共查询到19条相似文献，搜索用时 93 毫秒
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A Multivariate Empirical Orthogonal Function-Based Scheme for the Balanced Initial Ensemble Generation of an Ensemble Kalman Filter 
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下载免费PDF全文 The initial ensemble perturbations for an ensemble data assimilation system are expected to reasonably sample model uncertainty at the time of analysis to further reduce analysis uncertainty. Therefore, the careful choice of an initial ensemble perturbation method that dynamically cycles ensemble perturbations is required for the optimal performance of the system. Based on the multivariate empirical orthogonal function (MEOF) method, a new ensemble initialization scheme is developed to generate balanced initial perturbations for the ensemble Kalman filter (EnKF) data assimilation, with a reasonable consideration of the physical relationships between different model variables. The scheme is applied in assimilation experiments with a global spectral atmospheric model and with real observations. The proposed perturbation method is compared to the commonly used method of spatially-correlated random perturbations. The comparisons show that the model uncertainties prior to the first analysis time, which are forecasted from the balanced ensemble initial fields, maintain a much more reasonable spread and a more accurate forecast error covariance than those from the randomly perturbed initial fields. The analysis results are further improved by the balanced ensemble initialization scheme due to more accurate background information. Also, a 20-day continuous assimilation experiment shows that the ensemble spreads for each model variable are still retained in reasonable ranges without considering additional perturbations or inflations during the assimilation cycles, while the ensemble spreads from the randomly perturbed initialization scheme decrease and collapse rapidly. 相似文献
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The MM5, which is the PSU/NCAR mesoscale nonhydrostatic limited-area model, and its
adjoining modeling system are used in this paper. Taking T106 analysis data as background field the authors
generate an optimal initial condition of a typhoon by using two bogus data assimilation schemes, and conduct
some numerical simulating experiments. The results of No.9608 typhoon (Gloria) show that the optimal initial
field have some dramatic improvements, such as inaccurate position of typhoon center, weaker typhoon
circulation and incomplete inner structure of the typhoon, which are caused by shortage of data over the sea.
Some improvements have been made in the track forecast. Through several comparing experiments, the
initialization optimized by BDA scheme is found to be more reasonable than GFDL scheme and its typhoon track
forecast is better. 相似文献
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GU Jianfeng Qingnong XIAO Ying-Hwa KUO Dale M. BARKER XUE Jishan MA Xiaoxing 《大气科学进展》2005,22(3):415-427
Using the recently developed Weather Research and Forecasting (WRF) 3DVAR and the WRF model, numerical experiments are conducted for the initialization and simulation of typhoon Rusa (2002).The observational data used in the WRF 3DVAR are conventional Global Telecommunications System (GTS) data and Korean Automatic Weather Station (AWS) surface observations. The Background Error Statistics (BES) via the National Meteorological Center (NMC) method has two different resolutions, that is, a 210-km horizontal grid space from the NCEP global model and a 10-km horizontal resolution from Korean operational forecasts. To improve the performance of the WRF simulation initialized from the WRF 3DVAR analyses, the scale-lengths used in the horizontal background error covariances via recursive filter are tuned in terms of the WRF 3DVAR control variables, streamfunction, velocity potential, unbalanced pressure and specific humidity. The experiments with respect to different background error statistics and different observational data indicate that the subsequent 24-h the WRF model forecasts of typhoon Rusa‘s track and precipitation are significantly impacted upon the initial fields. Assimilation of the AWS data with the tuned background error statistics obtains improved predictions of the typhoon track and its precipitation. 相似文献
