Abel, S. J., and I. A. Boutle, 2012: An improved representation of the raindrop size distribution for single-moment microphysics schemes. Quart. J. Roy. Meteor. Soc., 138, 2151–2162, https://doi.org/10.1002/qj.1949.

Ballard, S. P., Z. H. Li, D. Simonin, and J.-F. Caron, 2016: Performance of 4D-var NWP-based nowcasting of precipitation at the met office for summer 2012. Quart. J. Roy. Meteor. Soc., 142, 472–487, https://doi.org/10.1002/qj.2665.

Brown, B. R., M. M. Bell, and A. J. Frambach, 2016: Validation of simulated hurricane drop size distributions using polarimetric radar. Geophys. Res. Lett., 43, 910–917, https://doi.org/10.1002/2015GL067278.

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, https://doi.org/10.1175/MWR-D-11-00046.1.

Cintineo, R., J. A. Otkin, M. Xue, and F. Y. Kong, 2014: Evaluating the performance of planetary boundary layer and cloud microphysical parameterization schemes in convectionpermitting ensemble forecasts using synthetic GOES-13 satellite observations. Mon. Wea. Rev., 142, 163–182, https://doi.org/10.1175/MWR-D-13-00143.1.

Dawson, D. T., 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, https://doi.org/10.1175/2009MWR2956.1.

Dawson, D. T., L. J. Wicker, E. R. Mansell, Y. Jung, and M. Xue, 2013: Low-level polarimetric radar signatures in EnKF analyses and forecasts of the May 8, 2003 Oklahoma City tornadic supercell: Impact of multimoment microphysics and comparisons with observation. Advances in Meteorology, 2013, 818394, https://doi.org/10.1155/2013/818394.

Dawson, D. T., E. R. Mansell, Y. Jung, L. J. Wicker, M. R. Kumjian, and M. Xue, 2014: Low-level ZDR signatures in supercell forward flanks: The role of size sorting and melting of hail. J. Atmos. Sci., 71, 276–299, https://doi.org/10.1175/JASD-13-0118.1.

Field, P. R., A. J. Heymsfield, and A. Bansemer, 2007: Snow size distribution parameterization for midlatitude and tropical ice clouds. J. Atmos. Sci., 64, 4346–4365, https://doi.org/10.1175/2007JAS2344.1.

Field, P. R., R. J. Hogan, P. R. A. Brown, A. J. Illingworth, T. W. Choularton, and R. J. Cotton, 2005: Parametrization of iceparticle size distributions for mid-latitude stratiform cloud. Quart. J. Roy. Meteor. Soc., 131, 1997–2017, https://doi.org/10.1256/qj.04.134.

Goldenberg, S. B., S. G. Gopalakrishnan, V. Tallapragada, T. Quirino, F. Marks Jr., S. Trahan, X. J. Zhang, and R. Atlas, 2015: The 2012 triply nested, high-resolution operational version of the hurricane weather research and forecasting model (HWRF): Track and intensity forecast verifications. Wea. Forecasting, 30, 710–729, https://doi.org/10.1175/WAF-D-14-00098.1.

Hanley, K. E., R. S. Plant, T. H. M. Stein, R. J. Hogan, J. C. Nicol, H. W. Lean, C. Halliwell, and P. A. Clark, 2015: Mixinglength controls on high-resolution simulations of convective storms. Quart. J. Roy. Meteor. Soc., 141, 272–284, https://doi.org/10.1002/qj.2356.

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

Houze, R. A., Jr., 2010: Clouds in tropical cyclones. Mon. Wea. Rev., 138, 293–344, https://doi.org/10.1175/2009MWR2989.1.

Johnson, M., Y. Jung, D. T. Dawson II, and M. Xue, 2016: Comparison of simulated polarimetric signatures in idealized supercell storms using two-moment bulk microphysics schemes in WRF. Mon. Wea. Rev., 144, 971–996, https://doi.org/10.1175/MWR-D-15-0233.1.

Jung, Y., G. F. Zhang, and M. Xue, 2008: Assimilation of simulated polarimetric radar data for a convective storm using the ensemble Kalman filter. Part I: Observation operators for reflectivity and polarimetric variables. Mon. Wea. Rev., 136, 2228–2245, https://doi.org/10.1175/2007MWR2083.1.

