Dynamic adjustment in a numerically simulated mesoscale convective system: Impact of the velocity field

Journal of the Atmospheric Sciences

Volumn 63, Issue 9, 2006, Pages 2246-2268

  Nascimento, Ernani de Lima ^a,b   Droegemier, Kelvin K ^a  

^a UNIVERSITY OF OKLAHOMA   (United States)

^b Instituto Technológico SIMEPAR   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; DYNAMICS; MATHEMATICAL MODELS; STORMS; VELOCITY MEASUREMENT;

DEEP CONVECTIVE STORMS; MESOSCALE CONVECTIVE SYSTEM; VELOCITY COMPONENTS; VELOCITY FIELD;

CLOUDS;

CLOUDS; COMPUTER SIMULATION; DYNAMICS; MATHEMATICAL MODELS; STORMS; VELOCITY MEASUREMENT;

COMPUTER SIMULATION; CONVECTIVE SYSTEM; GEOSTROPHIC FLOW; HYDROSTATICS; MESOSCALE METEOROLOGY; STORM; WIND FIELD;

EID: 33749245920     PISSN: 00224928     EISSN: None     Source Type: Journal    
DOI: 10.1175/JAS3744.1     Document Type: Article

References (79)

1. Bannon, P. R., 1995: Hydrostatic adjustment: Lamb's problem. J. Atmos. Sci., 52, 2302-2312.
2. Blumen, W., 1972: Geostrophic adjustment. Rev. Geophys. Space Phys., 10, 485-528.
3. Bretherton, C. S., and P. K. Smolarkiewicz, 1989: Gravity waves, compensating subsidence, and detrainment around cumulus clouds. J. Atmos. Sci., 46, 740-759.
4. Brewster, K., 2003a: Phase-correcting data assimilation and application to storm-scale numerical weather prediction. Part I: Method description and simulation testing. Mon. Wea. Rev., 131, 480-492.
5. Brewster, K., 2003b: Phase-correcting data assimilation and application to storm-scale numerical weather prediction. Part II: Application to a severe storm outbreak. Mon. Wea. Rev., 131, 493-507.
6. Chagnon, J. M., and P. R. Bannon, 2001: Hydrostatic and geostrophic adjustment in a compressible atmosphere: Initial response and final equilibrium to an instantaneous localized heating. J. Atmos. Sci., 58, 3776-3792.
7. Charney, J., M. Halem, and R. Jastrow, 1969: Use of incomplete historical data to infer the present state of the atmosphere. J. Atmos. Sci., 26, 1160-1163.
8. Crook, N. A., 1996: Sensitivity of moist convection forced by boundary layer processes to low-level thermodynamic fields. Mon. Wea. Rev., 124, 1767-1785.
9. Crook, N. A., and J. D. Tuttle, 1994: Numerical simulations initialized with radar-derived winds. Part II: Forecasts of three gust-front cases. Mon. Wea. Rev., 122, 1204-1217.
10. Crook, N. A., and J. Sun, 2002: Assimilating radar, surface, and profiler data for the Sydney 2000 forecast demonstration project. J. Atmos. Oceanic Technol., 19, 888-898.
11. Crook, N. A., and J. Sun, 2004: Analysis and forecasting of the low-level wind during the Sydney 2000 forecast demonstration project. Wea. Forecasting, 19, 151-167.
12. Daley, R., 1991: Atmospheric Data Analysis. Cambridge University Press, 457 pp.
13. Davies-Jones, R., R. J. Trapp, and H. B. Bluestein, 2001: Tornadoes and tornadic storms. Severe Convective Storms, Meteor. Monogr., No. 50, Amer. Meteor. Soc., 167-221.
14. Davis, C. A., and M. L. Weisman, 1994: Balanced dynamics of mesoscale vortices produced in simulated convective systems. J. Atmos. Sci., 51, 2005-2030.
15. Dowell, D. C., F. Zhang, L. J. Wicker, C. Snyder, and N. A. Crook, 2004: Wind and temperature retrievals in the 17 May 1981 Arcadia, Oklahoma, supercell: Ensemble Kalman filter experiments. Mon. Wea. Rev., 132, 1982-2005.
