Initialization and Numerical Forecasting of a Supercell Storm Observed during STEPS

Juanzhen Sun National Center for Atmospheric Research,* Boulder, Colorado

Search for other papers by Juanzhen Sun in
Current site
Google Scholar
PubMed
Close
Restricted access

We are aware of a technical issue preventing figures and tables from showing in some newly published articles in the full-text HTML view.
While we are resolving the problem, please use the online PDF version of these articles to view figures and tables.

Abstract

The feasibility of initializing a numerical cloud model with single-Doppler observations and predicting the evolution of thunderstorms has been tested using an observed case of a supercell storm during the Severe Thunderstorm Electrification and Precipitation Study (STEPS). Single-Doppler observations from the Weather Surveillance Radar-1988 Doppler (WSR-88D) at Goodland, Kansas, are assimilated into a cloud-scale numerical model using a four-dimensional variational data assimilation (4DVAR) scheme. A number of assimilation and short-range numerical prediction experiments are conducted. Both the assimilation and prediction results are compared with those of a dual-Doppler synthesis. The prediction results are also verified with reflectivity observations. It is shown that the analysis of the wind field captures the major structure of the storm as revealed by the dual-Doppler synthesis. Thermodynamical and microphysical features retrieved through the dynamical model show consistency with expectations for a deep convective storm. The predicted storm evolution represented by the reflectivity field correlates well with the observations for a 2-h prediction period. The relative importance of the initial fields on the subsequent prediction of the storm evolution is examined by alternately removing the perturbation in each of the initial fields. It is shown that the prediction is most sensitive to the initialization of wind, water vapor, and temperature perturbations.

A number of sensitivity experiments for initialization are conducted to show how the initial analysis depends on the application of a cycling procedure, the weights of the smoothness constraint, and the relative importance between the radial velocity and the reflectivity observations. It is found that the application of the cycling procedure improves the analysis and the subsequent forecast. Greater smoothness coefficients of the penalty term in the cost function result in a larger rms difference in the wind analysis, but help spread the information out and improve the forecast slightly. The radial velocity observations play a more important role than the reflectivity in terms of the wind analysis and the subsequent precipitation forecast.

Corresponding author address: Dr. Juanzhen Sun, National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307. Email: sunj@ucar.edu

Abstract

The feasibility of initializing a numerical cloud model with single-Doppler observations and predicting the evolution of thunderstorms has been tested using an observed case of a supercell storm during the Severe Thunderstorm Electrification and Precipitation Study (STEPS). Single-Doppler observations from the Weather Surveillance Radar-1988 Doppler (WSR-88D) at Goodland, Kansas, are assimilated into a cloud-scale numerical model using a four-dimensional variational data assimilation (4DVAR) scheme. A number of assimilation and short-range numerical prediction experiments are conducted. Both the assimilation and prediction results are compared with those of a dual-Doppler synthesis. The prediction results are also verified with reflectivity observations. It is shown that the analysis of the wind field captures the major structure of the storm as revealed by the dual-Doppler synthesis. Thermodynamical and microphysical features retrieved through the dynamical model show consistency with expectations for a deep convective storm. The predicted storm evolution represented by the reflectivity field correlates well with the observations for a 2-h prediction period. The relative importance of the initial fields on the subsequent prediction of the storm evolution is examined by alternately removing the perturbation in each of the initial fields. It is shown that the prediction is most sensitive to the initialization of wind, water vapor, and temperature perturbations.

A number of sensitivity experiments for initialization are conducted to show how the initial analysis depends on the application of a cycling procedure, the weights of the smoothness constraint, and the relative importance between the radial velocity and the reflectivity observations. It is found that the application of the cycling procedure improves the analysis and the subsequent forecast. Greater smoothness coefficients of the penalty term in the cost function result in a larger rms difference in the wind analysis, but help spread the information out and improve the forecast slightly. The radial velocity observations play a more important role than the reflectivity in terms of the wind analysis and the subsequent precipitation forecast.

Corresponding author address: Dr. Juanzhen Sun, National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307. Email: sunj@ucar.edu

Save
  • Albers, S., J. M. McGinley, D. Birkenheuer, and J. Smart, 1996: The local analysis and prediction system (LAPS): Analyses of clouds, precipitation and temperature. Wea. Forecasting, 11 , 273–287.

    • Search Google Scholar
    • Export Citation
  • Brewster, K., 1996: Implementation of a Bratseth analysis scheme including Doppler radar. Preprints, 15th Conf. on Weather Analysis and Forecasting, Norfolk, VA, Amer. Meteor. Soc., 19–23.

  • 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.

    • Search Google Scholar
    • Export Citation
  • Dowell, C. D., 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.

    • Search Google Scholar
    • Export Citation
  • Droegemeier, K., and Coauthors, 1996a: Real-time numerical prediction of storm-scale weather during VORTEX ’95. Part I: Goals and methodology. Preprints, 18th Conf. on Severe Local Storms, San Francisco, CA, Amer. Meteor. Soc., 6–10.

  • Ducrocq, V., D. Ricard, J-P. Lafore, and F. Orain, 2002: Storm-scale numerical rainfall prediction for five precipitating event over France: On the importance of the initial humidity field. Wea. Forecasting, 17 , 1236–1256.

    • Search Google Scholar
    • Export Citation
  • Evensen, G., 1994: Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res., 99 , C5,. 10143–10162.

    • Search Google Scholar
    • Export Citation
  • Gal-Chen, T., 1978: A method for the initialization of the anelastic equations: Implications for matching models with observations. Mon. Wea. Rev., 106 , 587–606.

