Improving Short-Term Storm Predictions by Assimilating both Radar Radial-Wind and Reflectivity Observations

Qingyun Zhao Marine Meteorology Division, Naval Research Laboratory, Monterey, California

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John Cook Marine Meteorology Division, Naval Research Laboratory, Monterey, California

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Qin Xu National Severe Storms Laboratory, Norman, Oklahoma

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Paul R. Harasti University Corporation for Atmospheric Research, Boulder, Colorado

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Abstract

A high-resolution data assimilation system is under development at the Naval Research Laboratory (NRL). The objective of this development is to assimilate high-resolution data, especially those from Doppler radars, into the U.S. Navy’s Coupled Ocean–Atmosphere Mesoscale Prediction System to improve the model’s capability and accuracy in short-term (0–6 h) prediction of hazardous weather for nowcasting. A variational approach is used in this system to assimilate the radar observations into the model. The system is upgraded in this study with new capabilities to assimilate not only the radar radial-wind data but also reflectivity data. Two storm cases are selected to test the upgraded system and to study the impact of radar data assimilation on model forecasts. Results from the data assimilation experiments show significant improvements in storm prediction especially when both radar radial-wind and reflectivity observations are assimilated and the analysis incremental fields are adequately constrained by the model’s dynamics and properly adjusted to satisfy the model’s thermodynamical balance.

Corresponding author address: Qingyun Zhao, Marine Meteorology Division, Naval Research Laboratory, 7 Grace Hopper Ave., Mail Stop II, Monterey, CA 93943. Email: allen.zhao@nrlmry.navy.mil

Abstract

A high-resolution data assimilation system is under development at the Naval Research Laboratory (NRL). The objective of this development is to assimilate high-resolution data, especially those from Doppler radars, into the U.S. Navy’s Coupled Ocean–Atmosphere Mesoscale Prediction System to improve the model’s capability and accuracy in short-term (0–6 h) prediction of hazardous weather for nowcasting. A variational approach is used in this system to assimilate the radar observations into the model. The system is upgraded in this study with new capabilities to assimilate not only the radar radial-wind data but also reflectivity data. Two storm cases are selected to test the upgraded system and to study the impact of radar data assimilation on model forecasts. Results from the data assimilation experiments show significant improvements in storm prediction especially when both radar radial-wind and reflectivity observations are assimilated and the analysis incremental fields are adequately constrained by the model’s dynamics and properly adjusted to satisfy the model’s thermodynamical balance.

Corresponding author address: Qingyun Zhao, Marine Meteorology Division, Naval Research Laboratory, 7 Grace Hopper Ave., Mail Stop II, Monterey, CA 93943. Email: allen.zhao@nrlmry.navy.mil

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  • Battan, L. J., 1973: Radar Observation of the Atmosphere. University of Chicago Press, 324 pp. (Reprinted by TechBooks.).

  • Daley, R., 1991: Atmospheric Data Analysis. Cambridge University Press, 457 pp.

  • Dawson, D., and Xue M. , 2006: Numerical forecasts of the 15–16 June 2002 southern plains mesoscale convective system: Impact of mesoscale data and cloud analysis. Mon. Wea. Rev., 134 , 16071629.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dixon, M., and Wiener G. , 1993: TITAN: Thunderstorm Identification, Tracking, Analysis and Nowcasting—A radar-based methodology. J. Atmos. Oceanic Technol., 10 , 785797.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Douglas, R., 1964: Hail size distribution. Preprints, 11th Radar Weather Conf., Boston, MA, Amer. Meteor. Soc., 146–149.

