Adlerman, E. J., and K. K. Droegemeier, 2002: The sensitivity of numerically simulated cyclic mesocyclogenesis to variations in model physical and computational parameters. Mon. Wea. Rev., 130, 2671−2691, https://doi.org/10.1175/1520-0493(2002)130<2671:TSONSC>2.0.CO;2.
Andrić, J., M. R. Kumjian, D. S. Zrnić, J. M. Straka, and V. M. Melnikov, 2013: Polarimetric signatures above the melting layer in winter storms: An observational and modeling study. J. Appl. Meteorol. Climatol., 52, 682−700, https://doi.org/10.1175/JAMC-D-12-028.1.
Bringi, V. N., and V. Chandrasekar, 2001: Polarimetric Doppler Weather Radar: Principles and Applications. Cambridge University Press, 636 pp.
Carlin, J. T., J. Gao, J. C. Snyder, and A. V. Ryzhkov, 2017: Assimilation of ZDR columns for improving the Spinup and forecast of convective storms in storm-scale models: Proof-of-concept experiments. Mon. Wea. Rev., 145(12), 5033−5057, https://doi.org/10.1175/MWR-D-17-0103.1.
Doviak, R. J., and D. S. Zrnić, 1993: Doppler Radar and Weather Observations. 2nd ed., Academic Press, 562 pp.
Doviak, R. J., V. Bringi, A. Ryzhkov, A. Zahrai, and D. S. Zrnić, 2000: Considerations for polarimetric upgrades to operational WSR-88D radars. J. Atmos. Ocean. Technol., 17, 257−278, https://doi.org/10.1175/1520-0426(2000)017<0257:CFPUTO>2.0.CO;2.
Ferrier, B. S., 1994: A double-moment multiple-phase four-class bulk ice scheme. Part I: Description. J. Atmos. Sci., 51, 249−280, https://doi.org/10.1175/1520-0469(1994)051<0249:ADMMPF>2.0.CO;2.
Ferrier, B. S., W.-K. Tao, and J. Simpson, 1995: A double-moment multiple- phase four-class bulk ice scheme. Part II: Simulations of convective storms in different large-scale environments and comparisons with other bulk parameterizations. J. Atmos. Sci., 52, 1001−1033, https://doi.org/10.1175/1520-0469(1995)052<1001:ADMMPF>2.0.CO;2.
Gao, J., and D. J. Stensrud, 2012: Assimilation of reflectivity data in a convective-scale, cycled 3DVAR framework with hydrometeor classification. J. Atmos. Sci., 69(3), 1054−1065, https://doi.org/10.1175/JAS-D-11-0162.1.
Jung, Y., G. Zhang, and M. Xue, 2008a: 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(6), 2228−2245, https://doi.org/10.1175/2007MWR2083.1.
Jung, Y., M. Xue, G. Zhang, and J. M. Straka, 2008b: Assimilation of simulated polarimetric radar data for a convective storm using the ensemble Kalman Filter. Part II: Impact of polarimetric data on storm analysis. Mon. Wea. Rev., 136(6), 2246−2260, https://doi.org/10.1175/2007MWR2288.1.
Jung, Y., M. Xue, and G. Zhang, 2010: Simulations of polarimetric radar signatures of a supercell storm using a two-moment bulk microphysics scheme. J. Appl. Meteorol. Climatol., 49(1), 146−163, https://doi.org/10.1175/2009JAMC2178.1.
Kumjian, M. R., and A. V. Ryzhkov, 2008: Polarimetric signatures in supercell thunderstorms. J. Appl. Meteor. Climatol., 47, 1940−1961, https://doi.org/10.1175/2007JAMC1874.1.
Li, X., and J. R. Mecikalski, 2010: Assimilation of the dual-polarization Doppler radar data for a convective storm with a warm-rain radar forward operator. J. Geophys. Res., 115, D16208, https://doi.org/10.1029/2009JD013666.
Li, X. L., J. R. Mecikalski, and D. Posselt, 2017: An ice-phase microphysics forward model and preliminary results of polarimetric radar data assimilation. Mon. Wea. Rev., 145, 683−708, https://doi.org/10.1175/MWR-D-16-0035.1.
Lin, Y.-L., R. D. Farley, and H. D. Orville, 1983: Bulk Parameterization of the Snow Field in a Cloud Model. Journal of Climate and Applied Meteorology, 22, 1065−1092, https://doi.org/10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2.
Mahale, V. N., G. Zhang, M. Xue, J. Gao, and H. D. Reeves, 2019: Variational retrieval of rain microphysics and related parameters from polarimetric radar data with a parameterized operator. J. Atmos. Ocean. Technol., 36(12), 2483−2500, https://doi.org/10.1175/JTECH-D-18-0212.1.
Matsui, T., B. Dolan, S. A. Rutledge, W. K. Tao, T. Iguchi, J. Barnum, and S. E. Lang, 2019: POLARRIS: A POLArimetric radar retrieval and instrument simulator. J. Geophys. Res., 124(8), 4634−4657, https://doi.org/10.1029/2018JD028317.
