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An Evaluation of WRF Microphysics Schemes for Simulating the Warm-Type Heavy Rain over the Korean Peninsula

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Abstract

The Korean peninsula is the region of distinctly showing the heavy rain associated with relatively low storm height and small ice water content in the upper part of cloud system (i.e., so-called warm-type heavy rainfall). The satellite observations for the warm-type rain over Korea led to a conjecture that the cloud microphysics parameterization suitable for the continental deep convection may not work well for the warm-type heavy rainfall over the Korean peninsula. Therefore, there is a growing need to examine the performance of cloud microphysics schemes for simulating the warm-type heavy rain structures over the Korean peninsula. This study aims to evaluate the capabilities of eight microphysics schemes in the Weather Research and Forecasting (WRF) model how warm-type heavy rain structures can be simulated, in reference to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) reflectivity measurements. The results indicate that the WRF Double Moment 6-class (WDM6) scheme simulated best the vertical structure of warm-type heavy rain by virtue of a reasonable collision-coalescence process between liquid droplets and the smallest amount of snow. Nonetheless the WDM6 scheme appears to have limitations that need to be improved upon for a realistic reflectivity structure, in terms of the reflectivity slope below the melting layer, discontinuity in reflectivity profiles around the melting layer, and overestimation of upper-level reflectivity due to high graupel content.

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References

  • Albrecht, B. A., 1989: Aerosols, cloud microphysics, and fractional cloudiness. Science, 245, 1227–1231, doi:10.1126/science.245.4923.1227.

    Article  Google Scholar 

  • Bryan, G. H., and H. Morrison, 2012: Sensitivity of a simulated squall line to horizontal resolution and parameterization of microphysics. Mon. Wea. Rev., 140, 202–225, doi:10.1175/MWR-D-11-00046.1.

    Article  Google Scholar 

  • Caine, S., T. P. Lane, P. T. May, C. Jakob, S. T. Siems, M. J. Manton, and J. Pinto, 2013: Statistical assessment of tropical convection-permitting model simulations using a cell tracking algorithm. Mon. Wea. Rev., 141, 557–581, doi:10.1175/MWR-D-11-00274.1.

    Article  Google Scholar 

  • Cecil, D. J., and C. B. Blankenship, 2012: Toward a global climatology of severe hailstorms as estimated by satellite passive microwave imagers. J. Climate, 25, 687–703, doi:10.1175/JCLI-D-11-00130.1.

    Article  Google Scholar 

  • Chen, F., and J. Dudhia, 2001: Coupling an advanced land surfacehydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569–585, doi:10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2.

    Google Scholar 

  • Choi, H.-Y., J.-H. Ha, D.-K. Lee, and Y.-H. Kuo, 2011: Analysis and simulation of mesoscale convective systems accompanying heavy rainfall: The goyang case. Asia-Pac. J. Atmos. Sci., 47, 265–279, doi: 10.1007/s13143-011-0015-x.

    Article  Google Scholar 

  • Ham, S.-H., B.-J. Sohn, S. Kato, and M. Satoh, 2013: Vertical structure of ice cloud layers from CloudSat and CALIPSO measurements and comparison to NICAM simulations. J. Geophys. Res., 118, 9930–9947, doi:10.1002/jgrd.50582.

    Google Scholar 

  • Han, M., S. A. Braun, T. Matsui, and C. R. Williams, 2013: Evaluation of cloud microphysics schemes in simulations of a winter storm using radar and radiometer measurements. J. Geophys. Res., 118, 1401–1419, doi:10.1002/jgrd.50115.

    Google Scholar 

  • Han, J., and H.-L. Pan, 2006: Sensitivity of hurricane intensity forecast to convective momentum transport parameterization. Mon. Wea. Rev., 134, 664–674, doi:10.1175/MWR3090.1.

    Article  Google Scholar 

  • Han, J., and H.-L. Pan, 2011: Revision of convection and vertical diffusion schemes in the NCEP global gorecast system. Wea. Forecasting, 26, 520–533, doi:10.1175/WAF-D-10-05038.1.

    Article  Google Scholar 

  • Hashino, T., M. Satoh, Y. Hagihara, T. Kubota, T. Matsui, T. Nasuno, and H. Okamoto, 2013: Evaluating cloud microphysics from NICAM against CloudSat and CALIPSO. J. Geophys. Res., 118, 7273–7292, doi:10.1002/jgrd.50564.

    Google Scholar 

  • Hallett, J, and S. C. Mossop, 1974: Production of secondary ice particles during the riming process. Nature, 249, 26–28, doi:10.1038/249026a0.

    Article  Google Scholar 

  • Heymsfield, A. J., and S. C. Mossop, 1984: Temperature dependence of secondary ice crystal production during. Quart. J. Roy. Meteor. Soc., 110, 765–770, doi:10.1002/qj.49711046512.