  • Dowell, D., Zhang F. , Wicker L. J. , Snyder C. , and Crook N. A. , 2004: Wind and temperature retrievals in the 17 May 1981 Arcadia, Oklahoma, supercell: Ensemble Kalman filter experiments. Mon. Wea. Rev., 132 , 19822005.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gal-Chen, T., 1978: A method for initializing the anelastic equations: Implications for matching models with observations. Mon. Wea. Rev., 106 , 587606.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gao, J., Xue M. , Shapiro A. , and Droegemeier K. K. , 1999: A variational analysis for the retrieval of three-dimensional mesoscale wind fields from two Doppler radars. Mon. Wea. Rev., 127 , 21282142.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gu, W., Gu H. , and Xu Q. , 2001: Impact of single-Doppler radar observations on numerical prediction of 7 May 1995 Oklahoma squall line. Preprints, Fifth Symp. on Integrated Observing Systems, Albuquerque, NM, Amer. Meteor. Soc., 139–142. [Available online at http://ams.confex.com/ams/annual2001/techprogram/paper_17251.htm.].

  • Hagen, M., and Yuter S. E. , 2003: Relations between radar reflectivity, liquid water content, and rainfall rate during the MAP SOP. Quart. J. Roy. Meteor. Soc., 129 , 477493.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hane, C. E., and Scott B. C. , 1978: Temperature and pressure perturbations within convective clouds derived from detailed air motion information: Preliminary testing. Mon. Wea. Rev., 106 , 654661.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hodur, R. M., 1997: The Naval Research Laboratory’s Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS). Mon. Wea. Rev., 125 , 14141430.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Johnson, K., and Coauthors, 1998: Warning decision support system: The next generation. Preprints, 14th Int. Conf. on Interactive Information and Processing System (IIPS) for Meteorology, Oceanography, and Hydrology, Phoenix, AZ, Amer. Meteor. Soc., J25–28.

  • Kakar, R., Goodman M. , Hood R. , and Gullory A. , 2006: Overview of the Convection and Moisture Experiment (CAMEX). J. Atmos. Sci., 63 , 518.

  • Kasahara, A., Mizzi A. , and Donner L. , 1992: Impact of cumulus initialization on the spinup of precipitation forecasts in the tropics. Mon. Wea. Rev., 120 , 13601380.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Keeler, R. J., and Passarelli R. E. , 1990: Signal processing for atmospheric radars. Radar in Meteorology, D. Atlas, Ed., Amer. Meteor. Soc., 199–229.

    • Search Google Scholar
    • Export Citation
  • Keeler, R. J., and Ellis S. M. , 2000: Observational error covariance matrices for radar data assimilation. Phys. Chem. Earth, 25B , 12771280.

    • Search Google Scholar
    • Export Citation
  • Marks, F., and Houze R. , 1987: Inner core structure of Hurricane Alicia from airborne radar observations. J. Atmos. Sci., 44 , 12961317.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mueller, C., Saxen T. , Roberts R. , Wilson J. , Betancourt T. , Detting S. , Oien N. , and Yee J. , 2003: NCAR Auto-Nowcast system. Wea. Forecasting, 18 , 545561.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qiu, C. J., and Xu Q. , 1992: A simple adjoint method of wind analysis for single-Doppler data. J. Atmos. Oceanic Technol., 9 , 588598.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qiu, C. J., and Xu Q. , 1996: A simple adjoint method of wind analysis for single-Doppler data. Mon. Wea. Rev., 124 , 11321144.

  • Roux, F., and Viltard N. , 1995: Structure and evolution of Hurricane Claudette on 7 September 1991 from airborne Doppler radar observations. Part I: Kinematics. Mon. Wea. Rev., 123 , 26112639.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shapiro, A., Ellis S. , and Shaw J. , 1995: Single-Doppler velocity retrieval with Phoenix II data: Clear air and microburst wind retrievals in the planetary boundary layer. J. Atmos. Sci., 52 , 12651287.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shapiro, A., Robinson P. , Wurman J. , and Gao J. , 2003: Single-Doppler velocity retrieval with rapid-scan radar data. J. Atmos. Oceanic Technol., 20 , 17581775.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Skamarock, W., 2004: Evaluating mesoscale NWP models using kinetic energy spectra. Mon. Wea. Rev., 132 , 30193032.

  • Snyder, C., and Zhang F. , 2003: Assimilation of simulated Doppler radar observations with an ensemble Kalman Filter. Mon. Wea. Rev., 131 , 16631677.

  • 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.

