Parameterization of cloud microphysics based on the prediction of bulk ice particle properties. Part I: Scheme description and idealized tests

Journal of the Atmospheric Sciences

Volumn 72, Issue 1, 2015, Pages 287-311

  Morrison, Hugh ^a   Milbrandt, Jason A ^b  

^a NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

^b ENVIRONMENT CANADA   (Canada)

Author keywords

Cloud microphysics; Cloud parameterizations

Indexed keywords

DEGREES OF FREEDOM (MECHANICS); PARAMETERIZATION; STORMS;

4 DEGREES OF FREEDOM; BULK MICROPHYSICS; CLOUD MICROPHYSICS; CLOUD PARAMETERIZATIONS; IDEALIZED MODELS; PARTICLE CHARACTERISTICS; PARTICLE PROPERTIES; SENSITIVITY TESTS;

ICE;

CLOUD MICROPHYSICS; ICE; MIXING RATIO; PARAMETERIZATION; PHYSICAL PROPERTY; PRECIPITATION (CLIMATOLOGY); PREDICTION; RIME;

EID: 84920569831     PISSN: 00224928     EISSN: 15200469     Source Type: Journal    
DOI: 10.1175/JAS-D-14-0065.1     Document Type: Article

References (105)

1. Adams-Selin, R. D., S. C. van den Heever, and R. H. Johnson, 2013: Impacts of graupel parameterization schemes on idealized bow echo simulations. Mon. Wea. Rev., 141, 3735-3756, doi:10.1175/MWR-D-12-00343.1.
2. Ansmann, A., and Coauthors, 2009: Evolution of the ice phase in tropical altocumulus: SAMUM lidar observations over Cape Verde. J. Geophys. Res., 114, D17208, doi:10.1029/2008JD011659.
3. Barklie, R. H. D., and N. R. Gokhale, 1959: The freezing of supercooled water drops. Alberta hail, 1958, and related studies, McGill University Stormy Weather Group Sci. Rep. MW-30, Part III, 43-64.
4. Beard, K. V., 1976: Terminal velocity and shape of cloud and precipitation drops aloft. J. Atmos. Sci., 33, 851-864, doi:10.1175/1520-0469(1976)033<0851:TVASOC>2.0.CO;2.
5. Beheng, K. D., 1994: A parameterization of warm cloud microphysical conversion processes. Atmos. Res., 33, 193-206, doi:10.1016/0169-8095(94)90020-5.
6. Berry, E., and R. Reinhardt, 1974: An analysis of cloud drop growth by collection: Part II. Single initial distributions. J. Atmos. Sci., 31, 1825-1831, doi:10.1175/1520-0469(1974)031<1825:AAOCDG>2.0.CO;2.
7. Bigg, E. K., 1953: The supercooling of water. Proc. Phys. Soc., 66B, 688-694, doi:10.1088/0370-1301/66/8/309.
8. Biggerstaff, M. I., and R. A. Houze, 1991: Kinematic and precipitation structure of the 10-11 June 1985 squall line. Mon. Wea. Rev., 119, 3034-3065, doi:10.1175/1520-0493(1991)119<3034:KAPSOT>2.0.CO;2.
9. Biggerstaff, M. I., and R. A. Houze, 1993: Kinematics and microphysics of the transition zone of the 10-11 June 1985 squall line. J. Atmos. Sci., 50, 3091-3110, doi:10.1175/1520-0469(1993)050<3091:KAMOTT>2.0.CO;2.
10. Braun, S. A., and R. A. Houze, 1994: The transition zone and secondary maximum of radar reflectivity behind a midlatitude squall line: Results retrieved fromDoppler radar data. J. Atmos. Sci., 51, 2733-2755, doi:10.1175/1520-0469(1994)051<2733:TTZASM>2.0.CO;2.
11. Brown, P. R. A., and P. N. Francis, 1995: Improved measurements of the ice water content in cirrus using a total water probe. J. Atmos. Oceanic Technol., 12, 410-414, doi:10.1175/1520-0426(1995)012<0410:IMOTIW>2.0.CO;2.
12. Bryan, G., 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.
13. Cao, Q., G. Zhang, E. Brandes, T. Schuur, A. Ryzhkov, and K. Ikeda, 2008: Analysis of video disdrometer and polarimetric radar data to characterize rain microphysics in Oklahoma. J. Appl. Meteor. Climatol., 47, 2238-2255, doi:10.1175/2008JAMC1732.1.
14. Cober, S. G., and R. List, 1993: Measurements of the heat and mass transfer parameters characterizing conical graupel growth. J. Atmos. Sci., 50, 1591-1609, doi:10.1175/1520-0469(1993)050<1591:MOTHAM>2.0.CO;2.