    Article  Google Scholar 

  • Hong, S.-Y., 2004: Comparison of heavy rainfall mechanisms in Korea and the central US. J. Meteorol. Soc. Japan, 82, 1469–1479, doi:10.2151/jmsj.2004.1469.

    Article  Google Scholar 

  • Hong, S.-Y., and J.-O. J. Lim, 2006: The WRF single-moment 6-class microphysics scheme (WSM6). J. Korean Meteor. Soc., 42, 129–151.

    Google Scholar 

  • Hong, S.-Y., and J.-W. Lee, 2009: Assessment of the WRF model in reproducing a flash flood heavy rainfall event over Korea. Atmos, Res., 93, 818–831, doi:10.1016/j.atmosres.2009.03.015.

    Article  Google Scholar 

  • Hong, S.-Y., and M. Kanamitsu, 2014: Dynamical downscaling: Fundamental Issues from an NWP point of view and recommendations. Asia-Pac. J. Atmos. Sci., 50, 83–104, doi:10.1007/s13143-014-0029-2.

    Article  Google Scholar 

  • Hong, S.-Y., J. Dudhia, and S.-H. Chen, 2004: A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon. Wea. Rev., 132, 103–120, doi:10.1175/1520-0493 (2004)132<0103:ARATIM>2.0.CO;2.

    Article  Google Scholar 

  • 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:10.1175/MWR3199.1.

    Article  Google Scholar 

  • Hong, S.-Y., K.-S. S. Lim, J.-H. Kim, J.-O. J. Lim, and J. Dudhia, 2009: Sensitivity Study of Cloud-Resolving Convective Simulations with WRF using two bulk microphysical parameterizations: Ice-phase microphysics versus sedimentation effects. J. Appl. Meteor. Climatol., 48, 61–76, doi:10.1175/2008JAMC1960.1.

    Article  Google Scholar 

  • Hong, S.-Y., K.-S. S. Lim, Y.-H. Lee, J.-C. Ha, H.-W. Kim, S.-J. Ham, and J. Dudhia, 2010: Evaluation of the WRF double-moment 6-class microphysics scheme for precipitating convection. Adv. Meteor., 2010, 707253, doi:10.1155/2010/707253.

    Article  Google Scholar 

  • Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, doi:10.1029/2008JD009944

    Article  Google Scholar 

  • Jiménez, P. A., J. Dudhia, J. F. González-Rouco, J. Navarro, J. P. Montávez, and E. García-Bustamante, 2012: A revised scheme for the WRF surface layer formulation. Mon. Wea. Rev., 140, 898–918, doi: 10.1175/MWR-D-11-00056.1.

    Article  Google Scholar 

  • **, H.-G., H. Lee, J. Lkhamjav, and J.-J. Baik, 2017: A hail climatology in South Korea. Atmos. Res., 188, 90–99, doi:10.1016/j.atmosres.2016.12. 013.

    Article  Google Scholar 

  • Jung, W., and T.-Y. Lee, 2013: Formation and evolution of mesoscale convective systems that brought the heavy rainfall over Seoul on September 21, 2010. Asia-Pac. J. Atmos. Sci., 49, 635–647, doi:10. 1007/s13143-013-0056-4.

    Article  Google Scholar 

  • Kain, J. S., and Coauthors, 2008: Some practical considerations regarding horizontal resolution in the first generation of operational convectionallowing NWP. Wea. Forecasting, 23, 931–952, doi:10.1175/WAF-2007106.1.

    Article  Google Scholar 

  • Kim, J.-H., D.-B. Shin, and C. Kummerow, 2013: Impacts of a priori databases using six WRF microphysics schemes on passive microwave rainfall retrievals. J. Atmos. Oceanic Technol., 30, 2367–2381, doi: 10.1175/JTECH-D-12-00261.1.

    Article  Google Scholar 

  • Kim, J.-H., M.-L. Ou, J.-D. Park, K. R. Morris, M. R. Schwaller, and D. B. Wolff, 2014: Global Precipitation Measurement (GPM) Ground Validation (GV) prototype in the Korean peninsula. J. Atmos. Oceanic Technol., 31, 1902–1921, doi:10.1175/JTECH-D-13-00193.1.

    Article  Google Scholar 

  • Lang, S., W.-K. Tao, J. Simpson, R. Cifelli, S. Rutledge, W. Olson, and J. Halverson, 2007: Improving simulations of convective system from TRMM LBA: Easterly and westerly regimes. J. Atmos. Sci., 64, 1141–1164, doi:10.1175/JAS3879.1.

    Article  Google Scholar 

  • Lang, S., W.-K. Tao, X. Zeng, and Y. Li, 2011: Reducing the biases in simulated radar reflectivities from a bulk microphysics scheme: Tropical convective systems. J. Atmos. Sci., 68, 2306–2320, doi:10.1175/JAS-D-10-05000.1.

