Algorithms for automatic,real-time tsunami detection in wind–wave measurements Part I: Implementation strategies and basic tests

Several, although not all, wind–wave gages are equipped with sensors capable of detecting sea-level oscillations within the tsunami frequency band. The present paper looks at the algorithms to be implemented in the software of these gages in order to automatically perform the real-time detection of a possible tsunami within recorded signals. In particular, a new algorithm is proposed and tested. The first part of the paper concentrates on the algorithms' characteristics, implementation strategies and basic testing. First of all, the situations in which wind–wave measurements are either essential, or useful for real-time tsunami detection are discussed. In the second place, already existing algorithms are recalled, specifying their characteristics and fields of application. Then, the characteristics of the new proposed algorithm – mainly based on an infinite impulse response, time domain filter – are illustrated and analyzed. Performance and efficiency of the considered algorithms are compared using synthetic time series. The second part of the paper discusses the algorithms' use in the framework of Tsunami Early Warning Systems (TEWS), testing them in actual cases.     

Seismic random noise attenuation by time-frequency peak filtering based on joint time-frequency distribution

Time-Frequency Peak Filtering (TFPF) is an effective method to eliminate pervasive random noise when seismic signals are analyzed. In conventional TFPF, the pseudo Wigner–Ville distribution (PWVD) is used for estimating instantaneous frequency (IF), but is sensitive to noise interferences that mask the borderline between signal and noise and detract the energy concentration on the IF curve. This leads to the deviation of the peaks of the pseudo Wigner–Ville distribution from the instantaneous frequency, which is the cause of undesirable lateral oscillations as well as of amplitude attenuation of the highly varying seismic signal, and ultimately of the biased seismic signal. With the purpose to overcome greatly these drawbacks and increase the signal-to-noise ratio, we propose in this paper a TFPF refinement that is based upon the joint time-frequency distribution (JTFD). The joint time-frequency distribution is obtained by the combination of the PWVD and smooth PWVD (SPWVD). First we use SPWVD to generate a broad time-frequency area of the signal. Then this area is filtered with a step function to remove some divergent time-frequency points. Finally, the joint time-frequency distribution JTFD is obtained from PWVD weighted by this filtered distribution. The objective pursued with all these operations is to reduce the effects of the interferences and enhance the energy concentration around the IF of the signal in the time-frequency domain. Experiments with synthetic and real seismic data demonstrate that TFPF based on the joint time-frequency distribution can effectively suppress strong random noise and preserve events of interest.     

关于集合Kalman滤波的理论和方法的发展

随着同化方法的不断的发展，一种新的资料同化方法——集合Kalman滤波正在兴起。简单地回顾了同化方法的发展，探讨了集合Kalman滤波的特点。同时，还介绍了集合Kalman滤波发展的过程以及指出目前所面临的问题和未来的发展趋势。     

位场向下延拓迭代法收敛性分析及稳健向下延拓方法研究

地磁导航作为一种新的无源导航方式,具有重要的国防意义.构建空间地磁数据库是实现地磁导航的基础,位场延拓是解决地磁数据库构建的有效方法.积分-迭代法是一种解决位场大深度向下延拓的实用方法.本文着重对积分-迭代法的收敛性进行了分析,从数学角度证明积分-迭代法能够收敛到直接下延法理论解.同时对积分-迭代法的抗干扰性进行了初步分析,当观测数据含有噪声时,积分-迭代过程中使得噪声得到累加,影响延拓数据的精度.本文利用正则化方法和递增型维纳滤波方法,提出了波数域位场向下延拓新算法.模型检验表明,新算法稳定、抗干扰能力强、计算速度快.     

用水位恢复数据反演越流承压含水层参数

水文地质勘测中,由于水位恢复阶段没有人力和机械因素干扰,由测量数据可以画出平滑的曲线,更适宜于分析水文地质参数,但经典非稳定流Theis公式和Theis水位恢复法所依据的若干假设条件在实际中难以满足。针对越流承压含水层具有补给条件而很快稳定以及非稳定抽水阶段流量常“抖动”的特点,论证了利用稳定流量和Hantush-Jacob越流模型计算的可行性,并用扩展的卡尔曼滤波器反演水文地质参数,经文献中历史数据和实地抽水试验检验结果表明,由该方法反演的预测值和实测值吻合良好。     

定位参数抗差估计的无偏性

根据抗差估计中误差的最基本假设—对称分布 ,考虑到ρ函数的条件及把反对称估计作为抗差估计计算迭代的初始值 ,验证了定位参数的抗差估计值也一定是反对称估计 ,满足无偏性条件 ,得到定位参数的抗差估计是无偏估计。     

多普勒雷达风场反演VAP方法的资料预处理

在分析了三类单多普勒雷达反演风场方法的基础上, 认为VAP方法是近期内可望在业务中应用的方法, 并指出VAP方法的关键是能否将原始资料中的中-U及以上尺度的风场信息过滤出来, 以消除中-V尺度以下风场信息对反演结果的影响.为此提出了二维区域滑动低通滤波方法对资料进行预处理.此外还对VAP方法的风速计算公式进行了改进以减小计算误差.     

定位参数抗差估计的无偏性

根据抗差估计中误差的最基本假设一对称分布,考虑到ρ函数的条件及把反对称估计作为抗差估计计算迭代的初始值,验证了定位参数的抗差估计值也一定是反对称估计,满足无偏性条件,得到定位参数的抗差估计是无偏估计.     

利用MM5模式输出产品制作空气质量预报方法探讨

根据2004年中尺度数值预报模式MM5输出产品和临沂市环境监测中心逐日监测资料建立了各污染物浓度预报方程,在2005年夏季的试报中,该方程的试报效果较差,其预报准确率明显低于其历史拟合率。为了提高预报准确率,利用逐步回归筛选的因子及统计模型研究中的有关数据,探讨了使用卡尔曼滤波方法制作空气污染物浓度预报的问题。分析发现,利用卡尔曼滤波方法制作空气质量预报可以取得比较满意的效果。     

集合Kalman滤波同化理论及其数值试验

集合Kalman滤波用于数值试验有着坚实的理论基础.本文介绍了集合Kalman滤波理论及其技术实现, 在此基础上搭建了集合Kalman滤波同化系统, 用MM5模式同化了实测探空资料并作了48 h的预报试验, 并将预报结果与实测值及4D VAR同化的结果作了比较.试验结果表明: 集合Kalman滤波同化探空资料可以改进MM5模式的预报效果, 且集合Kalman滤波同化后模式的预报效果明显优于4D VAR同化后模式的预报效果.