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To solve the problem of mesoscale analysis error accumulation after a period of continuous cycle data assimilation (CCDA), a blending method and a constraining method are compared to introduce global analysis information into the Global/Regional Assimilation and Prediction Enhanced System mesoscale three-dimensional variational data assimilation system (GRAPES-Meso 3Dvar). Based on a spatial filter used to obtain a blended analysis, the blending method is weighted toward the T639 global analysis for scales larger than the cutoff wavelength of 1,200 km and toward the GRAPES mesoscale analysis for wavelengths below that. The constraining method considers the T639 global analysis data as an extra source of information to be added in the 3DVar cost function. The cloud-resolving GRAPES-Meso system (3 km resolution) with a 3 h analysis cycle update is chosen, and forecast experiments on an extreme precipitation event over the eastern part of China are presented. The comparison shows that the inclusion of large-scale information with both methods has a positive impact on the regional model, in which the 3 h background forecasts are slightly closer to the radiosonde observations. The results also show that both methods are effective in improving large-scale analysis while reserving the well-featured mesoscale information, leading to an enhancement in the balance and accuracy of the analysis. Subjective verification reveals that the introduction of large-scale information has a visible beneficial impact on the forecast of precipitation location and intensity. The methodologies and experiences presented in this paper could serve as a reference for ongoing efforts toward the development of multi-scale analysis in GRAPES-Meso. 相似文献
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Using analysis state to construct a forecast error covariance matrix in ensemble Kalman filter assimilation 总被引：1，自引：0，他引：1
Correctly estimating the forecast error covariance matrix is a key step in any data assimilation scheme. If it is not correctly estimated, the assimilated states could be far from the true states. A popular method to address this problem is error covariance matrix inflation. That is, to multiply the forecast error covariance matrix by an appropriate factor. In this paper, analysis states are used to construct the forecast error covariance matrix and an adaptive estimation procedure associated with the error covariance matrix inflation technique is developed. The proposed assimilation scheme was tested on the Lorenz-96 model and 2D Shallow Water Equation model, both of which are associated with spatially correlated observational systems. The experiments showed that by introducing the proposed structure of the forecast error covariance matrix and applying its adaptive estimation procedure, the assimilation results were further improved. 相似文献
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罗哲贤 《Acta Meteorologica Sinica》1994,(1)
The energy dispersion of a typhoon vortex and its effect on the typhoon motion are studied using an analyticalmethod of double-Fourier expansion as well as a numerical model in a β-plane nondivergent barotropic framework.The analytic model and the linear version of the numerical model give essentially the same result:the energy dispersionfrom a tropical cyclone can creat an L-H-L wave train to the east of the tropical cyclone.Three numerical experiments,integrated for 7 model days by the nonlinear model,indicate that the closed high in the wave train produces obvious in-fluence on the structure and movement of the tropical cyclone. 相似文献
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SENSITIVITY OF LANDFALLING TYPHOON STRUCTURE AND PRECIPITATION TO VARYING CLOUD MICROPHYSICAL PROCESSES 总被引：1，自引：0，他引：1