    • Search Google Scholar
    • Export Citation
  • Sun, J., 2005: Initialization and numerical forecasting of a supercell storm observed during STEPS. Mon. Wea. Rev., 133 , 793813.

  • Sun, J., and Crook N. A. , 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 , 16421661.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, J., and Crook N. A. , 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 , 836852.

    • Search Google Scholar
    • Export Citation
  • Tong, M., and Xue M. , 2005: Ensemble Kalman filter assimilation of Doppler radar data with a compressible nonhydrostatic model: OSS experiments. Mon. Wea. Rev., 133 , 17891807.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Turner, B., Zawadzki I. , and Germann U. , 2004: Predictability of precipitation from continental radar images. Part III: Operational nowcasting implementation (MAPLE). J. Appl. Meteor., 43 , 231248.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weygandt, S. S., Shapiro A. , and Droegemeier K. K. , 2002a: Retrieval of initial forecast fields from single-Doppler observations of a supercell thunderstorm. Part I: Single-Doppler velocity retrieval. Mon. Wea. Rev., 130 , 433453.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weygandt, S. S., Shapiro A. , and Droegemeier K. K. , 2002b: Retrieval of initial forecast fields from single-Doppler observations of a supercell thunderstorm. Part II: Thermodynamic retrieval and model prediction. Mon. Wea. Rev., 130 , 454476.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, B., Verlinde J. , and Sun J. , 2000: Dynamical and microphysical retrievals from Doppler radar observations of a deep convective cloud. J. Atmos. Sci., 57 , 262283.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xiao, Q., Kuo Y-H. , Sun J. , Lee W-C. , Lim E. , Guo Y. , and Barker D. M. , 2005: Assimilation of Doppler radar observations with a regional 3DVAR system: Impact of Doppler velocities on forecasts of a heavy rainfall case. J. Appl. Meteor., 44 , 768788.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xu, Q., 2007: Measuring information content from observations for data assimilation: Relative entropy versus Shannon entropy difference. Tellus, 59A , 198209.

    • Search Google Scholar
    • Export Citation
  • Xu, Q., Qiu C. J. , Gu H. D. , and Yu J. X. , 1995: Simple adjoint retrievals of microburst winds from single-Doppler radar data. Mon. Wea. Rev., 123 , 18221833.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xu, Q., Gu H. , and Gu W. , 2001a: A variational method for Doppler radar data assimilation. Preprints, Fifth Symp. on Integrated Observing Systems, Albuquerque, NM, Amer. Meteor. Soc., 118–121. [Available online at http://ams.confex.com/ams/annual2001/techprogram/paper_17459.htm.].

  • Xu, Q., Gu H. , and Yang S. , 2001b: Simple adjoint method for three-dimensional wind retrievals from single-Doppler radar. Quart. J. Roy. Meteor. Soc., 127 , 10531067.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xu, Q., Wei L. , Lu H. , Qiu C. , and Zhao Q. , 2008: Time-expanded sampling for ensemble-based filters: Assimilation experiments with a shallow-water equation model. J. Geophys. Res., 113 .D02114, doi:10.1029/2007JD008624.

    • Search Google Scholar
    • Export Citation
  • Xue, M., Tong M. , and Droegemeier K. K. , 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 , 4666.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, F., Snyder C. , and Sun J. , 2004: Impacts of initial estimate and observation availability on convective-scale data assimilation with an ensemble Kalman filter. Mon. Wea. Rev., 132 , 12381253.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhao, Q., Cook J. , Schmidt J. , Frost M. , Harasti P. , and Gaudet B. , 2004: The use of radar observations of reflectivity in verifying model hydrometeor fields. Preprints, 20th Conf. on Weather Analysis and Forecasting and 16th Conf. on Numerical Weather Prediction, Seattle, WA, Amer. Meteor. Soc., P4.10. [Available online at http://ams.confex.com/ams/pdfpapers/97032.pdf.].

  • Zhao, Q., Cook J. , Xu Q. , and Harasti P. , 2006: Using radar wind observations to improve mesoscale numerical weather prediction. Wea. Forecasting, 21 , 502521.

    • Crossref
    • Search Google Scholar
    • Export Citation
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