16. Droegemeier, K. K., and R. P. Davies-Jones, 1987: Simulation of thunderstorm microbursts with a supercompressible numerical model. Proc. Fifth Int. Conf. on Numerical Methods in Laminar and Turbulent Flow, Montreal, QC, Canada, Concordia University and Cosponsors, 1386-1397.
17. Droegemeier, K. K., and J. Levit, 1993: Sensitivity of storm-scale predictions to initialization with simulated Doppler radar data. Preprints, 17th Conf. on Severe Local Storms, St. Louis, MO, Amer. Meteor. Soc., 431-435.
18. Ducrocq, V., J.-P. Lafore, J.-L. Redelsperger, and F. Orain, 2000: Initialization of a fine-scale model for convective-system prediction: A case study. Quart. J. Roy. Meteor. Soc., 126, 3041-3065.
19. Duffy, D. G., 2003: Hydrostatic adjustment in nonisothermal atmospheres. J. Atmos. Sci., 60, 339-353.
20. Durran, D. R., 1999: Numerical Methods for Wave Equations in Geophysical Fluid Dynamics. Springer-Verlag, 465 pp.
21. Elmore, K. L., D. J. Stensrud, and K. C. Crawford, 2002: Ensemble cloud model applications to forecasting thunderstorms. J. Appl. Meteor., 41, 363-381.
22. Fiedler, B. H., 2002: A wind transformation for acoustic adjustment in compressible models. Mon. Wea. Rev., 130, 741-746.
23. Fovell, R. G., 2002: Upstream influence of numerically simulated squall-line storms. Quart. J. Roy. Meteor. Soc., 128, 893-912.
24. Fritsch, J. M., and G. S. Forbes, 2001: Mesoscale convective systems. Severe Convective Storms, Meteor. Monogr., No. 50, Amer. Meteor. Soc., 323-357.
25. Gao, J., M. Xue, A. Shapiro, Q. Xu, and K. K. Droegemeier, 2001: Three-dimensional simple adjoint velocity retrievals from single-Doppler radar. J. Atmos. Oceanic Technol., 18, 26-38.
26. Gilmore, M. S., and L. J. Wicker, 1998: The influence of midtropospheric dryness on supercell morphology and evolution. Mon. Wea. Rev., 1126, 943-958.
27. Houze, R. A., Jr., 1993: Cloud Dynamics. Academic Press, 573 pp.
28. Johns, R. H., 1993: Meteorological conditions associated with bow echo development in convective storms. Wea. Forecasting, 8, 294-299.
29. Kalnay, E., 2003: Atmospheric Modeling, Data Assimilation, and Predictability. Cambridge University Press, 512 pp.
30. Klemp, J. B., and R. B. Wilhelmson, 1978: The simulation of three-dimensional convective storm dynamics. J. Atmos. Sci., 35, 1070-1096.
31. Klemp, J. B., and D. R. Durran, 1983: An upper boundary condition permitting internal gravity wave radiation in numerical mesoscale models. Mon. Wea. Rev., 111, 430-444.
32. Lamb, H., 1908: On the theory of waves propagated vertically in the atmosphere. Proc. London Math. Soc., 7, 122-141.
33. Lamb, H., 1932: Hydrodynamics. Dover Publications, 738 pp.
34. Laroche, S., and I. Zawadzki, 1994: A variational analysis method for the retrieval of three-dimensional wind field from single-Doppler radar data. J. Atmos. Sci., 51, 2664-2682.
35. Lazarus, S., A. Shapiro, and K. K. Droegemeier, 2001: Application of the Zhang-Gal-Chen single-Doppler velocity retrieval to a deep convective storm. J. Atmos. Sci., 58, 998-1016.
36. Li, Q., R. L. Bras, and S. Islam, 1995: Growth and decay of error in a numerical cloud model due to small initial perturbations and parameter changes. J. Appl. Meteor., 34, 1622-1632.
37. Liepman, H. W., and A. Roshko, 1957: Elements of Gasdynamics. John Wiley and Sons, 439 pp.
