Abstract
During the pre-summer rainy season, heavy rainfall occurs frequently in South China. Based on polarimetric radar observations, the microphysical characteristics and processes of convective features associated with extreme rainfall rates (ERCFs) are examined. In the regions with high ERCF occurrence frequency, sub-regional differences are found in the lightning flash rate (LFR) distributions. In the region with higher LFRs, the ERCFs have larger volumes of high reflectivity factor above the freezing level, corresponding to more active riming processes. In addition, these ERCFs are more organized and display larger spatial coverage, which may be related to the stronger low-level wind shear and higher terrain in the region. In the region with lower LFRs, the ERCFs have lower echo tops and lower-echo centroids. However, no clear differences of the most unstable convective available potential energy (MUCAPE) exist in the ERCFs in the regions with different LFR characteristics. Regardless of the LFRs, raindrop collisional coalescence is the main process for the growth of raindrops in the ERCFs. In the ERCFs within the region with lower LFRs, the main mechanism for the rapid increase of liquid water content with decreasing altitude below 4 km is through the warm-rain processes converting cloud drops to raindrops. However, in those with higher LFRs, the liquid water content generally decreases with decreasing altitude.
摘 要
华南前汛期强降雨频发. 基于双偏振雷达观测, 本文研究了具有极端降水率的对流系统 (ERCF) 的微观物理特征及过程. 在极端降水对流系统发生高频区, 闪电频率表现出明显的区域性分布差异特征. 在闪电频率较高的子区域, 极端降水对流系统在冻结层以上具有更大体积的强反射率因子, 对应更活跃的淞附过程. 此外, 该区域的极端降水对流系统表现出更强的对流组织性和更大的空间覆盖范围, 这与该地区更强的低层风切变和更高的地形有关. 在闪电频率较低的子区域, 极端降水对流系统的回波顶和回波质心的高度更低. 在上述两个不同闪电频率的子区域, 极端降水对流系统发生时对应的最不稳定的对流有效位能 (MUCAPE) 并没有显著差异. 无论闪电频率高低, 碰并过程是极端降水对流系统中雨滴生长的主要机制. 在闪电频率较低的子区域, 极端降水对流系统的液态水含量在4公里高度以下随着海拔高度降低而迅速增加, 其主要机制是通过暖雨过程将云滴转化为雨滴. 然而, 在闪电频率较高的子区域内, 极端降水对流系统的液态水含量通常随着海拔高度的降低而减少.
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References
Brauer, N. S., J. B. Basara, C. R. Homeyer, G. M. McFarquhar, and P. E. Kirstetter, 2020: Quantifying precipitation efficiency and drivers of excessive precipitation in post-landfall hurricane harvey. Journal of Hydrometeorology, 21, 433–452, https://doi.org/10.1175/JHM-D-19-0192.1.
Bringi, V. N., V. Chandrasekar, J. Hubbert, E. Gorgucci, W. L. Randeu, and M. Schoenhuber, 2003: Raindrop size distribution in different climatic regimes from disdrometer and dual-polarized radar analysis. J. Atmos. Sci., 60, 354–365, https://doi.org/10.1175/1520-0469(2003)060<0354:RSDIDC>2.0.CO;2.
Bringi, V. N., M. A. Rico-Ramirez, and M. Thurai, 2011: Rainfall estimation with an operational polarimetric C-band radar in the United Kingdom: Comparison with a gauge network and error analysis. Journal of Hydrometeorology, 12, 935–954, https://doi.org/10.1175/JHM-D-10-05013.1.
Carey, L. D., and S. A. Rutledge, 2000: The relationship between precipitation and lightning in tropical island convection: A C-band polarimetric radar study. Mon. Wea. Rev., 128, 2687–2710, https://doi.org/10.1175/1520-0493(2000)128<2687:TRBPAL>2.0.CO;2.
Chen, F. J., Y. F. Fu, and Y. J. Yang, 2019a: Regional variability of precipitation in tropical cyclones over the western north pacific revealed by the GPM dual-frequency precipitation radar and microwave imager. J. Geophys. Res., 124, 11 281–11 296, https://doi.org/10.1029/2019JD031075.
Chen, G., and Coauthors, 2019b: Microphysical characteristics of three convective events with intense rainfall observed by polarimetric radar and disdrometer in Eastern China. Remote Sensing, 11, 2004, https://doi.org/10.3390/rs11172004.