15. Cohard, J.-M., and J.-P. Pinty, 2000: A comprehensive twomoment warm microphysical bulk scheme. I: Description and tests. Quart. J. Roy. Meteor. Soc., 126, 1815-1842, doi:10.1256/smsqj.56613.
16. Cohen, C., and E. W. McCaul Jr., 2006: The sensitivity of simulated convective storms to variations in prescribed single-moment microphysics parameters that describe particle distributions, sizes, and numbers. Mon. Wea. Rev., 134, 2547-2565, doi:10.1175/MWR3195.1.
17. Colle, B. A., M. F. Garvert, J. B. Wolfe, C. F. Mass, and C. P. Woods, 2005: The 13-14 December 2001 IMPROVE-2 event. Part III: Simulated microphysical budgets and sensitivity studies. J. Atmos. Sci., 62, 3535-3558, doi:10.1175/JAS3552.1.
18. Connolly, P. J., T. W. Choularton, M. W. Gallagher, K. N. Bower, M. J. Flynn, and J. A. Whiteway, 2006: Cloud-resolving simulations of intense tropical Hector thunderstorms: Implications for aerosol-cloud interactions. Quart. J. Roy. Meteor. Soc., 132, 3079-3106, doi:10.1256/qj.05.86.
19. Cooper, W. A., 1986: Ice initiation in natural clouds. Precipitation Enhancement-A Scientific Challenge, Meteor. Monogr., No. 43, Amer. Meteor. Soc., 29-32.
20. 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 multi-moment bulk microhysics schemes in idealized simulations of tornadic thunderstorms. Mon. Wea. Rev., 138, 1152-1171, doi:10.1175/2009MWR2956.1.
21. de Boer, G., H. Morrison, M. D. Shupe, and R. Hildner, 2011: Evidence of liquid dependent ice nucleation in high-latitude stratiform clouds from surface remote sensors. Geophys. Res. Lett., 38, L01803, doi:10.1029/2010GL046016.
22. Ferrier, B. S., 1994: A double-moment multiple-phase four-class bulk ice scheme. Part I:Description. J. Atmos. Sci., 51, 249-280, doi:10.1175/1520-0469(1994)051<0249:ADMMPF>2.0.CO;2.
23. Field, P. R., A. J. Heymsfield, A. Bansemer, and C. H. Twohy, 2008: Determination of the combined ventilation factor and capacitance for ice crystal aggregates in airborne observations in a tropical anvil cloud. J. Atmos. Sci., 65, 376-391, doi:10.1175/2007JAS2391.1.
24. Frick, C., A. Seifert, and H. Wernli, 2013: A bulk parameterization of melting snowflakes with explicit water fraction for the COSMO model. Geosci. Model Dev., 6, 1925-1939, doi:10.5194/gmd-6-1925-2013.
25. Geresdi, I., 1998: Idealized simulation of the Colorado hailstorm case: Comparison of bulk and detailed microphysics. Atmos. Res., 45, 237-252, doi:10.1016/S0169-8095(97)00079-3.
26. Gilmore, M. S., J. M. Straka, and E. N. Rasmussen, 2004: Precipitation uncertainty due to variations in precipitation particle parameters within a simple microphysics scheme. Mon. Wea. Rev., 132, 2610-2627, doi:10.1175/MWR2810.1.
27. Grabowski, W. W., 2006: Indirect impact of atmospheric aerosols in idealized simulations of convective-radiative equilibrium. J. Climate, 19, 4664-4682, doi:10.1175/JCLI3857.1.
28. Grabowski, W. W., and H. Morrison, 2008: Toward the mitigation of spurious cloud-edge supersaturation in cloud models. Mon. Wea. Rev., 136, 1224-1234, doi:10.1175/2007MWR2283.1.
29. Gunn, R., and G. D. Kinzer, 1949: The terminal velocity of fall for water droplets in stagnant air. J. Meteor., 6, 243-244, doi:10.1175/1520-0469(1949)006<0243:TTVOFF>2.0.CO;2.
30. Hallett, J., and S. C. Mossop, 1974: Production of secondary ice particles during the riming process. Nature, 249, 26-28, doi:10.1038/249026a0.
31. Harrington, J. Y., K. Sulia, and H. Morrison, 2013a: A method for adaptive habit prediction in bulk microphysical models. Part I: Theoretical development. J. Atmos. Sci., 70, 349-364, doi:10.1175/JAS-D-12-040.1.
