Radar Data Assimination in Wrf Model to Forecast Heavy Rainfall at Ho Chi Minh City
Main Article Content
Abstract
Abstract: This paper uses high resolution WRF model to simulate a number of heavy rainfall events in summer in Ho Chi Minh city using radar data to assimilation initial conditions with 3DVAR method, the WRF3Dvar running simulation with two modes: cold start and warm start combine with three cases: only Reflectivity of radar; Reflectivity and Doppler radar radial wind observations; Reflectivity, Doppler radar radial wind, and GTS data. The background error used was CV7 created from 6 months forecast in South Vietnam. Radar data before assimilation was quality control and thinned to remove noise and create the best observation. 24 station rainfall in South Vietnam using to an evaluation of WRF model simulation. Results show assimilation only reflectivity will affect to variable Qcloud, Qvapor and Qrain on the initial condition of model and assimilation only Doppler radar radial wind improve wind. Compare each case show warm start simulation precipitation better than the cold start, assimilation both Doppler radar radial wind observations, the reflectivity of radar and GTS better than another case.
Keywords: WRFDA, RADAR.
References:
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[8] Tong, M. and Xue, M.: Ensemble Kalman filter assimilation of Doppler radar data with a compressible nonhydrostatic model: OSS experiments, Mon. Weather Rev., 133, 1789–1807, 2005
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[10] Hitschfeld, W. and Bordan, J.: Error inherent in the radar measurement of rainfall at attenuating wavelengths, J. Meteorol., 11, 58– 67, 1954.
[11] Browning, K. A., Pardoe, C. W., and Hill, F. F.: The nature of orographic rain at wintertime cold fronts, Q. J. Roy. Meteorol. Soc., 101, 333–352, 1975.
[12] Barker, D. M., W. Huang, Y-R. Guo, A. J. Bourgeois, and Q. N.Xiao, 2004: A three-dimensional variational data assimilation system for MM5: Implementation and initial results. Mon. Wea. Rev., 132,897–914.
[13] Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M.Barker, W. Wang, and J. G. Powers, 2005: A description of the advanced research WRF version 2. NCAR Tech. Note NCAR/TN-468+STR, 88 pp.
[14] 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.
[15] Mark A. Askelson 2000: An Adaptation of the Barnes Filter Applied to the Objective Analysis of Radar Data
[16] Parrish, D. F., and J. C. Derber, 1992: The National Meteorological Center’s spectral statistical-interpolation analysis system. Mon. Wea. Rev., 120, 1747–1763.
References
[2] Trần Hồng Thái và cộng sự, Phương pháp đồng hóa số liệu nudging cho quan trắc Radar và tác động tới dự báo mưa lớn trên khu vực Bắc Bộ. tạp chí Khí tượng Thủy văn 2016, số 670 tr.1-6. – 2016.
[3] Daley, R: Atmospheric Data Analysis, Cambridge University Press, Cambridge, UK, 1991.
[4] Sokol, Z: Effects of an assimilation of radar and satellite data on a very short range forecast of heavy convective rainfalls, Atmos. Res., 93, 188–206, 2009.
[5] Xiao, Q. and Sun, J.: Multiple radar data assimilation and shortrange Quantitative Precipitation Forecasting of a squall line ob served during IHOP 2002, Mon. Weather Rev., 135, 3381–3404, 2007
[6] Xiao, Q., Y-H. Kuo, J. Sun, W-C. Lee, E. Lim, Y-R. Guo, and D. M. Barker, 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, 768–788.
[7] Xiao, Q., Kuo, Y., Sun, J., Lee, W., Barker, D. M., and Lim, E.: An approach of radar reflectivity data assimilation and its assessment with the inland QPF of Typhoon Rusa (2002) at landfall, J. Appl. Meteorol. Clim., 46, 14–22, 2007.
[8] Tong, M. and Xue, M.: Ensemble Kalman filter assimilation of Doppler radar data with a compressible nonhydrostatic model: OSS experiments, Mon. Weather Rev., 133, 1789–1807, 2005
[9] J. Liu, M. Bray , and D. Han 2012: A study on WRF radar data assimilation for hydrological rainfall prediction
[10] Hitschfeld, W. and Bordan, J.: Error inherent in the radar measurement of rainfall at attenuating wavelengths, J. Meteorol., 11, 58– 67, 1954.
[11] Browning, K. A., Pardoe, C. W., and Hill, F. F.: The nature of orographic rain at wintertime cold fronts, Q. J. Roy. Meteorol. Soc., 101, 333–352, 1975.
[12] Barker, D. M., W. Huang, Y-R. Guo, A. J. Bourgeois, and Q. N.Xiao, 2004: A three-dimensional variational data assimilation system for MM5: Implementation and initial results. Mon. Wea. Rev., 132,897–914.
[13] Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M.Barker, W. Wang, and J. G. Powers, 2005: A description of the advanced research WRF version 2. NCAR Tech. Note NCAR/TN-468+STR, 88 pp.
[14] 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.
[15] Mark A. Askelson 2000: An Adaptation of the Barnes Filter Applied to the Objective Analysis of Radar Data
[16] Parrish, D. F., and J. C. Derber, 1992: The National Meteorological Center’s spectral statistical-interpolation analysis system. Mon. Wea. Rev., 120, 1747–1763.