Chen, H. N., V. Chandrasekar, and R. Bechini, 2017: An improved dual-polarization radar rainfall algorithm (DROPS2.0): Application in NASA IFloodS field campaign. Journal of Hydrometeorology, 18, 917–937, https://doi.org/10.1175/JHM-D-16-0124.1.
Chen, Q., J. W. Fan, S. Hagos, W. I. Gustafson Jr., and L. K. Berg, 2015: Roles of wind shear at different vertical levels: Cloud system organization and properties. J. Geophys. Res., 120, 6551–6574, https://doi.org/10.1002/2015JD023253.
Chu, C.-M., and Y.-L. Lin, 2000: Effects of orography on the generation and propagation of mesoscale convective systems in a two-dimensional conditionally unstable flow. J. Atmos. Sci., 57, 3817–3837, https://doi.org/10.1175/1520-0469(2001)057<3817:EOOOTG>2.0.CO;2.
Cifelli, R., W. A. Petersen, L. D. Carey, S. A. Rutledge, and M. A. F. da Silva Dias, 2002: Radar observations of the kinematic, microphysical, and precipitation characteristics of two MCSs in TRMM LBA. J. Geophys. Res., 107, 8077, https://doi.org/10.1029/2000JD000264.
Coceal, O., and S. E. Belcher, 2004: A canopy model of mean winds through urban areas. Quart. J. Roy. Meteor. Soc., 130, 1349–1372, https://doi.org/10.1256/qj.03.40.
Deierling, W., W. A. Petersen, J. Latham, S. Ellis, and H. J. Christian, 2008: The relationship between lightning activity and ice fluxes in thunderstorms. J. Geophys. Res., 113, D15210, https://doi.org/10.1029/2007JD009700.
Ding, Y. H., C. Y. Li, and Y. J. Liu, 2004: Overview of the South China sea monsoon experiment. Adv. Atmos. Sci., 21, 343–360, https://doi.org/10.1007/BF02915563.
Dixon, M., 2015. Radx C++ software package for radial radar data, [Available from https://github.com/NCAR/lrose-core/tree/master/codebase/apps/Radx/src/Radx2Grid]
Dixon, P. G., and T. L. Mote, 2003: Patterns and causes of Atlanta’s urban heat island-initiated precipitation. J. Appl. Meteorol. Climatol., 42, 1273–1284, https://doi.org/10.1175/1520-0450(2003)042<1273:PACOAU>2.0.CO;2.
Dolan, B., S. A. Rutledge, S. Lim, V. Chandrasekar, and M. Thurai, 2013: A robust C-band hydrometeor identification algorithm and application to a long-term polarimetric radar dataset. J. Appl. Meteorol. Climatol., 52, 2162–2186, https://doi.org/10.1175/JAMC-D-12-0275.1.
Dolan, B., B. Fuchs, S. A. Rutledge, E. A. Barnes, and E. J. Thompson, 2018: Primary modes of global drop size distributions. J. Atmos. Sci., 75, 1453–1476, https://doi.org/10.1175/JAS-D-17-0242.1.
Doswell III, C. A., 1985: The operational meteorology of convective weather. Volume II. Storm scale analysis. NOAA technical memorandum ERL ESG 15, 240 pp.
Gauthier, M. L., W. A. Petersen, L. D. Carey, and H. J. Christian Jr., 2006: Relationship between cloud-to-ground lightning and precipitation ice mass: A radar study over Houston. Geophys. Res. Lett., 33, L20803, https://doi.org/10.1029/2006GL027244.
Goodman, S. J., D. E. Buechler, P. D. Wright, and W. D. Rust, 1988: Lightning and precipitation history of a microburst-producing storm. Geophys. Res. Lett., 15, 1185–1188, https://doi.org/10.1029/GL015i011p01185.
Hamada, A., Y. N. Takayabu, C. T. Liu, and E. J. Zipser, 2015: Weak linkage between the heaviest rainfall and tallest storms. Nature Communications, 6, 6213, https://doi.org/10.1038/ncomms7213.
Hersbach, H., and Coauthors, 2020: The ERA5 global reanalysis. Quart. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803.
Huang, H., and Coauthors, 2018: Quantitative precipitation estimation with operational polarimetric radar measurements in Southern China: A differential phase-based variational approach. J. Atmos. Oceanic Technol., 35, 1253–1271, https://doi.org/10.1175/JTECH-D-17-0142.1.
