Application of assimilating Dual Doppler radar data in forecast of Hurricane Ike

Shen Feifei; Min Jinzhong; Xu Dongmei; Dai Zejun; Zhang Bing; Chen Yimeng

doi:10.3969/j.issn.0253-4193.2016.11.006

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Shen Feifei, Min Jinzhong, Xu Dongmei, Dai Zejun, Zhang Bing, Chen Yimeng. Application of assimilating Dual Doppler radar data in forecast of Hurricane Ike[J]. Haiyang Xuebao, 2016, 38(11): 60-72. doi: 10.3969/j.issn.0253-4193.2016.11.006

Citation:

Shen Feifei, Min Jinzhong, Xu Dongmei, Dai Zejun, Zhang Bing, Chen Yimeng. Application of assimilating Dual Doppler radar data in forecast of Hurricane Ike[J]. Haiyang Xuebao, 2016, 38(11): 60-72. doi: 10.3969/j.issn.0253-4193.2016.11.006

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Application of assimilating Dual Doppler radar data in forecast of Hurricane Ike

doi: 10.3969/j.issn.0253-4193.2016.11.006

1.
Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China
2.
Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China;National Center for Atmospheric Research, Boulder, Colorado 80307, USA
3.
Institute of Hunan Meteorology, Changsha 410118, China
4.
Jiangsu Research Institute of Meteorlogical Science, Nanjing 210044, China
5.
School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China

Received Date: 2015-07-09
Rev Recd Date: 2015-09-23

Abstract

Abstract

The impacts of assimilation of radial velocity (V_r) data for the application of analyses and forecasts for Hurricane Ike (2008) are investigated using the framework of Weather Research and Forecasting (WRF) V3.7 and its three-dimensional variational data (3DVAR) assimilation system developed by the U.S. National Center for Atmospheric Research (NCAR). To evaluate the impact of using the high spatial and temporal resolution of the radar data on the forecast of Hurricane Ike, V_r observations from two coastal radars are pre-processed with quality control procedures before they are assimilated using 3DVAR. Results show that, it is necessary to tune the background error length scale factor to better spread out observations for hurricane radar data assimilations. It is found that V_r data are able to adjust the hurricane's thermal and dynamic structure significantly. With smaller length scale factor, a much clearer cyclonic circulation wind increment around the observed hurricane center can be observed, providing effective meso-and micro scale information for the analysis, which can further improve the hurricane track and intensity forecast.
- hurricane,
- radial velocity,
- WRF model,
- cycling assimilation

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References

Kurihara Y, Bender M A, Ross R J. An initialization scheme of hurricane models by vortex specification[J]. Mon Wea Rev, 1993, 121: 2030-2045.

Zou X, Xiao Q. Studies on the initialization and simulation of a mature hurricane using a variational bogus data assimilation scheme[J]. J Atmos Sci, 2000, 57: 836-860.

Pu Z X, Braun S A. Evaluation of bogus vortex techniques with four-dimensional variational data assimilation[J]. Mon Wea Rev, 2001, 129: 2023-2039.

Xiao Q, Chen L, Zhang X. Evaluations of BDA scheme using the Advanced Research WRF (ARW) model[J]. J Appl Meteor Climatol, 2009, 48: 680-689.

Xiao Q, Kuo Y H, Sun J, et al. An approach of radar reflectivity data assimilation and its assessment with the inland QPF of typhoon Rusa (2002) at landfall[J]. J Appl Meteor Climatol, 2007, 46: 14-22.

Gu J F, Xiao Q N, Kuo Y H, et al. Assimilation and simulation of Typhoon Rusa (2002) using the WRF system[J]. Adv Atmos Sci, 2005, 22(3): 415-427.

Zhao Q, Jin Y. High-resolution radar data assimilation for Hurricane Isabel (2003) at landfall[J]. Bull Am Meteorol Soc, 2008, 89:1355-1372.

Zhao K, X Li, Xue M, et al. Short-term forecasting through intermittent assimilation of data from Taiwan and Mainland China coastal radars for typhoon Meranti (2010) at landfall[J]. J Geophy Res, 2012, 117: D06108.

陈锋, 冀春晓, 董美莹, 等. 雷达径向风速同化对台风麦莎模拟的影响[J]. 气象, 2012, 38(10): 1170-1181. Chen Feng, Ji Chunxiao, Dong Meiying, et al. The effects of radar radial velocity data assimilation on the simulation of Typhoon Matsa[J]. Meteorological Monthly, 2012,38(10):1170-1181.

李新峰, 赵坤, 王明筠, 等. 多普勒雷达资料循环同化在台风"鲇鱼"预报中的应用[J]. 气象科学, 2013, 33(3): 255-263. Li Xinfeng, Zhao Kun, Wang Mingjun, et al. Short-term forecasting of super typhoon Meji at landfall through cycling assimilation of China coastal radar data[J]. Journal of the Meteorological Sciences, 2013,33(3):255-263.

Lorenc A. The potential of the ensemble Kalman filter for NWP-a comparison with 4D-Var[J]. Quart J Roy Meteor Soc, 2003, 129, 3183-3204.

Sun J, Crook N A. Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part Ⅰ: Model development and simulated data experiments[J]. J Atmos Sci, 1997, 54(12): 1642-1661.

Sun J, Crook N A. 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]. J Atmos Sci, 1998, 55(5): 835-852.

Marshall J S, Palmer W M K. The distribution of raindrops with size[J]. J Meteor, 1948, 5(4): 165-166.

Hong S Y, J Dudhia, Chen S H. A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation[J]. Mon Wea Rev, 2004, 132: 103-120.

Grell G A, Devenyi D. A generalized approach to parameterizing convection combining ensemble and data assimilation techniques[J]. Geophys Res Lett, 2002, 29(14): 1693.

Noh Y, Cheon W G, Hong S Y, et al. Improvement of the K-profile model for the planetary boundary layer based on large eddy simulation data[J]. Bound-Lay Meteorol, 2003, 107: 401-427.

Parrish D F, Derber J C. The National Meteorological Center's spectral statistical interpolation analysis system[J]. Mon Wea Rev, 1992, 120(8): 1747-1763.

沈菲菲,闵锦忠,陈鹏,等. 多普勒雷达资料同化在台风"桑美"预报中的应用应用[J]. 海洋学报, 2015, 37(3): 25-36. Shen Feifei, Min Jinzhong, Chen Peng, et al. Experiments of assimilating Doppler radar data in forecast of typhoon Saomai[J]. Haiyang Xuebao, 2015,37(3):25-36.

沈菲菲,闵锦忠,许冬梅,等. WRF-Hybrid背景误差协方差调整在台风同化及预报中的应用研究[J]. 气象科学, 2015, 35(2): 150-159. Shen Feifei, Min Jinzhong, Xu Dongmei, et al. WRF-Hybrid background error covariance adjustment in typhoon assimilation and forecasting[J]. Journal of the Meteorological Sciences, 2015, 35(2): 150-159.

Xiao Q, Sun J. Multiple-radar data assimilation and short-range quantitative precipitation forecasting of a squall line observed during IHOP_2002[J]. Mon Wea Rev, 2007, 135: 3381-3404.

Snyder C, Zhang F. Assimilation of simulated Doppler radar observations with an ensemble Kalman filter[J]. Mon Wea Rev, 2003, 131: 1663-1677.

Tong M, Xue M. Ensemble Kalman filter assimilation of Doppler radar data with a compressible nonhydrostatic model: OSS experiments[J]. Mon Wea Rev, 2005, 133: 1789-1807.

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