38. Lighthill, J., 1978: Waves in Fluids. Cambridge University Press, 504 pp.
39. Lin, Y. H., 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.
40. Mapes, B. E., 1993: Gregarious tropical convection. J. Atmos. Sci., 50, 2026-2037.
41. McCaul, E. W., and C. Cohen, 2002: The impact on simulated storm structure and intensity of variations in the mixed layer and moist layer depths. Mon. Wea. Rev., 130, 1722-1748.
42. McPherson, R. A., and K. K. Droegemeier, 1991: Numerical predictability experiments of the 20 May 1977 Del City, OK supercell storm. Preprints, Ninth Conf. on Numerical Weather Prediction, Denver, CO, Amer. Meteor. Soc., 734-738.
43. Nicholls, M. E., and R. A. Pielke, 1994a: Thermal compression waves. I: Total-energy transfer. Quart. J. Roy. Meteor. Soc., 120, 305-332.
44. Nicholls, M. E., and R. A. Pielke, 1994b: Thermal compression waves. II: Mass adjustment and vertical transfer of total energy. Quart. J. Roy. Meteor. Soc., 120, 333-359.
45. Nicholls, M. E., and R. A. Pielke, 2000: Thermally induced compression waves and gravity waves generated by convective storms. J. Atmos. Sci., 57, 3251-3271.
46. Nicholls, M. E., R. A. Pielke, and W. R. Cotton, 1991: Thermally forced gravity waves in an atmosphere at rest. J. Atmos. Sci., 48: 1869-1884.
47. Pandya, R. E., and D. R. Durran, 1996: The influence of convectively generated thermal forcing on the mesoscale circulation around squall lines. J. Atmos. Sci., 53, 2924-2951.
48. Park, S. K., and K. K. Droegemeier, 2000: Sensitivity analysis of a 3D convective storm: Implications for variational data assimilation and forecast error. Mon. Wea. Rev., 128, 184-197.
49. Przybylinski, R. W., 1995: The bow echo: Observations, numerical simulations, and severe weather detection methods. Wea. Forecasting, 10, 203-218.
50. Qiu, C.-J., and Q. Xu, 1996: Least squares retrieval of microburst winds from single-Doppler radar data. Mon. Wea. Rev., 124, 1132-1144.
51. Richardson, Y., 1999: The influence of horizontal variations in vertical shear and moisture on numerically-simulated convective storms. Ph.D. dissertation, University of Oklahoma, 236 pp.
52. Shapiro, A., S. Ellis, and J. Shaw, 1995: Single Doppler velocity retrievals with Phoenix II data: Clear air and microburst wind retrievals in the planetary boundary layer. J. Atmos. Sci., 52, 1265-1285.
53. Skamarock, W. C., and J. B. Klemp, 1992: The stability of time-splitting numerical methods for hydrostatic and nonhydrostatic elastic equations. Mon. Wea. Rev., 120, 2109-2127.
54. Skamarock, W. C., and J. B. Klemp, 1994: Efficiency and accuracy of the Klemp-Wilhelmson time splitting technique. Mon. Wea. Rev., 122, 2623-2630.
55. Smagorinsky, J., K. Miyakoda, and R. Strickler, 1970: The relative importance of variables in initial conditions for dynamical weather prediction. Tellus, 22, 141-154.
56. Snyder, C., and F. Zhang, 2003: Assimilation of simulated Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 131, 1663-1677.
57. Sotack, T., and P. R. Bannon, 1999: Lamb's adjustment for heating of finite duration. J. Atmos. Sci., 56, 71-81.
58. Sun, J., and N. A. Crook, 1997: Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part I: Model development and simulated data experiments. J. Atmos. Sci., 54, 1642-1661.
