暴雨模拟中多普勒雷达径向速度变分同化的应用

针对2008年6月广东地区的一次强降雨过程,利用WRF中尺度数值模式及其三维变分同化系统(WRF-3DVAR),进行了多普勒雷达径向速度变分同化对暴雨过程模拟效果影响研究。结果表明:WRF-3DVAR能够有效地同化多普勒雷达径向速度,同化后的主要影响在于改进了初始动力场,使得初始场包含有更详尽的中尺度特征信息,进而显著提高模式对广东局地暴雨过程的模拟效果。在高分辨率中尺度数值模式中有效地利用多普勒天气雷达资料,是提高中尺度降雨预报的关键。     

Contributions of Fuqing ZHANG to Predictability,Data Assimilation,and Dynamics of High Impact Weather: A Tribute

This article reviews Fuqing ZHANG’s contributions to mesoscale atmospheric science,from research to mentoring to academic service,over his 20-year career.His fundamental scientific contributions on predictability,data assimilation,and dynamics of high impact weather,especially gravity waves and tropical cyclones,are highlighted.His extremely generous efforts to efficiently transmit to the community new scientific knowledge and ideas through mentoring,interacting,workshop organizing,and reviewing are summarized.Special appreciation is given to his tremendous contributions to the development of mesoscale meteorology in China and the education of Chinese graduate students and young scientists.     

集合卡尔曼滤波同化多普勒雷达资料的数值试验

利用集合卡尔曼滤波(EnKF)在云数值模式中同化模拟多普勒雷达资料,并考察了不同条件下EnKF同化方法的性能.结果显示,经过几个同化周期后,EnKF分析结果非常接近真值.单多普勒雷达资料EnKF同化对雷达位置不太敏感,双雷达资料同化结果在同化的初期阶段比单雷达资料同化结果准确.同化由反射率导出的雨水比直接同化反射率资料更有效,联合同化径向速度和雨水有利于提高同化分析效果.协方差对EnKF同化效果起着非常重要的作用,考虑模式全部预报变量与径向速度协方差的同化效果比仅考虑速度场与径向速度协方差的同化效果好.雷达资料缺值降低了同化效果,此时增加地面常规观测资料的同化可以明显提高同化分析效果.EnKF同化技术对雷达观测资料误差不太敏感.初始集合对同化分析有较大影响.EnKF同化受集合大小和观测资料影响半径.同化对模式误差较敏感.利用EnKF同化双多普勒雷达资料,分析了一次梅雨锋暴雨过程的中尺度结构.结果表明,EnKF同化技术能够从双多普勒雷达资料反演暴雨中尺度系统的动力场、热力场和微物理场,反演的风场是较准确的,反演的热力场和微物理场分布也是基本合理的.中低层切变线是此次暴雨的主要动力特征,对流云表现为低层辐合、高层辐散并有垂直上升运动伴随,其热力特征表现为低层是低压区,高层为高压区,中部为暖区而上、下部为冷区,水汽、云水和雨水分别集中在对流云体内、上升气流区和强回波区.     

Representations of inverse covariances by differential operators

In the cost function of three- or four-dimensional variational data assimilation, each term is weighted by the inverse of its associated error covariance matrix and the background error covariance matrix is usually much larger than the other covariance matrices. Although the background error covariances are traditionally normalized and parameterized by simple smooth homogeneous correlation functions, the covariance matrices constructed from these correlation functions are often too large to be inverted or even manipulated. It is thus desirable to find direct representations of the inverses of background error correlations. This problem is studied in this paper. In particular, it is shown that the background term can be written into f dx|Dv(x)|^2, that is, a squared L2 norm of a vector differential operator D, called the D-operator, applied to the field of analysis increment v(x). For autoregressive correlation functions, the D-operators are of finite orders. For Gaussian correlation functions, the D-operators are of infinite order. For practical applications, the Gaussian D-operators must be truncated to finite orders. The truncation errors are found to be small even when the Gaussian D-operators are truncated to low orders. With a truncated D-operator, the background term can be easily constructed with neither inversion nor direct calculation of the covariance matrix. D-operators are also derived for non-Gaussian correlations and transformed into non-isotropic forms.     

Assimilation of Polarimetric Radar Data Using an Ensemble Kalman Filter for the Analysis and Forecast of Tropical Storm Ewiniar

This study explores the potential for directly assimilating polarimetric radar data (including reflectivity Z and differential reflectivity ZDR) using an ensemble Kalman filter (EnKF) based on the Weather Research and Forecasting (WRF) model to improve analysis and forecast of Tropical Storm Ewiniar (2018). Ewiniar weakened but brought about heavy rainfall over Guangdong, China after its final landfall. Two experiments are performed, one assimilating only Z and the other assimilating both Z and ZDR. Assimilation of ZDR together with Z effectively modifies hydrometeor fields, and improves the intensity, shape and position of rainbands. Forecast of 24-hour extraordinary rainfall ≥250 mm is significantly improved. Improvement can also be seen in the wind fields because of cross-variable covariance. The current study shows the possibility of applying polarimetric radar data to improve forecasting of tropical cyclones, which deserves more researches in the future.     