    Article  Google Scholar 

  • Lean, H. W., P. A. Clark, M. Dixon, N. M. Roberts, A. Fitch, R. Forbes, and C. Halliwell, 2008: Characteristics of high-resolution versions of the Met Office Unified Model for forecasting convection over the United Kingdom. Mon. Wea. Rev., 136, 3408–3424, doi:10.1175/2008-MWR2332.1.

    Article  Google Scholar 

  • Lee, J.-Y., W. Kim, and T.-Y. Lee, 2017: Physical and dynamic factors that drove the heavy rainfall event over the middle Korean peninsula on 26-27 July 2011. Asia-Pac. J. Atmos. Sci., 53, 101–120, doi:10.1007/s13143-017-0009-4.

    Article  Google Scholar 

  • Li, X., W.-K. Tao, T. Matsui, C. Liu, and H. Masunaga, 2010: Improving a spectral bin microphysical scheme using TRMM satellite observations. Quart. J. Roy. Meteor. Soc., 136, 382–399, doi:10.1002/qj.569.

    Google Scholar 

  • Lim, K.-S. S., and S.-Y. Hong, 2010: Development of an effective doublemoment cloud microphysics scheme with prognostic cloud condensation nuclei (CCN) for weather and climate models. Mon. Wea. Rev., 138, 1587–1612, doi:10.1175/2009MWR2968.1.

    Article  Google Scholar 

  • Lim, K.-S. S., S.-Y. Hong, J.-H. Yoon, and J. Han, 2014: Simulation of the summer monsoon rainfall over East Asia using the NCEP GFS cumulus parameterization at different horizontal resolutions. Wea. Forecasting, 29, 1143–1154, doi:10.1175/WAF-D-13-00143.1.

    Article  Google Scholar 

  • Mansell, E. R., C. L. Ziegler, and E. C. Bruning, 2010: Simulated electrification of a small thunderstorm with two-moment bulk microphysics. J. Atmos. Sci., 67, 171–194, doi:10.1175/2009JAS2965.1.

    Article  Google Scholar 

  • Min, K.-H., S. Choo, D. Lee, and G. Lee, 2015: Evaluation of WRF cloud microphysics schemes using radar observations. Wea. Forecasting, 30, 1571–1589, doi:10.1175/WAF-D-14-00095.1.

    Article  Google Scholar 

  • 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:10.1175/2008MWR2556.1.

    Article  Google Scholar 

  • Morrison, H., J. A. Milbrandt, G. H. Bryan, K. Ikeda, S. A. Tessendorf, and G. Thompson, 2015: Parameterization of cloud microphysics based on the prediction of bulk ice particle properties. Part II: case study comparisons with observations and other schemes. J. Atmos. Sci., 72, 312–339, doi:10.1175/JAS-D-14-0066.1.

    Google Scholar 

  • Mossop, S. C., 1976: Production of secondary ice particles during the growth of graupel by riming. Quart. J. Roy. Meteor. Soc., 102, 45–57, doi:10.1002/qj.49710243104.

    Article  Google Scholar 

  • Mossop, S. C., 1980: The mechanism of ice splinter production during riming. Geophys. Res. Lett., 7, 167–169, doi:10.1029/GL007i002p00167.

    Article  Google Scholar 

  • Mossop, S. C., 1985: Secondary ice particle production during rime growth: The effect of drop size distribution and rimer velocity. Quart. J. Roy. Meteor. Soc., 111, 1113–1124, doi:10.1002/qj.49711147012.

    Article  Google Scholar 

  • Mossop, S. C., J. L. Brownscombe, and G. J. Collins, 1974: The production of secondary ice particles during riming. Quart. J. Roy. Meteor. Soc., 100, 427–436, doi:10.1002/qj.49710042514.

    Article  Google Scholar 

  • Park, S., S.-H. Jung, and G. W. Lee, 2015: Cross-validation of TRMM PR reflectivity profiles using 3-D reflectivity composite from the groundbased radar network over the Korean peninsula. J. Hydrometeor., 16, 668–687, doi:10.1175/JHM-D-14-0092.1.

    Article  Google Scholar 

  • Roh, W., and M. Satoh, 2014: Evaluation of precipitating hydrometeor parameterizations in a single-moment bulk microphysics scheme for deep convective systems over the tropical central Pacific. J. Atmos. Sci., 71, 2654–2673, doi:10.1175/JAS-D-13-0252.1.

    Article  Google Scholar 

  • Ryu, G.-H., B.-J. Sohn, C. D. Kummerow, E.-K. Seo, and G. J. Tripoli, 2012: Rain rate characteristics over the Korean peninsula and improvement of the Goddard Profiling (GPROF) database for TMI rainfall retrievals. J. Appl. Meteor. Climatol., 51, 786–798, doi:10.1175/JAMCD-11-094.1.