59. Sun, J., and N. A. Crook, 1998: Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part II: Retrieval experiments of an observed Florida convective storm. J. Atmos. Sci., 55, 835-852.
60. Sun, J., and N. A. Crook, 2001: Real-time low-level wind and temperature analysis using single WSR-88D data. Wea. Forecasting, 16, 117-132.
61. Sun, J., D. W. Flicker, and D. K. Lilly, 1991: Recovery of three-dimensional wind and temperature fields from simulated single-Doppler radar data. J. Atmos. Sci., 48, 876-890.
62. Tong, M., and M. Xue, 2005: Ensemble Kalman filter assimilation of Doppler radar data with a compressible nonhydrostatic model: OSSE experiments. Mon. Wea. Rev., 133, 1789-1807.
63. van Delden, A., 2000: Linear dynamics of hydrostatic adjustment to horizontally homogeneous heating. Tellus, 52A, 380-390.
64. Wakimoto, R. M., 2001: Convectively driven high wind events. Severe Convective Storms, Meteor. Monogr., No. 50, Amer. Meteor. Soc., 255-298.
65. Weisman, M. L., 1993: The genesis of severe, long-lived bow echoes. J. Atmos. Sci., 50, 645-670.
66. Weisman, M. L., 2001: Bow echoes: A tribute to T. T. Fujita. Bull. Amer. Meteor. Soc., 82, 97-116.
67. 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.
68. Weygandt, S. S., P. Nutter, E. Kalnay, S. K. Park, and K. K. Droegemeier, 1999: The relative importance of different data fields in a numerically-simulated convective storm. Preprints, Eighth Conf. on Mesoscale Processes, Boulder, CO, Amer. Meteor. Soc., 310-315.
69. Weygandt, S. S., A. Shapiro, and K. K. Droegemeier, 2002a: Retrieval of model initial fields from single-Doppler observations of a supercell thunderstorm. Part I: Single-Doppler velocity retrieval. Mon. Wea. Rev., 130, 433-453.
70. Weygandt, S. S., A. Shapiro, and K. K. Droegemeier, 2002b: Retrieval of model initial fields from single-Doppler observations of a supercell thunderstorm. Part II: Thermodynamic retrieval and numerical prediction. Mon. Wea. Rev., 130, 454-476.
71. 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.
72. Xue, M., and Coauthors, 2001: The Advanced Regional Prediction System (ARPS) - A multi-scale nonhydrostatic atmospheric simulation and prediction model. Part II: Model physics and applications. Meteor. Atmos. Phys., 76, 143-165.
73. Xue, M., D. Wang, J. 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., 78, 139-170.
74. Xue, M., M. Tong, and K. K. Droegemeier, 2006: An OSSE framework based on the ensemble square-root Kalman filter for evaluating impact of data from radar networks on thunderstorm analysis and forecast. J. Atmos. Oceanic Technol., 23, 46-66.
75. Yang, M.-J., and R. A. Houze Jr., 1995a: Multicell squall-line structure as a manifestation of vertically trapped gravity waves. Mon. Wea. Rev., 123, 641-661.
76. Yang, M.-J., and R. A. Houze Jr., 1995b: Sensitivity of squall line rear inflow to ice microphysics and environmental humidity. Mon. Wea. Rev., 123, 3175-3193.
77. Zhang, F., C. Snyder, and J. Sun, 2004: Impacts of initial estimate and observation availability on convective-scale data assimilation with an ensemble Kalman filter. Mon. Wea. Rev., 132, 1238-1253.
78. 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.
79. Ziegler, C. L., 1988: Retrieval of thermal and microphysical variables in observed convective storms. Part II: Sensitivity of cloud processes to variation of the microphysical parameterization. J. Atmos. Sci., 45, 1072-1090.