Huang, H., K. Zhao, G. F. Zhang, D. M. Hu, and Z. W. Yang, 2020: Optimized raindrop size distribution retrieval and quantitative rainfall estimation from polarimetric radar. J. Hydrol., 580, 124248, https://doi.org/10.1016/j.jhydrol.2019.124248.
Istok, M. J., and Coauthors, 2009: WSR-88D dual polarization initial operational capabilities. Preprints, 25th Conf. on International Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, Phoenix, AZ, Amer. Meteor. Soc.
Kumjian, M. R., and A. V. Ryzhkov, 2010: The impact of evaporation on polarimetric characteristics of rain: Theoretical model and practical implications. J. Appl. Meteorol. Climatol., 49, 1247–1267, https://doi.org/10.1175/2010JAMC2243.1.
Kumjian, M. R., and O. P. Prat, 2014: The impact of raindrop collisional processes on the polarimetric radar variables. J. Atmos. Sci., 71, 3052–3067, https://doi.org/10.1175/JAS-D-13-0357.1.
Li, F. Y., D. Rosa, W. D. Collins, and M. F. Wehner, 2012: “Super-parameterization”: A better way to simulate regional extreme precipitation. Journal of Advances in Modeling Earth Systems, 4, M04002, https://doi.org/10.1029/2011MS000106.
Liu, C. T., and E. J. Zipser, 2009: “Warm Rain” in the tropics: Seasonal and regional distributions based on 9 yr of TRMM data. J. Climate, 22, 767–779, https://doi.org/10.1175/2008JCLI2641.1.
Liu, C. T., and E. Zipser, 2013a: Regional variation of morphology of organized convection in the tropics and subtropics. J. Geophys. Res., 118, 453–466, https://doi.org/10.1029/2012JD018409.
Liu, C. T., and E. J. Zipser, 2013b: Why does radar reflectivity tend to increase downward toward the ocean surface, but decrease downward toward the land surface. J. Geophys. Res., 118, 135–148, https://doi.org/10.1029/2012JD018134.
Liu, C. T., D. J. Cecil, E. J. Zipser, K. Kronfeld, and R. Robertson, 2012: Relationships between lightning flash rates and radar reflectivity vertical structures in thunderstorms over the tropics and subtropics. J. Geophys. Res., 117, D06212, https://doi.org/10.1029/2011JD017123.
May, R., and Z. Bruick, 2019: MetPy: An community-driven, open-source python toolkit for meteorology. Preprints, American Geophysical Union Fall Meeting 2019, NS21A-16.
McKnight, P. E., and J. Najab, 2010: Mann-whitney U test. The Corsini Encyclopedia of Psychology, 4th ed., I. B. Weiner and W. E. Craighead, Eds., John Wiley & Sons, Inc., 1, https://doi.org/10.1002/9780470479216.corpsy0524.
Naccarato, K. P., M. M. F. Saba, C. Schumann, O. Pinto, C. Medeiros, and S. Heckman, 2013: Waveform analysis of cloud-to-ground flashes as detected by fast e-field antennas and lightning location systems: On the way to precisely estimate the stroke peak current. Preprints, 2013 International Symposium on Lightning Protection, Belo Horizonte, IEEE, 57–61, https://doi.org/10.1109/SIPDA.2013.6729196.
Nielsen, E. R., and R. S. Schumacher, 2020: Dynamical mechanisms supporting extreme rainfall accumulations in the houston “Tax Day” 2016 Flood. Mon. Wea. Rev., 148, 83–109, https://doi.org/10.1175/MWR-D-19-0206.1.
Petersen, W. A., and S. A. Rutledge, 1998: On the relationship between cloud-to-ground lightning and convective rainfall. J. Geophys. Res., 103, 14 025–14 040, https://doi.org/10.1029/97JD02064.
Piao, S. L., and Coauthors, 2010: The impacts of climate change on water resources and agriculture in China. Nature, 467, 43–51, https://doi.org/10.1038/nature09364.
Saunders, C. P. R., 1993: A review of thunderstorm electrification processes. J. Appl. Meteorol. Climatol., 32, 642–655, https://doi.org/10.1175/1520-0450(1993)032<0642:AROTEP>2.0.CO;2.
Steiner, M., R. A. Houze Jr., and S. E. Yuter, 1995: Climatological characterization of three-dimensional storm structure from operational radar and rain gauge data. J. Appl. Meteorol. Climatol., 34, 1978–2007, https://doi.org/10.1175/1520-0450(1995)034<1978:CCOTDS>2.0.CO;2.
