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雷达资料三维变分同化研究

Study on Three Dimensional Variational Data Assimilation of Radar Data

【作者】 刘红亚

【导师】 徐海明; 薛纪善;

【作者基本信息】 南京信息工程大学 , 气象学, 2009, 博士

【摘要】 本文设计了一个雷达资料三维变分同化方案并采用梅雨和台风天气的实际雷达观测资料进行了同化和预报试验。文献中广泛应用的雷达径向风和反射率因子的观测算子被用来建立观测资料和模式变量之间的物理联系。较强的垂直运动是中尺度天气系统的典型特征之一,本文采用了两种技术来处理垂直速度。其一是采用Richardson方程通过水平风场、温度和气压来对垂直速度进行诊断,其二是利用统计方法由观测的反射率因子反演出垂直速度后,再采用Richardson方程作为观测算子对反演的垂直速度进行同化。研究发现,前一种方法得到的垂直速度偏小,分析出的中尺度对流系统不明显,后一种技术可以得到比较明显的三维中尺度环流结构。同时还发现下边界地形和Richardson方程中的加热项对垂直速度的同化有重要影响。水汽和云水采用一定的诊断方法得到,以构造动力、热力和水成物相互协调的三维对流结构。梅雨和台风暴雨个例试验结果表明,本文同化技术在缓解spinup现象、提高中尺度数值预报水平方面均显示出明显的正效果。论文的创新之处和主要结论有如下几个方面:(1)本文建立的雷达资料三维变分中尺度同化系统是基本合理和有效的,单点检验证明同化系统中各观测算子和约束关系是合理的,天气个例试验显示同化雷达资料后预报结果均得到较大改善。(2)以Richardson方程作为观测算子同化垂直速度可以改善初始场中中尺度系统的三维动力和热力结构,方程中的非绝热项对同化结果有重要影响。(3)淮河暴雨试验结果表明同化雷达资料可以改善梅雨锋(切变线)上的中-β尺度对流系统的预报,缓解Spinup现象,并实现数值模式的热启动。(4)登陆台风试验结果表明同化雷达资料可以提高台风降水、强度和移动路径的预报水平,并改善初始场中台风螺旋雨带上的中-β尺度对流系统的结构。鉴于中尺度和天气尺度天气系统之间的巨大差别,在中尺度资料三维变分同化时,背景误差相关模型的设置、观测误差结构和观测资料的代表性等方面还需要进行更加深入的研究。

【Abstract】 A Doppler weather radar data assimilation scheme with three dimensional variational algorithms is proposed and tested with real observational radar data of both Meiyu torrential rain and typhoon events. The observational operators, commonly used in literatures, describing the physical connection between the fundamental observational elements, i.e. the radial velocity and the intensity of reflectivity, and the model state variables are introduced in this paper. Two approaches dealing with the vertical velocity, which is crucial for meso scale weather system and appears in the observational operators, are compared. One of them introduces the Richardson’s equation to compute diagnostically the vertical velocity with horizontal wind, temperature, pressure and its tendency. The other one retrieves vertical velocity from the reflectivity using statistical algorithm and assimilates the vertical velocity taking Richardson’s equation as observational operator. It is found that the vertical velocity derived by the former is usually too weak while the later gets the distinct three dimensional convective structure of meso-scale system with strong vertical velocity. It is also found that lower terrain and the diabatic term in the Richardson’s equation should not be neglected in assimilating vertical velocity. Vapor and cloud are diagnosticated in order to perfect the convective system. The results of assimilation and prediction experiments with this scheme using operational radar data for a torrential rain event in the Meiyu season and a Typhoon case are analyzed in detail. Both cases show the positive contribution to relief Spin-up phenomenon and improvements of prediction of precipitation caused by meso-P scale convective systems.The innovations and primary conclusions are summarized as follows.(1) The mesoscale 3DVAR radar data assimilation system created in this paper is basically reasonable and effective, single observational datum experiment demonstrates the relations among variables are rational, and the weather cases experiments show assimilating radar data can improve prediction results.(2) Taking Richardson’s equation as observation factor to assimilate vertical velocity can advance the dynamical and thermal structure of mesoscale weather system, and the heating term of Richardson’s equation has great impact on the results.(3) The weather case experiment of Meiyu torrential precipitation indicates assimilating radar data can ameliorate the prediction of meso-P scale convective weather system on Meiyu front or shear line, relief Spinup phenomenon, and hot-start NWP model.(4) Simulation of a typhoon case presents assimilating radar data advanced prediction of typhoon precipitation, intensity and track, enhanced the meso-P scale system on typhoon spiral rain-band.Because of the fatal differs between large-scale and mesoscale weather systems, such problems as relevant model of background error, representativeness of observation data and observation error structure still need to carry on deeper research.

  • 【分类号】P412.25;P456.7
  • 【被引频次】5
  • 【下载频次】541
  • 攻读期成果
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