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海洋气象观测系统在热带气旋资料同化中的应用 被引量:4

The application of marine meteorological observation in tropical cyclone data assimilation
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摘要 在分析南海海洋气象观测现状和发展规划的基础上,发现有必要发展合适的资料同化技术,提高资料利用效率,才能克服海洋气象资料相对缺乏来提升数值预报水平。利用多尺度/分块逐批资料同化技术,进行热带气旋资料同化试验。结果表明:多尺度/分块逐批资料同化技术能够适应具有多尺度特征的热带气旋资料同化,较好地满足热带气旋资料同化对流依赖背景误差协方差同化技术的要求,能够较合理高效地利用海洋气象观测资料。基于多尺度/分块逐批资料同化技术,加强海洋气象观测系统的应用,是形成高质量热带气旋初值环流的一种有效途径。 Based on the current situation and development plan of marine meteorological observation,it is recognized that there is a need to develop appropriate data assimilation technology for enhancing the efficiency of data utilization.Only in that way,there is a chance to overcome the lack of observation,and to improve numerical weather prediction.In this paper,the multi-scale/block batch-wise data assimilation is suggested to perform the test of tropical cyclone data assimilation.The results show: the multi-scale/block batch-wise data assimilation can be appropriate for the data assimilation of tropical cyclone multi-scale circulation,satisfy with the flow-dependent background error covariance required by tropical cyclone data assimilation,also can use effectively the marine meteorological observation.By means of the multi-scale/block batch-wise data assimilation,to amplify the utilization of marine meteorological observation,it is an effective approach to obtain high quality tropical cyclone initial circulation.
出处 《中国工程科学》 北大核心 2012年第10期33-42,共10页 Strategic Study of CAE
基金 公益性行业(气象)科研专项(GYHY201006016) 广东省自然科学基金创新团队项目(8351030101000002)
关键词 海洋气象观测 资料利用效率 多尺度/分块逐批资料同化 热带气旋初值环流 marine meteorological observation the efficiency of data utilization multi-scale/block batch-wise data assimilation tropical cyclone initial circulation
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  • 1Meng, Z., and F. Zhang, 2007: Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part II: Imperfect model experiments. Mon. Wea. Rev., 135, 1403- 1423.
  • 2Meng, Z., and F. Zhang, 2008a: Test of an ensemble-Kahnan filter for mesoscale and regional-scale data assimilation. Part III: Comparison with 3Dvar in a real-data case study. Mort. Wea. Rev., 136, 522-540.
  • 3Meng, Z., and F. Zhang, 2008b: Test of an ensemble-Kalman filter for mesoscale and regional-scale data assimilation. Part IV: Performance over a warmseason month of June 2003. Mort. Wea. Rev., 136, 3671 -3682.
  • 4Navon, I. M., D. N. Daescu, and Z. Liu, 2005: The impact of background error on incomplete observations for 4D-Var data assimilation with the FSU GSM. Computational Science-ICCS 2005, PT 2, 3515, 837 844.
  • 5R.abier, F., J. N. Thepaut, and P. Courtier, 1998: Extended assimilation and forecast experiments with a four-dimensional variational assimilation system. Quart. J. Roy. Meteor. Soc., 124, 1861- 1887.
  • 6Snyder, C., and F. Zhang, 2003: Assimilation of simulated Doppler radar observations with an ensemble Kalman filter. Mort. Wea. Rev., 131, 1663-1677.
  • 7Sun, 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.
  • 8Talagrand, O., 1997: Assimilation of observations, an introduction. J. Meteor. Soc. Japan, 75, 191-209.
  • 9Wang, X., C. Snyder, and T. M. Hamill, 2007: On the theoretical equivalence of differently proposed ensemble- 3DVAtt hybrid analysis schemes. Mon. Wea. Rev., 135, 222-227.
  • 10Whitaker, J. S., and T. M. Hamill, 2002: Ensemble data assimilation without perturbed observations. Mort. Wea. Rev., 130, 1923.

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