    • Search Google Scholar
    • Export Citation
  • Gilmore, M. S., J. M. Straka, and E. N. Rasmussen, 2004: Precipitation and evolution sensitivity in simulated deep convective storms: Comparisons between liquid-only and simple ice and liquid phase microphysics. Mon. Wea. Rev., 132 , 1897–1916.

    • Search Google Scholar
    • Export Citation
  • Hayden, C. M., and R. J. Purser, 1995: Recursive filter objective analysis of meteorological fields: Applications to NESDIS operational processing. J. Appl. Meteor., 34 , 3–15.

    • Search Google Scholar
    • Export Citation
  • Klemp, J. B., R. B. Wilhelmson, and P. S. Ray, 1981: Observed and numerically simulated structure of a mature supercell thunderstorm. J. Atmos. Sci., 38 , 1558–1580.

    • Search Google Scholar
    • Export Citation
  • Laroche, S., and I. Zawadzki, 1994: A variational analysis method for the retrieval of three-dimensional wind field from single-Doppler data. J. Atmos. Sci., 51 , 2664–2682.

    • Search Google Scholar
    • Export Citation
  • Lin, C-L., T. Chai, and J. Sun, 2002: On the smoothness constraints for four-dimensional data assimilation. J. Comput. Phys., 181 , 430–453.

    • Search Google Scholar
    • Export Citation
  • Lin, Y., P. Ray, and K. Johnson, 1993: Initialization of a modeled convective storm using Doppler radar derived fields. Mon. Wea. Rev., 121 , 2757–2775.

    • Search Google Scholar
    • Export Citation
  • Miller, L. J., C. G. Mohr, and A. J. Weinheimer, 1986: The simple rectification to Cartesian space of folded radial velocities from Doppler radar sampling. J. Atmos. Oceanic Technol., 3 , 162–174.

    • Search Google Scholar
    • Export Citation
  • Mohr, C. G., and R. L. Vaughan, 1979: An economical procedure for Cartesian interpolation and display of reflectivity data in three dimensional space. J. Appl. Meteor., 18 , 661–670.

    • Search Google Scholar
    • Export Citation
  • Mohr, C. G., R. L. Vaughan, and H. W. Frank, 1986: The merger of mesoscale datasets into a common Cartesian format for efficient and systematic analyses. J. Atmos. Oceanic Technol., 3 , 144–161.

    • Search Google Scholar
    • Export Citation
  • Montmerle, T., A. Caya, and I. Zawadzki, 2001: Simulation of a midlatitude convective storm initialized with bistatic Doppler radar data. Mon. Wea. Rev., 129 , 1949–1967.

    • Search Google Scholar
    • Export Citation
  • Shapiro, S., 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 , 1265–1287.

    • Search Google Scholar
    • Export Citation
  • Snyder, C., and F. Zhang, 2003: Assimilation of simulated Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 131 , 1663–1677.

    • Search Google Scholar
    • Export Citation
  • Straka, J. M., and E. N. Rasmussen, 1997: Toward improving microphysical parameterizations of conversion processes. J. Appl. Meteor., 36 , 896–902.

    • Search Google Scholar
    • Export Citation
  • Sun, J., 2004: Numerical prediction of thunderstorms: Fourteen years later. Atmospheric Turbulence and Mesoscale Meteorology, E. Fedorovich, R. Rotunno, and B. Stevens, Eds., Cambridge University Press, 139–164.

  • 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.

    • Search Google Scholar
    • Export Citation
  • 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.

    • Search Google Scholar
    • Export Citation
  • 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.

    • Search Google Scholar
    • Export Citation
  • Warner, T. T., E. E. Brandes, C. K. Mueller, J. Sun, and D. N. Yates, 2000: Prediction of a flash flood in complex terrain. Part I: A comparison of rainfall estimates from radar, and very short range rainfall simulations from a dynamic model and an automated algorithmic system. J. Appl. Meteor., 39 , 815–825.

    • Search Google Scholar
    • Export Citation
  • Weygandt, S., A. Shapiro, and K. Droegemier, 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.

    • Search Google Scholar
    • Export Citation
  • Weygandt, S., A. Shapiro, and K. Droegemier, 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.

    • Search Google Scholar
    • Export Citation
  • Wilhelmson, R. B., and J. B. Klemp, 1981: Three-dimensional numerical simulation of splitting severe storms on 3 April 1964. J. Atmos. Sci., 38 , 1558–1580.

    • Search Google Scholar
    • Export Citation
  • Wurman, S., S. Heckman, and D. Boccippio, 1993: A bistatic multiple-Doppler radar network. J. Appl. Meteor., 32 , 1802–1818.

  • Xue, M., and Coauthors, 1996: Real-time numerical prediction of storm-scale weather during VORTEX ’95. Part II: Operations summary and example predictions. Preprints, 18th Conf. on Severe Local Storms, San Francisco, CA, Amer. Meteor. Soc., 178–182.

  • Zhang, J., F. Carr, and K. Brewster, 1998: ADAS cloud analysis. Preprints, 12th Conf. on Numerical Weather Prediction, Phoenix, AZ, Amer. Meteor. Soc., 185–188.

  • Ziegler, C. L., 1985: Retrieval of thermal and microphysical variables in observed convective storm. Part 1: Model development and preliminary testing. J. Atmos. Sci., 42 , 1487–1509.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1605 1020 190
PDF Downloads 353 93 7