32. Harrington, J. Y., K. Sulia, and H. Morrison, 2013b: A method for adaptive habit prediction in bulk microphysical models. Part II: Parcel model corroboration. J. Atmos. Sci., 70, 365-376, doi:10.1175/JAS-D-12-0152.1.
33. Hashino, T., and G. J. Tripoli, 2007: The Spectral Ice Habit Prediction System (SHIPS). Part I: Model description and simulation of the vapor deposition process. J. Atmos. Sci., 64, 2210-2237, doi:10.1175/JAS3963.1.
34. Heymsfield, A. J., 1982: A comparative study of the rates of development of potential graupel and hail embryos in High Plains storms. J. Atmos. Sci., 39, 2867-2897, doi:10.1175/1520-0469(1982)039<2867:ACSOTR>2.0.CO;2.
35. Heymsfield, A. J., 2003: Properties of tropical and midlatitude ice cloud particle ensembles. Part II: Applications for mesoscale and climate models. J. Atmos. Sci., 60, 2592-2611, doi:10.1175/1520-0469(2003)060<2592:POTAMI>2.0.CO;2.
36. Heymsfield, A. J., A. Bansemer, and C. H. Twohy, 2007: Refinements to ice particle mass dimensional and terminal velocity relationships for ice clouds. Part I: Temperature dependence. J. Atmos. Sci., 64, 1047-1067, doi:10.1175/JAS3890.1.
37. Houze, R. A., M. I. Biggerstaff, S. A. Rutledge, and B. F. Smull, 1989: Interpretation of Doppler weather radar displays of midlatitude mesoscale convective systems. Bull. Amer. Meteor. Soc., 70, 608-619, doi:10.1175/1520-0477(1989)070<0608:IODWRD>2.0.CO;2.
38. Jarecka, D., W. W. Grabowski, H. Morrison, and H. Pawlowska, 2013: Homogeneity of the subgrid-scale turbulent mixing in large-eddy simulation of shallow convection. J. Atmos. Sci., 70, 2751-2767, doi:10.1175/JAS-D-13-042.1.
39. Kessler, E., 1969: On the Distribution and Continuity of Water Substance in Atmosphere Circulations. Meteor. Monogr., No. 32, Amer. Meteor. Soc., 84 pp.
40. Khain, A., A. Pokrovsky, M. Pinsky, A. Seifert, and V. Phillips, 2004: Simulation of effects of atmospheric aerosols on deep turbulent convective clouds using a spectral microphysics mixed-phase cumulus cloud model. Part I: Model description and possible application. J. Atmos. Sci., 61, 2963-2982, doi:10.1175/JAS-3350.1.
41. Khairoutdinov, M. F., and Y. Kogan, 2000: A new cloud physics parameterization in a large-eddy simulation model of marine stratocumulus. Mon. Wea. Rev., 128, 229-243, doi:10.1175/1520-0493(2000)128<0229:ANCPPI>2.0.CO;2.
42. Khvorostyanov, V. I., and J. A. Curry, 2002: Terminal velocities of droplets and crystals: Power laws with continuous parameters over the size spectrum. J. Atmos. Sci., 59, 1872-1884, doi:10.1175/1520-0469(2002)059<1872:TVODAC>2.0.CO;2.
43. Koenig, L. R., and F. W. Murray, 1976: Ice-bearing cumulus cloud evolution: Numerical simulation and general comparison against observations. J. Appl. Meteor., 15, 747-762, doi:10.1175/1520-0450(1976)015<0747:IBCCEN>2.0.CO;2.
44. Kogan, Y. L., and A. Belochitski, 2012: Parameterization of cloud microphysics based on full integral moments. J. Atmos. Sci., 69, 2229-2242, doi:10.1175/JAS-D-11-0268.1.
45. Lang, S., W.-K. Tao, and X. Zeng, 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.
46. Lebo, Z., and J. H. Seinfeld, 2011: Theoretical basis for convective invigoration due to increased aerosol concentration. Atmos. Chem. Phys., 11, 5407-5429, doi:10.5194/acp-11-5407-2011.
47. Lim, K.-S. S., and S.-Y. Hong, 2010: Development of an effective double-moment 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.
48. Lin, Y., and B. A. Colle, 2011: A new bulk microphysical scheme that includes riming intensity and temperature-dependent ice characteristics. Mon. Wea. Rev., 139, 1013-1035, doi:10.1175/2010MWR3293.1.
49. Lin, Y., L. J. Donner, and B. A. Colle, 2011: Parameterization of riming intensity and its impact on ice fall speed using ARM data. Mon. Wea. Rev., 139, 1036-1047, doi:10.1175/2010MWR3299.1.