Jung, Y., M. Xue, and G. F. Zhang, 2010: Simulations of polarimetric radar signatures of a supercell storm using a two-moment bulk microphysics scheme. Journal of Applied Meteorology and Climatology, 49, 146–163, https://doi.org/10.1175/2009JAMC2178.1.

Jung, Y., M. Xue, and M. J. Tong, 2012: Ensemble Kalman filter analyses of the 29–30 May 2004 Oklahoma tornadic thunderstorm using one-and two-moment bulk microphysics schemes, with verification against polarimetric radar data. Mon. Wea. Rev., 140, 1457–1475, https://doi.org/10.1175/MWR-D-11-00032.1.

Kim, D.-J., 2015: Center report from KMA-forecasting system operation & research. WGNE-30.

Lin, Y.-L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow field in a cloud model. J. Appl. Meteor., 22, 1065–1092, https://doi.org/10.1175/1520-0450 (1983)022<1065:BPOTSF>2.0.CO;2.

Liu, C. H., K. Ikeda, G. Thompson, R. Rasmussen, and J. Dudhia, 2011: High-resolution simulations of wintertime precipitation in the Colorado Headwaters region: Sensitivity to physics parameterizations. Mon. Wea. Rev., 139, 3533–3553, https://doi.org/10.1175/MWR-D-11-00009.1.

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, https://doi.org/10.1175/2009JAS2965.1.

McMillen, J. D., and W. J. Steenburgh, 2015: Impact of microphysics parameterizations on simulations of the 27 October 2010 Great Salt Lake-effect snowstorm.Wea. Forecasting, 30, 136–152, https://doi.org/10.1175/WAF-D-14-00060.1.

Milbrandt, J. A., and M. K. Yau, 2005: A multimoment bulk microphysics parameterization. Part II: A proposed threemoment closure and scheme description. J. Atmos. Sci., 62, 3065–3081, https://doi.org/10.1175/JAS3535.1.

Milbrandt, J. A., and M. K. Yau, 2006: A multimoment bulk microphysics parameterization. Part IV: Sensitivity experiments. J. Atmos. Sci., 63, 3137–3159, https://doi.org/10.1175/JAS3817.1.

Morrison, H., and J. Milbrandt, 2011: Comparison of two-moment bulk microphysics schemes in idealized supercell thunderstorm simulations. Mon. Wea. Rev., 139, 1103–1130, https://doi.org/10.1175/2010MWR3433.1.

Morrison, H., G. Thompson, and V. Tatarskii, 2009: Impact ofcloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of oneand two-moment schemes. Mon. Wea. Rev., 137, 991–1007, https://doi.org/10.1175/2008MWR2556.1.

Morrison, H., S. A. Tessendorf, K. Ikeda, and G. Thompson, 2012: Sensitivity of a simulated midlatitude squall line to parameterization of raindrop breakup. Mon. Wea. Rev., 140, 2437–2460, https://doi.org/10.1175/MWR-D-11-00283.1.

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, https://doi.org/10.1175/JAS-D-14-0066.1.

Nicol, J. C., R. J. Hogan, T. H. M. Stein, K. E. Hanley, P. A. Clark, C. E. Halliwell, H. W. Lean, and R. S. Plant, 2015: Convective updraught evaluation in high-resolution NWP simulations using single-Doppler radar measurements. Quart. J. Ror. Meteor. Soc., 141, 3177–3189, https://doi.org/10.1002/qj.2602.

Pan, Y. J., M. Xue, and G. Q. Ge, 2016: Incorporating diagnosed intercept parameters and the graupel category within the ARPS cloud analysis system for the initialization of double-moment microphysics: Testing with a squall line over South China. Mon. Wea. Rev., 144, 371–392, https://doi.org/10.1175/MWR-D-15-0008.1.

Park, H. S., A. V. Ryzhkov, D. S. Zrnic, and K.-E. Kim, 2009: The hydrometeor classification algorithm for the polarimetric WSR-88D: Description and application to an MCS. Wea. Forecasting, 24, 730–748, https://doi.org/10.1175/2008WAF2222205.1.

