Seismic random noise attenuation and signal-preserving by multiple directional time-frequency peak filtering

Time-frequency peak filtering (TFPF) is an effective method for seismic random noise attenuation. The linearity of the signal has a significant influence on the accuracy of the TFPF method. The higher the linearity of the signal to be filtered is, the better the denoising result is. With this in mind, and taking the lateral coherence of reflected events into account, we do TFPF along the reflected events to improve the degree of linearity and enhance the continuity of these events. The key factor to realize this idea is to find the traces of the reflected events. However, the traces of the events are too hard to obtain in the complicated field seismic data. In this paper, we propose a Multiple Directional TFPF (MD–TFPF), in which the filtering is performed in certain direction components of the seismic data. These components are obtained by a directional filter bank. In each direction component, we do TFPF along these decomposed reflected events (the local direction of the events) instead of the channel direction. The final result is achieved by adding up the filtering results of all decomposition directions of seismic data. In this way, filtering along the reflected events is implemented without accurately finding the directions. The effectiveness of the proposed method is tested on synthetic and field seismic data. The experimental results demonstrate that MD–TFPF can more effectively eliminate random noise and enhance the continuity of the reflected events with better preservation than the conventional TFPF, curvelet denoising method and F–X deconvolution method.     

Assimilating Best Track Minimum Sea Level Pressure Data Together with Doppler Radar Data Using an Ensemble Kalman Filter for Hurricane Ike (2008) at a Cloud-Resolving Resolution

Extending an earlier study, the best track minimum sea level pressure (MSLP) data are assimilated for landfalling Hurricane Ike (2008) using an ensemble Kalman filter (EnKF), in addition to data from two coastal ground-based Doppler radars, at a 4-km grid spacing. Treated as a sea level pressure observation, the MSLP assimilation by the EnKF enhances the hurricane warm core structure and results in a stronger and deeper analyzed vortex than that in the GFS (Global Forecast System) analysis; it also improves the subsequent 18-h hurricane intensity and track forecasts. With a 2-h total assimilation window length, the assimilation of MSLP data interpolated to 10-min intervals results in more balanced analyses with smaller subsequent forecast error growth and better intensity and track forecasts than when the data are assimilated every 60 minutes. Radar data are always assimilated at 10-min intervals. For both intensity and track forecasts, assimilating MSLP only outperforms assimilating radar reflectivity (Z) only. For intensity forecast, assimilating MSLP at 10-min intervals outperforms radar radial wind (Vr) data (assimilated at 10-min intervals), but assimilating MSLP at 60-min intervals fails to beat Vr data. For track forecast, MSLP assimilation has a slightly (noticeably) larger positive impact than Vr(Z) data. When Vr or Z is combined with MSLP, both intensity and track forecasts are improved more than the assimilation of individual observation type. When the total assimilation window length is reduced to 1h or less, the assimilation of MSLP alone even at 10-min intervals produces poorer 18-h intensity forecasts than assimilating Vr only, indicating that many assimilation cycles are needed to establish balanced analyses when MSLP data alone are assimilated; this is due to the very limited pieces of information that MSLP data provide.     

Effect of doubling the ensemble size on the performance of ensemble prediction in the warm season using MOGREPS implemented at the KMA

Using the Met Office Global and Regional Ensemble Prediction System (MOGREPS) implemented at the Korea Meteorological Administration (KMA), the effect of doubling the ensemble size on the performance of ensemble prediction in the warm season was evaluated. Because a finite ensemble size causes sampling error in the full forecast probability distribution function (PDF), ensemble size is closely related to the efficiency of the ensemble prediction system. Prediction capability according to doubling the ensemble size was evaluated by increasing the number of ensembles from 24 to 48 in MOGREPS implemented at the KMA. The initial analysis perturbations generated by the Ensemble Transform Kalman Filter (ETKF) were integrated for 10 days from 22 May to 23 June 2009. Several statistical verification scores were used to measure the accuracy, reliability, and resolution of ensemble probabilistic forecasts for 24 and 48 ensemble member forecasts. Even though the results were not significant, the accuracy of ensemble prediction improved slightly as ensemble size increased, especially for longer forecast times in the Northern Hemisphere. While increasing the number of ensemble members resulted in a slight improvement in resolution as forecast time increased, inconsistent results were obtained for the scores assessing the reliability of ensemble prediction. The overall performance of ensemble prediction in terms of accuracy, resolution, and reliability increased slightly with ensemble size, especially for longer forecast times.     