50. 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, doi:10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2.
51. Locatelli, J. D., and P. V. Hobbs, 1974: Fall speeds and masses of solid precipitation particles. J. Geophys. Res., 79, 2185-2197, doi:10.1029/JC079i015p02185.
52. 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.
53. Martin, G. M., D. W. Johnson, and A. Spice, 1994: The measurement and parameterization of effective radius of droplets in warm stratocumulus clouds. J. Atmos. Sci., 51, 1823-1842, doi:10.1175/1520-0469(1994)051<1823:TMAPOE>2.0.CO;2.
54. Matson, R. J., and A. W. Huggins, 1980: The direct measurement of the sizes, shapes and kinematics of falling hailstones. J. Atmos. Sci., 37, 1107-1125, doi:10.1175/1520-0469(1980)037<1107:TDMOTS>2.0.CO;2.
55. McCumber, M., W.-K. Tao, J. Simpson, R. Penc, and S.-T. Soong, 1991: Comparison of ice-phase microphysical parameterization schemes using numerical simulations of tropical convection. J. Appl. Meteor., 30, 985-1004, doi:10.1175/1520-0450-30.7.985.
56. McFarquhar, G. M., H. Zhang, G. Heymsfield, R. Hood, J. Dudhia, J. B. Halverson, and F. Marks Jr., 2006: Factors affecting the evolution of Hurricane Erin (2001) and the distributions of hydrometeors: Role of microphysical processes. J. Atmos. Sci., 63, 127-150, doi:10.1175/JAS3590.1.
57. Meyers, M. P., R. L.Walko, J. Y. Harrington, andW. R. Cotton, 1997: New RAMS cloud microphysics. Part II: The twomoment scheme. Atmos. Res., 45, 3-39, doi:10.1016/S0169-8095(97)00018-5.
58. 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, doi:10.1175/JAS3534.1.
59. 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, doi:10.1175/JAS3535.1.
60. Milbrandt, J. A., and R. McTaggart-Cowan, 2010: Sedimentation-induced errors in bulk microphysics schemes. J. Atmos. Sci., 67, 3931-3948, doi:10.1175/2010JAS3541.1.
61. Milbrandt, J. A., and H. Morrison, 2013: Predicting graupel density in a bulk microphysics scheme. J. Atmos. Sci., 70, 410-429, doi:10.1175/JAS-D-12-0204.1.
62. Mitchell, D. L., 1996: Use of mass- and area-dimensional power laws for determining precipitation particle terminal velocities. J. Atmos. Sci., 53, 1710-1723, doi:10.1175/1520-0469(1996)053<1710:UOMAAD>2.0.CO;2.
63. Mitchell, D. L., and A. J. Heymsfield, 2005: The treatment of ice particle terminal velocities, highlighting aggregates. J. Atmos. Sci., 62, 1637-1644, doi:10.1175/JAS3413.1.
64. Mitchell, D. L., and E. Erfani, cited 2014: Developing and bounding ice particle mass- and area-dimension expressions for use in climate models and remote sensing. [Available online at https://ams.confex.com/ams/14CLOUD14ATRAD/webprogram/Paper250163.html.]
65. Mitchell, D. L., R. Zhang, and R. L. Pitter, 1990: Mass-dimensional relationships for ice particles and the influence of riming on snowfall rates. J. Appl. Meteor., 29, 153-163, doi:10.1175/1520-0450(1990)029<0153:MDRFIP>2.0.CO;2.
66. Morrison, H., 2012: On the numerical treatment of hydrometeor sedimentation in bulk and hybrid bulk-bin schemes. Mon. Wea. Rev., 140, 1572-1588, doi:10.1175/MWR-D-11-00140.1.
67. Morrison, H., and W. W. Grabowski, 2007: Comparison of bulk and bin warm rain microphysics models using a kinematic framework. J. Atmos. Sci., 64, 2839-2861, doi:10.1175/JAS3980.
68. Morrison, H., and W. W. Grabowski, 2008a: A novel approach for representing ice microphysics in models: Description and tests using a kinematic framework. J. Atmos. Sci., 65, 1528-1548, doi:10.1175/2007JAS2491.1.
69. Morrison, H., and W. W. Grabowski, 2008b: Modeling supersaturation and subgrid-scale mixing with two-moment warm bulk microphysics. J. Atmos. Sci., 65, 792-812, doi:10.1175/2007JAS2374.1.
