formation in **njiang. Chinese J. Atmos. Sci., 45, 107–122. (in Chinese)
Shu, W. X., H. **ao, D. H. Fu, et al., 2022: Effects of cloud condensation nuclei concentration on the evolution of severe convective storms. Atmos. Res., 276, 106252, doi: https://doi.org/10.1016/j.atmosres.2022.106252.
Sinkevich, A. A., and T. W. Krauss, 2014: Changes in thunderstorm characteristics due to feeder cloud merging. Atmos. Res., 142, 124–132, doi: https://doi.org/10.1016/j.atmosres.2013.06.007.
Skamarock, W. C., J. B. Klemp, J. Dudhia, et al., 2008: A Description of the Advanced Research WRF Version 3. No. NCAR/TN-475+STR, University Corporation for Atmospheric Research, Boulder, 113 pp., doi: https://doi.org/10.5065/D68S4MVH.
Song, H.-J., and B.-J. Sohn, 2018: An evaluation of WRF microphysics schemes for simulating the warm-type heavy rain over the Korean Peninsula. Asia-Pac. J. Atmos. Sci., 54, 225–236, doi: https://doi.org/10.1007/s13143-018-0006-2.
Song, H.-J., B.-J. Sohn, S.-Y. Hong, et al., 2017: Idealized numerical experiments on the microphysical evolution of warm-type heavy rainfall. J. Geophys. Res. Atmos., 122, 1685–1699, doi: https://doi.org/10.1002/2016JD025637.
Stevens, B., C. Acquistapace, A. Hansen, et al., 2020: The added value of large-eddy and storm-resolving models for simulating clouds and precipitation. J. Meteor. Soc. Japan, 98, 395–435, doi: https://doi.org/10.2151/jmsj.2020-021.
Su, A. F., X. N. Lyu, L. M. Cui, et al., 2021: The basic observational analysis of “7.20” extreme rainstorm in Zhengzhou. Torr. Rain Dis., 40, 445–454, doi: https://doi.org/10.3969/j.issn.1004-9045.2021.05.001. (in Chinese)
Sun, Y., H. **ao, H. L. Yang, et al., 2021: Analysis of dynamic conditions and hydrometeor transport of Zhengzhou superheavy rainfall event on 20 July 2021 based on optical flow field of remote sensing data. Chinese J. Atmos. Sci., 45, 1384–1399. (in Chinese)
Tellman, B., J. A. Sullivan, C. Kuhn, et al., 2021: Satellite imaging reveals increased proportion of population exposed to floods. Nature, 596, 80–86, doi: https://doi.org/10.1038/s41586-021-03695-w.
Tewari, M., F. Chen, J. Dudhia, et al., 2022: Understanding the sensitivity of WRF hindcast of Bei**g extreme rainfall of 21 July 2012 to microphysics and model initial time. Atmos. Res., 271, 106085, doi: https://doi.org/10.1016/j.atmosres.2022.106085.
Van Weverberg, K., N. P. M. van Lipzig, and L. Delobbe, 2011: The impact of size distribution assumptions in a bulk one-moment microphysics scheme on simulated surface precipitation and storm dynamics during a low-topped supercell case in Belgium. Mon. Wea. Rev., 139, 1131–1147, doi: https://doi.org/10.1175/2010MWR3481.1.
Wang, G. L., D.-L. Zhang, and J. S. Sun, 2021: A multiscale analysis of a nocturnal extreme rainfall event of 14 July 2017 in Northeast China. Mon. Wea. Rev., 149, 173–187, doi: https://doi.org/10.1175/MWR-D-20-0232.1.
Wang, M. J., K. Zhao, M. Xue, et al., 2016: Precipitation microphysics characteristics of a Typhoon Matmo (2014) rainband after landfall over eastern China based on polarimetric radar observations. J. Geophys. Res. Atmos., 121, 12,415–12,433, doi: https://doi.org/10.1002/2016JD025307.
Wang, X. H., X. P. Cui, and S. F. Hao, 2019: Diagnostic and numerical study on surface rainfall processes associated with tropical cyclone Soudelor (2015) over the ocean. Chinese J. Atmos. Sci., 43, 417–436, doi: https://doi.org/10.8788/j.issn.1066-8955.1804.18118. (in Chinese)
Wang, Y. P., Y. J. Huang, and X. P. Cui, 2019: Surface rainfall processes during the genesis period of tropical cyclone Durian (2001). Adv. Atmos. Sci., 36, 451–464, doi: https://doi.org/10.1007/s00376-018-8157-8.
Wood, V. T., R. A. Brown, and S. V. Vasiloff, 2003: Improved detection using negative elevation angles for mountaintop WSR-88Ds. Part II: Simulations of the three radars covering Utah. Wea. Forecasting, 18, 393–403, doi: https://doi.org/10.1175/1520-0434(2003)18<393:IDUNEA>2.0.CO;2.
