Skip to main content
Log in

Sensitivities of tornadogenesis to drop size distribution in a simulated subtropical supercell over eastern China

  • Published:
Advances in Atmospheric Sciences Aims and scope Submit manuscript

Abstract

Numerical simulations with the Advanced Regional Prediction System (ARPS) model were performed to investigate the impact of microphysical drop size distribution (DSD) on tornadogenesis in a subtropical supercell thunderstorm over Anhui Province, eastern China. Sensitivity experiments with different intercept parameters of rain, hail and snow DSDs in a Lin-type microphysics scheme were conducted. Results showed that rain and hail DSDs have a significant impact on the simulated storm both microphysically and dynamically. DSDs characterized by larger (smaller) intercepts have a smaller (larger) particle size and a lower (higher) mass-weighted mean fall velocity, and produce relatively stronger (weaker) and wider (narrower) cold pools through enhanced (reduced) rain evaporation and hail melting processes, which are then less favorable (favorable) for tornadogenesis. However, tornadogenesis will also be suppressed by the weakened mid-level mesocyclone when the cold pool is too weak. When compared to a U.S. Great Plain case, the two microphysical processes are more sensitive to DSD variations in the present case with a higher melting level and deeper warm layer. This suggests that DSD-related cloud microphysics has a stronger influence on tornadogenesis in supercells over the subtropics than the U.S. Great Plains.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Adlerman, E. J., K. K. Droegemeier, and R. Davies-Jones, 1999: A numerical simulation of cyclic mesocyclogenesis. J. Atmos. Sci., 56, 2045–2069.

    Article  Google Scholar 

  • 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 dualpolarized radar analysis. J. Atmos. Sci., 60, 354–365.

    Article  Google Scholar 

  • Caya, A., J. Sun, and C. Snyder, 2005: A comparison between the 4DVAR and the ensemble kalman filter techniques for radar data assimilation. Mon. Wea. Rev., 133, 3081–3094.

    Article  Google Scholar 

  • Chan, P. W., J. Wurman, C. M. Shun, P. Robinson, and K. Kosiba, 2012: Application of a method for the automatic detection and Ground-Based Velocity Track Display (GBVTD) analysis of a tornado crossing the Hong Kong International Airport. Atmospheric Research, 106, 18–29.

    Article  Google Scholar 

  • Chen, B. J., J. Yang, and J. P. Pu, 2013: Statistical characteristics of raindrop size distribution in the Meiyu season observed in Eastern China. J. Meteor. Soc. Japan, 91, 215–227, doi: 10.2151/jmsj.2013-208.

    Article  Google Scholar 

  • Davies-Jones, P. R., 1984: Streamwise vorticity: The origin of updraft rotation in supercell storms. J. Atmos. Sci., 41, 2991–3006.

    Article  Google Scholar 

  • Dawson, D. T., II, M. Xue, J. A. Milbrandt, M. K. Yau, and G. Zhang, 2007: Impact of multi-moment microphysics and model resolution on predicted cold pool and reflectivity intensity and structures in the Oklahoma tornadic supercell storms of 3 May 1999. Preprints, 22nd Conf. on Weather Analysis and Forecasting/18th Conf. on Numerical Weather Prediction, Salt Lake City, UT, Amer. Meteor. Soc., 10B. 2.

    Google Scholar 

  • Dawson, D. T., II, M. Xue, J. A. Milbrandt, and M. K. Yau, 2010: Comparison of evaporation and cold pool development between single-moment and multimoment bulk microphysics schemes in idealized simulations of tornadic thunderstorms. Mon. Wea. Rev., 138, 1152–1171.

    Article  Google Scholar 

  • Finley, C. A., W. R. Cotton, and R. A. Pielke, 2001: Numerical simulation of tornadogenesis in a high-precipitation supercell. Part I: Storm evolution and transition into a bow echo. J. Atmos. Sci., 58, 1597–1629.

    Article  Google Scholar 

  • Fujita, T. T., 1981: Tornadoes and downbursts in the context of generalized planetary scales. J. Atmos. Sci., 38, 1511–1534.

    Article  Google Scholar 

  • Gao, J. D., and M. Xue, 2008: An efficient dual-resolution approach for ensemble data assimilation and tests with simulated Doppler radar data. Mon. Wea. Rev., 136, 945–963.

    Article  Google Scholar 

  • Gao, W. H., F. S. Zhao, Z. J. Hu, and X. Feng, 2011: A twomoment bulk microphysics coupled with a mesoscale model WRF: Model description and first results. Adv. Atmos. Sci., 28(5), 1184–1200, doi: 10.1007/s00376-010-0087-z.