Typhoon KROSA in 2007 is simulated using GRAPES, a mesoscale numerical model, in which a two-parameter mixed-phase microphysics scheme is implanted. A series of numerical experiments are designed to test the sensitivity of landfalling typhoon structure and precipitation to varying cloud microphysics and latent heat release. It is found that typhoon track is sensitive to different microphysical processes and latent heat release. The cloud structures of simulated cyclones can be quite different with that of varying microphysical processes. Graupel particles play an important role in the formation of local heavy rainfall and the maintenance of spiral rainbands. Analysis reveals that the feedback of latent heat to dynamic fields can significantly change the content and distribution of cloud hydrometeors, thus having an impact on surface precipitation. 相似文献
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Luo Zhexian 《Acta Meteorologica Sinica》1994,8(1):51-59
The energy dispersion of a typhoon vortex and its effect on the typhoon motion are studied using an analytical method of double-Fourier expansion as well as a numerical model in a β-plane nondivergent barotropic framework.The analytic model and the linear version of the numerical model give essentially the same result:the energy dispersion from a tropical cyclone can creat an L-H-L wave train to the east of the tropical cyclone.Three numerical experiments,integrated for 7 model days by the nonlinear model,indicate that the closed high in the wave train produces obvious influence on the structure and movement of the tropical cyclone. 相似文献
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Representations of inverse covariances by differential operators 总被引：2，自引：1，他引：1
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. 相似文献
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目前多数快速更新循环同化系统在各分析时刻常使用固定的背景场误差协方差。为在快速更新循环同化系统中采用日变化的背景场误差协方差,基于RMAPS-ST系统分析了其夏季和冬季日变化背景场误差协方差特征,并进行了同化及预报对比试验。结果表明,该系统夏、冬两季的背景场误差协方差均呈现出明显的日变化特征,且夜间各变量(U、V、T、RH)的误差标准差与特征值均大于日间,反映模式系统夜间的预报误差大于日间;而夏季各变量误差标准差和特征值大于冬季,也说明系统在夏季的模式预报误差比冬季大;连续3 d的循环同化试验初步表明,采用日变化背景场误差协方差可以提高同化及预报效果。 相似文献
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在四维变分同化中运用集合协方差的试验 总被引：1，自引：1，他引：1
利用浅水方程模式和模式模拟资料进行数值试验比较3种不同的背景误差协方差矩阵处理方法对四维变分(4DVAR)资料同化的影响.3种背景误差协方差矩阵分别是:(1)对单一变量将背景误差协方差矩阵简化为对角矩阵;(2)将背景误差协方差矩阵的作用简化为高斯过滤;(3)由预报集合生成背景误差协方差矩阵并利用奇异值分解技术解决矩阵的求逆.通过一系列数值试验,比较不同观测密度、不同观测误差下3种背景误差协方差处理方法对4DVAR同化效果的影响.结果表明,背景误差协方差的结构对4DVAR有重大影响.当观测资料的空间密度不够高时,采用对角矩阵得不到满意的结果.高斯过滤方案可以明显改善同化结果,但是对背景误差特征长度比较敏感.第3种方法采用的背景误差协方差矩阵是流型依赖的,而且并不以显式的方式出现在目标函数中.避免了对它求逆的复杂运算.由于做了降维处理,在观测点的密度较低和观测误差较大时可望取得较好的同化结果,同化效果较为稳定. 相似文献
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在集合卡尔曼滤波方法中, 根据预报集合统计提供的依流型而变的预报误差协方差对同化起到决定性的作用。但在集合样本容量不足及模式存在系统误差时, 由预报集合估计的预报误差协方差会出现明显偏差。既要减小这种估计偏差对同化产生的影响而又不增加计算量, 一种可供选择的方法是将定常或准定常的高斯型预报误差协方差和由预报集合估计的预报误差协方差加权平均用于集合卡尔曼滤波同化。利用浅水方程模式, 通过观测系统模拟试验检验在不同的模式误差、 集合成员数以及观测密度条件下, 将这种混合预报误差协方差矩阵用于在集合平方根滤波的效果。试验结果表明, 当预报集合成员数较多而模式又无误差时, 不必采用混合的预报误差协方差矩阵, 否则, 采用混合的预报误差协方差矩阵都有可能改进分析和预报。混合预报误差协方差的最优的权重系数与模式误差关系密切, 模式误差越大, 定常预报误差协方差的权重越大。最优的权重系数与集合成员数及观测密度也有一定关系。 相似文献
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MM5三维变分系统在北京地区冷暖季背景场误差的对比分析 总被引：2，自引：2，他引：2
NMC方法是目前较广泛采用的一种对模式背景场误差协方差进行统计分析的一种方法。本文根据积累的2002年8月份和2003年2月份各一个月模式预报结果,采用NMC方法,计算了中尺度模式MM5V3在北京地区的冷暖季背景场误差,详细给出其气候统计特征。通过对比分析发现,背景场误差特征对于不同的模式变量、水平分辨率、垂直层各不相同,冷暖季背景场误差也有不同的特征,其差别主要表现在风场。这些特征与模式模拟区域的平均天气状况相对应,同化应该在各模式区域分别进行。MM5三维变分系统在北京地区的实际应用中,应发展根据实际季节变换背景场误差协方差矩阵的方法。 相似文献
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基于资料同化集合设计了流依赖球面小波背景场误差协方差模型中背景误差方差和局地垂直相关协方差的统计计算方法。为了提高背景误差方差的估计精度,采用客观滤波技术来减少因集合样本个数不足而引入的随机取样噪声。最后在银河四维变分同化业务系统(YH4DVar)上设计了集合资料同化的试验系统,以流依赖背景误差方差为重点验证了模型的有效性。结果表明:基于流依赖球面小波背景误差协方差模型能够有效估计出随天气状态变化的背景场误差方差,对台风等剧烈变化的天气过程的同化分析和预报都具有一定的正效果。 相似文献
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构造合理的背景场误差协方差是做好资料同化的关键。分析了背景误差协方差中变量相关关系在台风季节和非台风季节隐含的不同动力平衡特征,并讨论其对台风同化和预报的影响。分析发现,与非台风季节相比,在台风季节温度与非平衡速度势具有更强的动力相关性,拟相对湿度与其他控制变量的相关性也更显著。这些动力相关性在背景场误差中协方差的引入,将在同化分析过程中使得观测信息可以合理地对同化分析场产生影响。台风循环同化和预报的结果验证了对变量平衡特征的分析:背景误差协方差中新平衡关系的建立,对同化和预报有较大的正面影响,尤其是相对湿度和其他控制变量相关的建立,明显改善了台风路径、强度和降水的预报效果。 相似文献
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利用中尺度WRF数值模式及WRF三维变分同化系统,在对比试验的基础上,选取了适合本地的积云过程、微物理过程和辐射过程的方案组合;选择了NCEP/GFS作为模式的背景场;统计计算了以云南为中心的区域背景误差协方差并替换了三维变分同化系统中原有的背景误差协方差;同时,考虑模式底层高度与地面观测站高度的差异,进行了地面资料地形订正.通过上述试验研究,建立了本地化的中尺度WRF数值预报业务系统,该系统能较好地刻画本地下垫面的动力和热力状况,预报能力有明显改善. 相似文献