    Article  Google Scholar 

  • Satoh, M., and Y. Kitao, 2013: Numerical examination of the diurnal variation of summer precipitation over southern China. Sci. Online Lett. Atmos., 9, 129–133, doi:10.2151/sola.2013-029.

    Google Scholar 

  • Satoh, M., T. Matsuno, H. Tomita, H. Miura, T. Nasuno, and S. Iga, 2008: Nonhydrostatic icosahedaral atmospheric model (NICAM) for global cloud resolving simulations. J. Comput. Phys., 227, 3486–3514, doi:10. 1016/j.jcp.2007.02.006.

    Article  Google Scholar 

  • Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, M. G. Duda, X.-Y. Huang, W. Wang, and J. G. Powers, 2008: A description of the Advanced Research WRF Version 3. NCAR Tech. Note TN-475_STR, USA, 113 pp. [Available online at http://www2.mmm.ucar.edu/wrf/users/docs/arw_v3.pdf

    Google Scholar 

  • Sohn, B.-J., H.-J. Han, and E.-K. Seo, 2010: Validation of satellite-based high-resolution rainfall products over the Korean peninsula using data from a dense rain gauge network. J. Appl. Meteor. Climatol., 49, 701–714, doi:10.1175/2009JAMC2266.1.

    Article  Google Scholar 

  • Sohn, B.-J., G.-H. Ryu, H.-J. Song, and M.-L. Oh, 2013: Characteristic features of warm-type rain producing heavy rainfall over the Korean peninsula inferred from TRMM measurements. Mon. Wea. Rev., 141, 3873–3888, doi:10.1175/MWR-D-13-00075.1.

    Article  Google Scholar 

  • Song, H.-J., and B.-J. Sohn, 2015: Two heavy rainfall types over the Korean peninsula in the humid East Asian summer environment: A satellite observation study. Mon. Wea. Rev., 143, 363–382, doi:10.1175/MWR-D-14-00184.1.

    Article  Google Scholar 

  • Song, H.-J., B.-J. Sohn, S.-Y. Hong, and T. Hashino, 2017: Idealized numerical experiments on the microphysical evolution of warm-type heavy rainfall. J. Geophys. Res., 122, 1685–1699, doi:10.1002/2016JD02563.

    Google Scholar 

  • Takahashi, T., T. Kawano, and M. Ishihara, 2015: Different precipitation mechanisms produce heavy rain with and without lightning in Japan. J. Meteorol. Soc. Japan., 93, 245–263, doi:10.2151/jmsj.2015-014.

    Article  Google Scholar 

  • Tao, W.-K., and Coauthors, 2003: Microphysics, radiation and surface processes in the Goddard Cumulus Ensemble (GCE) model. Meteorol. Atmos. Phys., 82, 97–137, doi:10.1007/s00703-001-0594-7.

    Article  Google Scholar 

  • Thompson, G., and T. Eidhammer, 2014: A study of aerosol impacts on clouds and precipitation development in a large winter cyclone. J. Atmos. Sci., 71, 3636–3658, doi:10.1175/JAS-D-13-0305.1.

    Article  Google Scholar 

  • Thompson, G., P. R. Field, R. M. Rasmussen, and W. D. Hall, 2008: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: Implementation of a new snow parameterization. Mon. Wea. Rev., 136, 5095–5115, doi:10.1175/2008MWR2387.1.

    Google Scholar 

  • Van Weverberg, K., A. M. Vogelmann, W. Lin, E. P. Luke, A. Cialella, P. Minnis, M. Khaiyer, E. R. Boer, and M. P. Jensen, 2013: The role of cloud microphysics parameterization in the simulation of mesoscale convective system clouds and precipitation in the tropical western pacific. J. Atmos. Sci., 70, 1104–1128, doi:10.1175/JAS-D-12-0104.1.

    Article  Google Scholar 

  • Yang, S., and S. W. Nesbitt, 2014: Statistical properties of precipitation as observed by the TRMM precipitation radar. Geophys. Res. Lett., 41, 5636–5643, doi:10.1002/2014GL060683.

    Article  Google Scholar 

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  1. School of Earth and Environmental Sciences, Seoul National University, Seoul, Korea

    Hwan-** Song & Byung-Ju Sohn

  2. School of Earth and Environmental Sciences, Seoul National University, NS80, Seoul, 08826, Korea

    Byung-Ju Sohn

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Song, HJ., Sohn, BJ. An Evaluation of WRF Microphysics Schemes for Simulating the Warm-Type Heavy Rain over the Korean Peninsula. Asia-Pacific J Atmos Sci 54, 225–236 (2018). https://doi.org/10.1007/s13143-018-0006-2

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