Ensemble data assimilation in a simple coupled climate model: The role of ocean-atmosphere interaction

A conceptual coupled ocean-atmosphere model was used to study coupled ensemble data assimilation schemes with a focus on the role of ocean-atmosphere interaction in the assimilation. The optimal scheme was the fully coupled data assimilation scheme that employs the coupled covariance matrix and assimilates observations in both the atmosphere and ocean. The assimilation of synoptic atmospheric variability that captures the temporal fluctuation of the weather noise was found to be critical for the estimation of not only the atmospheric, but also oceanic states. The synoptic atmosphere observation was especially important in the mid-latitude system, where oceanic variability is driven by weather noise. The assimilation of synoptic atmospheric variability in the coupled model improved the atmospheric variability in the analysis and the subsequent forecasts, reducing error in the surface forcing and, in turn, in the ocean state. Atmospheric observation was able to further improve the oceanic state estimation directly through the coupled covariance between the atmosphere and ocean states. Relative to the mid-latitude system, the tropical system was influenced more by ocean-atmosphere interaction and, thus, the assimilation of oceanic observation becomes more important for the estimation of the ocean and atmosphere.     

地面气象测报业务试题库自动化管理系统

将地面气象观测规范、地面气象观测、气象学等多项知识形成题库,利用VB6编程、Access 2003数据库及Word 2003文字处理软件,研制了地面气象测报业务试题库自动化管理系统,实现了以下主要功能:用户管理、数据库管理、试题库维护、自动生成试卷、试卷编辑打印。着重阐述该系统的设计思路、技术方法、功能实现及使用效果。     

星载GPS自主定轨的长期稳定性

通过模拟长达100天的星载GPS伪距观测资料,进行卡尔曼滤波定轨仿真计算．重点研究：1)采用简化的动力学模型与简化状态转移矩阵,是否保证滤波的长期稳定性；2)模型误差矩阵Q的选取对滤波定轨精度的影响；3)与事后最小二乘批处理相比较,在简化模型下自主定轨的精度．同时给出了相应的结论．     

An acousto-optical imaging spectrophotometer for astrophysical observations

We present the results of our tests of an acousto-optical imaging spectrophotometer with a CCD detector for astronomical observations. The tunable acousto-optical filter, based on a paratellurite single crystal with a 13 Å pass band operates in the wavelength range 6300–11000 Å. We obtained image spectra for the planetary nebula NGC 7027 in the Hα line and for Saturn in the methane absorption band, as well as Hα and continuum images for the nuclear region of the Seyfert galaxy NGC 1068.     

基于CC的防火墙安全功能分析

防火墙是网络安全的核心手段。依据基于CC（Common Criteria）制订的国家标准——包过滤防火墙安全技术要求和应用级防火墙安全技术要求，提出每项安全功能要求对应的实际安全措施，并分析当前防火墙未实现的安全功能要求。     

CHARACTERIZATION OF THE EFFECT OF PEAK SHIFTS ON THE PERFORMANCE OF THE KALMAN FILTER IN MULTICOMPONENT ANALYSES

The effect of peak shifts on the performance of a Kalman filter multicomponent analysis algorithm hasbeen investigated.A series of Gaussian test systems were employed to characterize the concentrationestimation errors and the morphology of the on-line residuals(the innovations sequence).Both forwardand reverse filters were used in the generation of the innovations sequences.It was found that thedifference between the forward and reverse innovations sequences gave an accurate indication of thedirection and magnitude of the peak shift.A series of overlapped two-component systems were alsoinvestigated.Again,a correlation between the difference innovations and the degree of the responseshift was observed.The behavior of the Katman filter in fitting the shifted fluorescence emissionspectrum of benzo[a]pyrene was also examined.The response for henzo[a]pyrene in cyclohexanesolution was compared to that obtained on the surface of a reversed phase thin layer chromatographyplate.A red shift of 4 nm was detected for the surface spectrum by observing the difference innovationssequence.This approach holds promise for correction of response shifts in multicomponent systems.     

雷电滤波器

本文叙述了两种雷电滤波器的工作原理及其使用方法。