70. Morrison, H., and W. W. Grabowski, 2010: An improved representation of rimed snow and conversion to graupel in a mutlicomponent bin microphysics scheme. J. Atmos. Sci., 67, 1337-1360, doi:10.1175/2010JAS3250.1.
71. Morrison, H., and J. A. Milbrandt, 2011: Comparison of two-moment bulk microphysics schemes in idealized supercell thunderstorm simulations. Mon. Wea. Rev., 139, 1103-1130, doi:10.1175/2010MWR3433.1.
72. Morrison, H., J. A. Curry, and V. I. Khvorostyanov, 2005: A new doublemoment microphysics parameterization for application in cloud and climate models. Part I: Description. J. Atmos. Sci., 62, 1665-1677, doi:10.1175/JAS3446.1.
73. 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.
74. Morrison, H., J.A. Milbrandt, G. H. Bryan, K. Ikeda, S. A. Tessendorf, and G. Thompson, 2015: Parameterization of 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.
75. Musil, D. J., 1970: Computer modeling of hailstone growth in feeder clouds. J. Atmos. Sci., 27, 474-482, doi:10.1175/1520-0469(1970)027<0474:CMOHGI>2.0.CO;2.
76. Philips, V. T. J., L. J. Donner, and S. T. Garner, 2007: Nucleation processes in deep convection simulated by a cloud-resolving model with double-moment bulk microphysics. J. Atmos. Sci., 64, 738-761, doi:10.1175/JAS3869.1.
77. Pruppacher, H. R., and J. D. Klett, 1997: Microphysics of Clouds and Precipitation. Kluwer Academic Publishers, 954 pp.
78. Rasmussen, R. M., V. Levizzani, and H. R. Pruppacher, 1984: A wind tunnel and theoretical study on the melting behavior of atmospheric ice particles: III. Experiment and theory for spherical ice particles of radius. 500mm. J. Atmos. Sci., 41, 381-388, doi:10.1175/1520-0469(1984)041<0381:AWTATS>2.0.CO;2.
79. Reisin, T., Z. Levin, and S. Tzivion, 1996: Rain production in convective clouds as simulated in an axisymmetric model with detailed microphysics. Part I: Description of the model. J. Atmos. Sci., 53, 497-519, doi:10.1175/1520-0469(1996)053<0497:RPICCA>2.0.CO;2.
80. Reisner, J., R. M. Rasmussen, and R. T. Bruintjes, 1998: Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model. Quart. J. Roy. Meteor. Soc., 124, 1071-1107, doi:10.1002/qj.49712454804.
81. Rogers, D. C., 1974: The aggregation of natural ice crystals. Rep. AR110, 91 pp. [Available from University of Wyoming, Atmospheric Science, Dept. 3038, 1000 E. University Ave., Laramie, WY 82072.]
82. Rutledge, S. A., and P. V. Hobbs, 1983: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. VII: A model for the "seeder-feeder" process in warm-frontal rainbands. J.Atmos. Sci., 40, 1185-1206, doi:10.1175/1520-0469(1983)040<1185:TMAMSA>2.0.CO;2.
83. Rutledge, S. A., and P. V. Hobbs, 1984: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. XII: A diagnostic modeling study of precipitation development in narrow cold-frontal rainbands. J. Atmos. Sci., 41, 2949-2972, doi:10.1175/1520-0469(1984)041<2949:TMAMSA>2.0.CO;2.
84. Rutledge, S. A., and R. A. Houze, 1987: A diagnostic modelling study of the trailing stratiform region of a midlatitude squall line. J. Atmos. Sci., 44, 2640-2656, doi:10.1175/1520-0469(1987)044<2640:ADMSOT>2.0.CO;2.
85. Schmitt, C. G., and A. J. Heymsfield, 2010: Dimensional characteristics of ice crystal aggregates from fractal geometry. J. Atmos. Sci., 67, 1605-1616, doi:10.1175/2009JAS3187.1.
86. Seifert, A., 2008: On the parameterization of evaporation of raindrops as simulated by a one-dimensional rainshaft model. J. Atmos. Sci., 65, 3608-3619, doi:10.1175/2008JAS2586.1.
87. Seifert, A., and K. D. Beheng, 2001: A double-moment parameterization for simulating autoconversion, accretion and selfcollection. Atmos. Res., 59-60, 265-281, doi:10.1016/S0169-8095(01)00126-0.