Park, J.-S., Y. H. Lee, M. Suk, K. Nam, Y. Jung, and J. Ko, 2015a: Evaluation of UM microphysics using dual-polarised radar simulator. Proceedings of the 37th Conference on Radar Meteorology, Norman, OK, American Meteorological Society.

Park, S., S.-H. Jung, and G. Lee, 2015b: Cross validation of TRMM PR reflectivity profiles using 3D reflectivity composite from the ground-based radar network over the Korean peninsula. Journal of Hydrometeorology, 16, 668–687, https://doi.org/10.1175/JHM-D-14-0092.1.

Potvin, C. K., and M. L. Flora, 2015: Sensitivity of idealized supercell simulations to horizontal grid spacing: Implications for warn-on-forecast. Mon. Wea. Rev., 143, 2998–3024, https://doi.org/10.1175/MWR-D-14-00416.1.

Putnam, B. J., M. Xue, Y. Jung, G. F. Zhang, and F. Y. Kong, 2017: Simulation of polarimetric radar variables from 2013 CAPS spring experiment storm-scale ensemble forecasts and evaluation of microphysics schemes. Mon. Wea. Rev., 145, 49–73, https://doi.org/10.1175/MWR-D-15-0415.1.

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, https://doi.org/10.1175/1520-0469 (1983)040<1185:TMAMSA>2.0.CO;2.

Straka, J. M., M. S. Gilmore, K. M. Kanak, and E. N. Rasmussen, 2005: A comparison of the conservation of number concentration for the continuous collection and vapor diffusion growth equations using one-and two-moment schemes. J. Appl. Meteor., 44, 1844–1849, https://doi.org/10.1175/JAM2314.1.

Tang, Y. M., H. W. Lean, and J. Bornemann, 2013: The benefits of the Met Office variable resolution NWP model for forecasting convection. Meteorological Applications, 20, 417–426, https://doi.org/10.1002/met.1300.

Tao, W.-K., and J. Simpson, 1993: Goddard cumulus ensemble model. Part I: Model description. TAO, 4, 35–72, https://doi. org/10.3319/TAO.1993.4.1.35(A).

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, https://doi.org/10.1175/2008MWR2387.1.

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, https://doi.org/10.1175/2010MWR3481.1.

Van Weverberg, K., A. M. Vogelmann, H. Morrison, and J. A. Milbrandt, 2012: Sensitivity of idealized squall-line simulations to the level of complexity used in two-moment bulk microphysics schemes. Mon. Wea. Rev., 140, 1883–1907, https://doi.org/10.1175/MWR-D-11-00120.1.

Verrelle, A., D. Ricard, and C. Lac, 2015: Sensitivity of highresolution idealized simulations of thunderstorms to horizontal resolution and turbulence parametrization. Quart. J. Roy. Meteor. Soc., 141, 433–448, https://doi.org/10.1002/qj.2363.

Wainwright, C. E., D. T. Dawson II, M. Xue, and G. F. Zhang, 2014: Diagnosing the intercept parameters of the exponential drop size distributions in a single-moment microphysics scheme and impact on supercell storm simulations. J. Appl. Meteor. Climatol., 53, 2072–2090, https://doi.org/10.1175/JAMC-D-13-0251.1.

Weisman, M. L., W. C. Skamarock, and J. B. Klemp, 1997: The resolution dependence of explicitly modeled convective systems. Mon. Wea. Rev., 125, 527–548, https://doi.org/10.1175/1520-0493(1997)125<0527:TRDOEM>2.0.CO;2.

Wilkinson, J. M., A. N. F. Porson, F. J. Bornemann, M. Weeks, P. R. Field, and A. P. Lock, 2013: Improved microphysical parametrization of drizzle and fog for operational forecasting using the Met Office Unified Model. Quart. J. Roy. Meteor. Soc., 139, 488–500, https://doi.org/10.1002/qj.1975.

Wilson, D. R., and S. P. Ballard, 1999: A microphysically based precipitation scheme for the UK meteorological office unified model. Quart. J. Roy. Meteor. Soc., 125, 1607–1636, https://doi.org/10.1002/qj.49712555707.

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.