Milbrandt, J. A., and M. K. Yau, 2005a: A multimoment bulk microphysics parameterization. Part I: Analysis of the role of the spectral shape parameter. J. Atmos. Sci., 62, 3051−3064, https://doi.org/10.1175/JAS3534.1.
Milbrandt, J. A., and M. K. Yau, 2005b: A multimoment bulk microphysics parameterization. Part II: A proposed three-moment closure and scheme description. J. Atmos. Sci., 62, 3065−3081, https://doi.org/10.1175/JAS3535.1.
Morrison, H., J. A. Curry, and V. I. Khvorostyanov, 2005: A new double-moment microphysics parameterization for application in cloud and climate models. Part I: Description. J. Atmos. Sci., 62, 1665−1677, https://doi.org/10.1175/JAS3446.1.
Noda, A., and H. Niino, 2003: Critical grid size for simulating convective storms: A case study of the Del City supercell storm. Geophys. Res. Lett., 30, 1844, https://doi.org/10.1029/2003GL017498.
Pan, Y., M. Xue, and G. Ge, 2016: Incorporating diagnosed intercept parameters and the graupel category within the ARPS cloud analysis system for the initialization of double-moment microphysics with the assimilation of reflectivity data and testing with a squall line over south China Mon. Wea. Rev., 144, 371−392, https://doi.org/10.1175/MWR-D-15-0008.1.
Posselt, D. J., X. Li, S. A. Tushaus, and J. R. Mecikalski, 2015: Assimilation of dual-polarization radar observations in mixed- and ice-phase regions of convective storms: Information content and forward model errors. Mon. Wea. Rev., 143, 2611−2636, https://doi.org/10.1175/MWR-D-14-00347.1.
Putnam, B. J., M. Xue, Y. Jung, N. Snook, and G. F. Zhang, 2019: Ensemble Kalman Filter assimilation of polarimetric radar observations for the 20 May 2013 Oklahoma tornadic supercell case. Mon. Wea. Rev., 147, 2511−2533, https://doi.org/10.1175/MWR-D-18-0251.1.
Ryzhkov, A. V., and D. S. Zrnic, 2019: Radar Polarimetry for Weather Observations. Springer Press, 486 pp.
Ryzhkov, A., M. Pinsky, A. Pokrovsky, and A. Khain, 2011: Polarimetric radar observation operator for a cloud model with spectral microphysics. J. Appl. Meteorol. Climatol., 50(4), 873−894, https://doi.org/10.1175/2010JAMC2363.1.
Skamarock, W. C., and Coauthors, 2008: A description of the advanced research WRF version 3. NCAR Tech Note NCAR/TN-475+STR, 113 pp.
Smith, P. L. Jr., C. G. Myers, and H. D. Orville, 1975: Radar reflectivity factor calculations in numerical cloud models using bulk parameterization of precipitation. J. Appl. Meteorol. Climatol., 14, 1156−1165, https://doi.org/10.1175/1520-0450(1975)014<1156:RRFCIN>2.0.CO;2.
Sun, J., 2005: Initialization and numerical forecasting of a supercell storm observed during STEPS. Mon. Wea. Rev., 133, 793−813, https://doi.org/10.1175/MWR2887.1.
Thomas, G., J.-F. Mahfouf, and T. Montmerle, 2020: Toward a variational assimilation of polarimetric radar observations in a convective-scale numerical weather prediction (NWP) model. Atmospheric Measurement Techniques, 13, 2279−2298, https://doi.org/10.5194/amt-13-2279-2020.
Vivekanandan, J., W. M. Adams, and V. N. Bringi, 1991: Rigorous approach to polarimetric radar modeling of hydrometeor orientation distributions. J. Appl. Meteorol. Climatol., 30, 1053−1063, https://doi.org/10.1175/1520-0450(1991)030<1053:RATPRM>2.0.CO;2.
Waterman, P. C., 1965: Matrix formulation of electromagnetic scattering. Proceedings of the IEEE, 53, 805−812, https://doi.org/10.1109/PROC.1965.4058.
Weisman, M. L., and J. B. Klemp, 1982: The dependence of numerically simulated convective storms on vertical wind shear and buoyancy. Mon. Wea. Rev., 110, 504−520, https://doi.org/10.1175/1520-0493(1982)110<0504:TDONSC>2.0.CO;2.
Zhang, G., 2016: Weather Radar Polarimetry. CRC Press, 304 pp.
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(4), 830−841, https://doi.org/10.1109/36.917906.
Zhang, G., and Coauthors, 2019: Current status and future challenges of weather radar polarimetry: Bridging the gap between radar meteorology/hydrology/engineering and numerical weather prediction. Adv. Atmos. Sci., 36(6), 571−588, https://doi.org/10.1007/s00376-019-8172-4.