    Article  Google Scholar 

  • Grams, J. S., R. L. Thompson, D. V. Snively, J. A. Prentice, G. M. Hodges, and L. J. Reames, 2012: A climatology and comparison of parameters for significant tornado events in the United States. Wea. Forecasting, 27, 106–123.

    Article  Google Scholar 

  • Grasso, L. D., and W. R. Cotton, 1995: Numerical simulation of a tornado vortex. J. Atmos. Sci., 52, 1192–1203.

    Article  Google Scholar 

  • Gilmore, M. S., and L. J. Wicker, 1998: The influence of midtropospheric dryness on supercell morphology and evolution. Mon. Wea. Rev., 126, 943–958.

    Article  Google Scholar 

  • Gilmore, M. S., J. M. Straka, and E. N. Rasmussen, 2004a: Precipitation and evolution sensitivity in simulated deep convective storms: Comparisons between liquid-only and simple ice and liquid phase microphysics. Mon. Wea. Rev., 132, 1897–1916.

    Article  Google Scholar 

  • Gilmore, M. S., J. M. Straka, and E. N. Rasmussen, 2004b: Precipitation uncertainty due to variations in precipitation particle parameters within a simple microphysics scheme. Mon. Wea. Rev., 132, 2610–2627.

    Article  Google Scholar 

  • James, R. P., and P. M. Markowski, 2010: A numerical investigation of the effects of dry air aloft on deep convection. Mon. Wea. Rev., 138, 140–161.

    Article  Google Scholar 

  • Lee, B. D., and R. B. Wilhelmson, 1997: The numerical simulation of nonsupercell tornadogenesis. Part II: Evolution of a family of tornadoes along a weak outflow boundary. J. Atmos. Sci., 54, 2387–2415.

    Article  Google Scholar 

  • Lemon, L. R., and C. A. Dowsell III, 1979: Severe thunderstorm evolution and mesocyclone structure as related to tornadogenesis. Mon. Wea. Rev., 107, 1184–1197.

    Article  Google Scholar 

  • Lerach, D. G., B. J. Gaudet, and W. R. Cotton, 2008: Idealized simulations of aerosol influences on tornadogenesis. Geophys. Res. Lett., 35, L23806, doi: 10.1029/2008GL035617.

    Article  Google Scholar 

  • Lin, H.-M., P. K. Wang, and R. E. Schlesinger, 2005: Threedimensional nonhydrostatic simulations of summer thunderstorms in the humid subtropics versus High Plains. Atmospheric Research, 78, 103–145.

    Article  Google Scholar 

  • Lin, Y.-L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor., 22, 1065–1092.

    Article  Google Scholar 

  • Liu, X. L., and S. J. Niu, 2010: Numerical simulation of macroand micro-structures of intense convective clouds with a spectral bin microphysics model. Adv. Atmos. Sci., 27(5), 1078–1088, doi: 10.1007/s00376-010-8088-5.

    Article  Google Scholar 

  • Markowski, P. M., 2002: Hook echoes and rear-flank downdrafts: A review. Mon. Wea. Rev., 130, 852–876.

    Article  Google Scholar 

  • Markowski, P. M., and Y. P. Richardson, 2009: Tornadogenesis: Our current understanding, forecasting considerations, and questions to guide future research. Atmospheric Research, 93, 3–10.

    Article  Google Scholar 

  • Markowski, P. M., and Y. P. Richardson, 2010: Hazards associated with deep moist convection. Mesoscale Meteorology in Midlatitudes, John Wiley & Sons, Ltd, 273–292.

    Chapter  Google Scholar 

  • Markowski, P. M., J. M. Straka, and E. N. Rasmussen, 2002: Direct surface thermodynamic observations within the rear-Flank downdrafts of nontornadic and tornadic Supercells. Mon. Wea. Rev., 130, 1692–1721.

    Article  Google Scholar 

  • Markowski, P. M., Y. P. Richardson, E. N. Rasmussen, J. M. Straka, R. P. Davies-Jones, and R. J. Trapp, 2008: Vortex lines within low-level mesocyclones obtained from pseudodual-Doppler radar observations. Mon. Wea. Rev., 136, 3513–3535.

    Article  Google Scholar 

  • Milbrandt, J. A., and M. K. Yau, 2005: A multimoment bulk microphysics parameterization. Part I: Analysis of the role of the spectral shape parameter. J. Atmos. Sci., 62, 3051–3064.