利用伴随法反演风应力系数

基于无结构网格有限体积法的正模型和伴随数据同化模型,建立了风应力系数反演表达式,将风应力系数的确定变成依赖于区域内观测值的数值迭代过程,实现了风应力系数确定的自动化,并成功进行了概化河口一系列风应力系数反演的伴随同化实验,反演得到的结果精度较高,实验结果表明：1）伴随法反演风应力系数是合理可行的;2）充分的观测数据能够提高反演的精度;3）风速在10 m/s或15 m/s的情况下,对于风应力系数反演的结果影响不大。     

多普勒雷达资料4DVAR同化反演的模拟研究

利用Sun等建立的同化模式和四维变分同化方法对多普勒雷达资料反演大气风场、热力场和微物理场进行了模拟试验研究.反演的基本思路是将4DVAR同化方法应用到三维云模式,定义价值函数表征雷达资料与模式预报结果之间的差别,通过极小化价值函数得到反演场,价值函数相对模式控制变量的梯度由伴随模式求取.试验结果表明,4DVAR同化技术能够从单(双)多普勒雷达资料反演大气三维风场、热力场和微物理场.各个变量反演精度高低与同化过程中变量受约束的大小程度呈正相关.速度场和雨水场反演精度较高,温度场、云水和水汽的反演精度次之,温度场的准确反演需要较长的同化时间.价值函数中加入背景场,哪怕是单点探空给出的平均场信息也有利于提高反演精度.在采用单部多普勒雷达资料进行反演时,速度场的反演误差较大.反演区相对雷达站的位置变化对速度场反演结果有一定的影响,而对其他变量的反演影响很小.两个时次的雷达观测资料基本足够提供反演所需的时间演变信息,同化更多时次的雷达资料,反演效果改进很小.雷达观测资料的缺值会显著降低同化效果,甚至可能导致同化失败,引入背景场可以改善这一状况.4DVAR同化技术对于雷达观测资料误差不太敏感.利用双多普勒雷达合成风场提供水平风场边界条件是比较准确可靠的.在反演主体离边界较远时,VAD风场也基本可用作水平风场边界条件.微物理场的反演对模式中的微物理参数化方案较敏感.     

ASSIMILATION OF OBSERVED SURFACE WIND WITH GRAPES

With the advances of numerical weather simulation and reduced data assimilation updating cycle, surface observation data assimilation becomes more and more important in data assimilation systems. It is widely accepted that a better data assimilation system should contain the restriction of thermodynamic processes in the surface layer. Therefore, in this paper, a new surface wind observation operator is utilized in Global and Regional Assimilation PrEdiction System_3D-Variance (GRAPES_3D-Var), with the restriction of thermodynamic process in the planetary boundary layer (PBL). In order to research the ability of this new surface wind observation operator in assimilation and forecasting, a series of experiments are operated by using the GRAPES model. The main results indicate that this new method of surface wind observation operator has positive impact on the forecast with the GRAPES model.     

利用ARGO资料改进海洋资料同化和海洋模式中的物理过程

国际ARGO计划的实施每年将可提供多达 10万个剖面 (0～ 2 0 0 0m水深 )的海水温度和盐度资料 ,这些资料的获取无疑将会大大促进海洋和大气科学的发展 ,使人们加深对海洋过程的了解 ,揭示海 气相互作用的机理 ,为长期天气预报和短期气候预测提供模式初始场 ,提高长期天气预报和短期气候预测的能力。如何利用这些资料开展研究工作以及在实际业务中应用这些资料是目前大气和海洋科学界的一个前沿课题。本研究将ARGO浮标资料引入了国家气候中心的NCC GODAS同化系统 ,结果分析表明 ,同化ARGO资料后所得到的海温场在三大洋中不仅在温度数值的大小 ,而且在分布形式方面都与观测场具有较好的一致性 ,可以很好地反映出观测到的冬季和夏季海温的分布形式以及海温的季节变化特征和异常特征。本研究还应用最新的ARGO海洋观测资料 ,通过建立新的热带西太平洋次表层海温参数化方案 ,改进了Zebiak Cane(1987)海洋模式 (ZC模式 ) ,克服了ZC模式几乎没有模拟赤道西太平洋表层和次表层海温变化能力的缺陷。在ZC模式中引用新的次表层海温参数化方案后 ,在赤道西太平洋不仅次表层海温的模拟得到了改善 ,对海面温度异常的模拟也有了较大的改进 ,不仅模拟出了赤道西太平洋表层和次表层海温异常的年际变化特征 ,也模拟出了与观     

雷达反射率资料的三维变分同化研究

应用天气研究和预报模式(WRF)三维变分系统中一种新的雷达反射率资料间接同化方法来进行反射率资料的三维变分同化研究,评估雷达反射率资料对夏季短时定量降水预报的作用.该方法不直接同化雷达反射率资料,而是同化由反射率资料反演出的雨水和估计的水汽.以2009年夏季北京地区发生的4次强降水过程为例,考察了北京市气象局业务运行的快速更新循环同化预报系统对京津冀地区雷达网的雷达反射率资料的同化性能以及雷达反射率资料和径向风资料同时同化的效果.数值试验结果表明:(1)同化反演雨水或水汽都能改善降水预报,但同化反演水汽对降水预报效果的改善起了更重要的作用;(2)同化反射率资料能极大地提高短时降水预报的效果,其稳定的正面效果可以延伸到6h的预报时效,而同化径向风资料不能得到稳定的正效果;(3)同化雷达资料时,应用快速更新循环同化预报系统是提高短时定量降水预报的一个有效途径.