88. Simmel, M., T. Trautmann, and G. Tetzlaff, 2002: Numerical solution of the stochastic collection equation comparison of the linear discrete method with other methods. Atmos. Res., 61, 135-148, doi:10.1016/S0169-8095(01)00131-4.
89. Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note TN-475+STR, 113 pp. [Available online at http://www.mmm.ucar.edu/wrf/users/docs/arw_v3_bw.pdf.]
90. Smith, P. L., 1984: Equivalent radar reflectivity factors for snow and ice particles. J. Climate Appl. Meteor., 23, 1258-1260, doi:10.1175/1520-0450(1984)023<1258:ERRFFS>2.0.CO;2.
91. Stevens, B., R. L. Walko, and W. R. Cotton, 1996: The spurious production of cloud-edge supersaturation by Eulerian models. Mon. Wea. Rev., 124, 1034-1041, doi:10.1175/1520-0493(1996)124<1034:TSPOCE>2.0.CO;2.
92. Straka, J. M., and E. R. Mansell, 2005: A bulk microphysics parameterization with multiple ice precipitation categories. J. Appl. Meteor., 44, 445-466, doi:10.1175/JAM2211.1.
93. Sulia, K., J. Y. Harrington, and H. Morrison, 2013: A method for adaptive habit prediction in bulk microphysical models. Part III: Applications and studies within a two-dimensional kinematic model. J. Atmos. Sci., 70, 3302-3320, doi:10.1175/JAS-D-12-0316.1.
94. Takahashi, T., 1976: Hail in an axisymmetric cloud model. J. Atmos. Sci., 33, 1579-1601, doi:10.1175/1520-0469(1976)033<1579:HIAACM>2.0.CO;2.
95. Thompson, G., R.M. Rasmussen, andK. Manning, 2004: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis. Mon. Wea. Rev., 132, 519-542, doi:10.1175/1520-0493(2004)132<0519:EFOWPU>2.0.CO;2.
96. 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.
97. VanWeverberg, K., 2013: Impact of environmental instability on convective precipitation uncertainty associated with the nature of the rimed ice species in a bulk microphysics scheme. Mon. Wea. Rev., 141, 2841-2849, doi:10.1175/MWR-D-13-00036.1.
98. Verlinde, H., and W. R. Cotton, 1993: Fitting microphysical observations of nonsteady convective clouds to a numerical model: An application of the adjoint technique of data assimilation to a kinematic model. Mon. Wea. Rev., 121, 2776-2793, doi:10.1175/1520-0493(1993)121<2776:FMOONC>2.0.CO;2.
99. Walko, R. L., W. R. Cotton, M. P. Meyers, and J. Y. Harrington, 1995: New RAMS cloud microphysics. Part I: The onemoment scheme. Atmos. Res., 38, 29-62, doi:10.1016/0169-8095(94)00087-T.
100. Wang, H., W. C. Skamarock, and G. Feingold, 2009: Evaluation of scalar advection schemes in the Advanced Research WRF model using large-eddy simulations of aerosol-cloud interactions. Mon. Wea. Rev., 137, 2547-2558, doi:10.1175/2009MWR2820.1.
101. Wang, H., T. Auligne, and H.Morrison, 2012: Impact of microphysics scheme complexity on the propagation of initial perturbations. Mon. Wea. Rev., 140, 2287-2296, doi:10.1175/MWR-D-12-00005.1.
102. 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, doi:10.1175/1520-0493(1982)110<0504:TDONSC>2.0.CO;2.
103. Weisman, M. L., and J. B. Klemp, 1984: The structure and classification of numerically simulated convective storms in directionally varying wind shears. Mon. Wea. Rev., 112, 2479-2498, doi:10.1175/1520-0493(1984)112<2479:TSACON>2.0.CO;2.
104. Zhang, F., N. Bei, R. Rotunno, C. Snyder, and C. C. Epifanio, 2007: Mesoscale predictability of moist baroclinic waves: Convection-permitting experiments and multistage error growth dynamics. J. Atmos. Sci., 64, 3579-3594, doi:10.1175/JAS4028.1.
105. Ziegler, C. L., 1985: Retrieval of thermal and microphysical variables in observed convective storms. Part I: Model development and preliminary testing. J. Atmos. Sci., 42, 1487-1509, doi:10.1175/1520-0469(1985)042<1487:ROTAMV>2.0.CO;2.