Sun, J. Z., 2005: Initialization and numerical forecasting of a super-cell storm observed during STEPS. Mon. Wea. Rev., 133, 793–813, https://doi.org/10.1175/MWR2887.1.
Sun, X. Y., and Coauthors, 2021: On the localized extreme rainfall over the great bay area in South China with complex topography and strong UHI effects. Mon. Wea. Rev., 149, 2777–2801, https://doi.org/10.1175/MWR-D-21-0004.1.
Takahashi, T., T. Kawano, and M. Ishihara, 2015: Different precipitation mechanisms produce heavy rain with and without lightning in Japan. J. Meteor. Soc. Japan, 93, 245–263, https://doi.org/10.2151/jmsj.2015-014.
Vincent, B. R., L. D. Carey, D. Schneider, K. Keeter, and R. Gonski, 2003: Using WSR-88D reflectivity data for the prediction of cloud-to-ground lightning: A central North Carolina study. Natl. Wea. Dig, 27, 35–44.
Vitale, J. D., and T. Ryan, 2013: Operational recognition of high precipitation efficiency and low-echo-centroid convection. Journal of Operational Meteorology, 1, 128–143, https://doi.org/10.15191/nwajom.2013.0112.
Wang, M. J., K. Zhao, W.-C. Lee, and F. Q. Zhang, 2018: Micro-physical and kinematic structure of convective-scale elements in the inner rainband of typhoon matmo (2014) after landfall. J. Geophys. Res., 123, 6549–6564, https://doi.org/10.1029/2018JD028578.
Wu, P., B. K. Xi, X. Q. Dong, and Z. B. Zhang, 2018: Evaluation of autoconversion and accretion enhancement factors in general circulation model warm-rain parameterizations using ground-based measurements over the Azores. Atmospheric Chemistry and Physics, 18, 17 405–17 420, https://doi.org/10.5194/acp-18-17405-2018.
Xu, W. X., and E. J. Zipser, 2012: Properties of deep convection in tropical continental, monsoon, and oceanic rainfall regimes. Geophys. Res. Lett., 39, L07802, https://doi.org/10.1029/2012GL051242.
Xu, W. X., E. J. Zipser, and C. T. Liu, 2009: Rainfall characteristics and convective properties of Mei-Yu precipitation systems over South China, Taiwan, and the South China Sea. Part I: TRMM observations. Mon. Wea. Rev., 137, 4261–4275, https://doi.org/10.1175/2009MWR2982.1.
Zhang, G., J. Vivekanandan, and E. Brandes, 2001: A method for estimating rain rate and drop size distribution from polarimetric radar measurements. IEEE Trans. Geosci. Remote Sens., 39, 830–841, https://doi.org/10.1109/36.917906.
Acknowledgements
The authors would like to thank the scientists and engineers working on Guangzhou S-POL, the south-China ENTLS, the ERA5 reanalysis, and the DMSP/OLS nighttime light dataset. The DMSP/OLS nighttime light dataset can be downloaded at https://www.ngdc.noaa.gov/eog/dmsp/downloadV4composites.html. The extreme-rainfall convective feature data-set used in this work is available at https://doi.org/10.5281/zenodo.6331267. This work is primarily supported by the National Natural Science Foundation of China (Grant Nos. 42025501, 41905019, and 61827901) and the National Key Research and Development Program of China (Grant 2018YFC1506404 and Grant 2017YFC1501703). The authors also thank Dr. Haonan CHEN (CSU) and Prof. Anning HUANG (NJU) for their suggestions on this work.
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Article Highlights
• Clear differences in microphysics of the extreme-rainfall convective features found in regions with different lighting flash rates.
• Stronger low-level wind shear and higher terrain may favor the organization and ice processes of the extreme-rainfall convection.
This paper is a contribution to the special issue on the 14th International Conference on Mesoscale Convective Systems and High-Impact Weather.
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Huang, H., Zhao, K., Chan, J.C.L. et al. Microphysical Characteristics of Extreme-Rainfall Convection over the Pearl River Delta Region, South China from Polarimetric Radar Data during the Pre-summer Rainy Season. Adv. Atmos. Sci. 40, 874–886 (2023). https://doi.org/10.1007/s00376-022-1319-8
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DOI: https://doi.org/10.1007/s00376-022-1319-8