Wu, X. S., S. L. Guo, J. B. Yin, et al., 2018: On the event-based extreme precipitation across China: Time distribution patterns, trends, and return levels. J. Hydrol., 562, 305–317, doi: https://doi.org/10.1016/j.jhydrol.2018.05.028.
Wu, Y.-C., M.-J. Yang, and P.-H. Lin, 2020: Evolution of water budget and precipitation efficiency of mesoscale convective systems over the South China Sea. Terr. Atmos. Ocean. Sci., 31, 141–158, doi: https://doi.org/10.3319/TAO.2019.07.17.01.
Wu, Z. N., Y. H. Cui, and Y. Guo, 2021: A case study of flood risk evaluation based on emergy theory and cloud model in Anyang region, China. Water, 13, 420, doi: https://doi.org/10.3390/w13040420.
Xu, H. Y., G. Q. Zhai, and X. F. Li, 2018: Convective-stratiform rainfall separation of typhoon Fitow (2013): A 3D WRF modeling study. Terr. Atmos. Ocean. Sci., 29, 315–329, doi: https://doi.org/10.3319/TAO.2017.10.11.01.
Yang, H.-L., H. **ao, and C.-W. Guo, 2015: Structure and evolution of a squall line in northern China: A case study. Atmos. Res., 158–159, 139–157, doi: https://doi.org/10.1016/j.atmosres.2015.02.012.
Yin, J.-F., D.-H. Wang, Z.-M. Liang, et al., 2018: Numerical study of the role of microphysical latent heating and surface heat fluxes in a severe precipitation event in the warm sector over Southern China. Asia-Pac. J. Atmos. Sci., 54, 77–90, doi: https://doi.org/10.1007/s13143-017-0061-0.
Yin, J. F., H. D. Gu, X. D. Liang, et al., 2022: A possible dynamic mechanism for rapid production of the extreme hourly rainfall in Zhengzhou City on 20 July 2021. J. Meteor. Res., 36, 6–25, doi: https://doi.org/10.1007/s13351-022-1166-7.
Yue, C. J., S. W. Shou, and X. F. Li, 2009: Water vapor, cloud, and surface rainfall budgets associated with the landfall of Typhoon Krosa (2007): A two-dimensional cloud-resolving modeling study. Adv. Atmos. Sci., 26, 1198–1208, doi: https://doi.org/10.1007/s00376-009-8135-2.
Zhang, D. L., and R. A. Anthes, 1982: A high-resolution model of the planetary boundary layer—Sensitivity tests and comparisons with SESAME-79 data. J. Appl. Meteor., 21, 1594–1609, doi: https://doi.org/10.1175/1520-0450(1982)021<1594:AHRMOT>2.0.CO;2.
Zhang, G. S., J. Y. Mao, W. Hua, et al., 2023: Synergistic effect of the planetary-scale disturbance, typhoon and meso-β-scale convective vortex on the extremely intense rainstorm on 20 July 2021 in Zhengzhou. Adv. Atmos. Sci., 40, 428–446, doi: https://doi.org/10.1007/s00376-022-2189-9.
Zhang, Q., X. H. Gu, V. P. Singh, et al., 2017: Timing of floods in southeastern China: Seasonal properties and potential causes. J. Hydrol., 552, 732–744, doi: https://doi.org/10.1016/j.jhydrol.2017.07.039.
Zhang, Y., 2014: Spatial-temporal distribution characteristics of rainstorm days from 1961 to 2010 in Henan Province. Meteor. Environ. Sci., 37, 103–106, doi: https://doi.org/10.3969/j.issn.1673-7148.2014.01.017. (in Chinese)
Zhu, T., and D.-L. Zhang, 2006: Numerical simulation of Hurricane Bonnie (1998). Part II: Sensitivity to varying cloud microphysical processes. J. Atmos. Sci., 63, 109–126, doi: https://doi.org/10.1175/JAS3599.1.
Zhu, X. L., D. Li, W. Y. Zhou, et al., 2017: An idealized LES study of urban modification of moist convection. Quart. J. Roy. Meteor. Soc., 143, 3228–3243, doi: https://doi.org/10.1002/qj.3176.
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Supported by the National Key Research and Development Program of China (2016YFE0201900-02 and 2019YFC1510304) and National Natural Science Foundation of China (41575037).
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Shu, W., Fu, D., **ao, H. et al. Cloud Microphysical Processes and Atmospheric Water Budget during the 20 July 2021 Extreme Precipitation Event in Zhengzhou, China. J Meteorol Res 37, 722–742 (2023). https://doi.org/10.1007/s13351-023-2166-y
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DOI: https://doi.org/10.1007/s13351-023-2166-y