    Article  Google Scholar 

  • Noda, A. T., and H. Niino, 2005: Genesis and structure of a major tornado in a numerical-simulated supercell storm: Importance of vertical vorticity in a gust front. J. Meteor. Soc. Japan, 1, 5–8.

    Google Scholar 

  • Rosenfeld, D., and C. W. Ulbrich, 2003: Cloud microphysical properties, processes, and rainfall estimation opportunities. Meteor. Monogr., 30, 237–258.

    Article  Google Scholar 

  • Rotunno, R., and J. B. Klemp, 1985: On the rotation and propagation of simulated supercell thunderstorms. J. Atmos. Sci., 42, 271–292.

    Article  Google Scholar 

  • Sánchez, J. L., and Coauthors, 2009: Characterization of hailstone size spectra in hailpad networks in France, Spain, and Argentina. Atmospheric Research, 93, 641–654.

    Article  Google Scholar 

  • Snook, N. A., and M. Xue, 2006: Sensitivity of tornadogenesis in very-high resolution numerical simulations to variations in model microphysical parameters. Preprint, 23rd Conference on Severe Local Storms, 16.4, St. Louis, MO, Amer. Meteor. Soc.

    Google Scholar 

  • Snook, N., and M. Xue, 2008: Effects of microphysical drop size distribution on tornadogenesis in supercell thunderstorms. Geophys. Res. Lett., 35, L24803, doi: 10.1029/2008GL035866.

    Article  Google Scholar 

  • Straka, J. M., E. N. Rasmussen, R. P. Davies-Jones, and P. M. Markowski, 2007: An observational and idealized numerical examination of low-level counter-rotating vortices in the rear flank of supercells. Electronic J. Severe Storms Meteor., 2(8), 1–22.

    Google Scholar 

  • van den Heever, S. C., and W. R. Cotton, 2004: The impact of hail size on simulated supercell storms. J. Atmos. Sci., 61, 1596–1609.

    Article  Google Scholar 

  • Wicker, L. J., and R. B. Wihelmson, 1995: Simulation and analysis of tornado development and decay within a three-dimensional supercell thunderstorm. J. Atmos. Sci., 52, 2675–2703.

    Article  Google Scholar 

  • Xie, B. G., Q. H. Zhang, and Y. Q. Wang, 2010: Observed characteristics of hail size in four regions in China during 1980–2005. J. Climate, 23, 4973–4982.

    Article  Google Scholar 

  • Xue, M., K. K. Droegemeier, and V. Wong, 2000: The Advanced Regional Prediction System (ARPS)—A multi-scale nonhydrostatic atmospheric simulation and prediction model. Part I: Model dynamics and verification. Meteor. Atmos. Phys., 75, 161–193.

    Article  Google Scholar 

  • Xue, M., and Coauthors, 2001: The Advanced Regional Prediction System (ARPS)—A multiscale nonhydrostatic atmospheric simulation and prediction tool. Part II: Model physics and applications. Meteor. Atmos. Phys., 76, 143–165.

    Article  Google Scholar 

  • Xue, M., D. H. Wang, J. D. Gao, K. Brewster, and K. K. Droegemeier, 2003: The Advanced Regional Prediction System (ARPS), storm-scale numerical weather prediction and data assimilation. Meteor. Atmos. Phys., 82, 139–170.

    Article  Google Scholar 

  • Yao, Y. Q., X. D. Yu, Y. Hao, J. Li, and Y. Y. Zheng, 2007: The contrastive analysis of synoptic situation and Doppler radar data for two intense tornado cases. Chinese J. Trop. Meteor., 23(5), 483–490. (in Chinese)

    Google Scholar 

  • Yu, X. D., Y. Y. Zheng, A. M. Zhang, Y. Q. Yao, and C. Fang, 2006: The detection of a severe tornado event in Anhui with China new generation weather radar. Plateau Meteorology, 25, 914–924. (in Chinese)

    Google Scholar 

  • Yu, X. D., Y. Y. Zheng, Y. F. Liao, Y. Q. Yao, and C. Fang, 2008: Observational investigation of a tornadic heavy precipitation supercell storm. Chinese J. Atmos. Sci., 32, 508–552. (in Chinese)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Baojun Chen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zheng, K., Chen, B. Sensitivities of tornadogenesis to drop size distribution in a simulated subtropical supercell over eastern China. Adv. Atmos. Sci. 31, 657–668 (2014). https://doi.org/10.1007/s00376-013-3143-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00376-013-3143-7

Key words

Navigation