地震数据采集器中△-∑AD转换器512kHz数据流的仿真

根据△-∑AD转换器原理，通过编程将给定的输入信号转换为1位串行△-∑数据流。用此数据流可以仿真地震数据采集器中的滤波抽样过程，检验设计构造的各级滤波参数能否满足地震观测的需要。为了证明该仿真程序的正确性，本文介绍了利用CS5376A公布的数字滤波参数对数据流进行滤波验证。     

逐步逼近曲化平方法研究

位场资料的常规处理解释方法是建立在平面数据理论之上的，然而实际的位场数据大多为曲面数据，若把曲面数据当成平面数据进行处理，必然导致很大的误差，因此有必要进行“曲化平”处理. 曲化平目前存在的主要问题是计算精度低、计算量大，因此，研究快速、精度高且适合大数据量处理的曲化平方法具有重要的价值. 本文在已有的泰勒级数曲化平方法基础上提出了逐步逼近技术和平均平面技术，使得曲面位场资料处理的精度得到了很大提高. 最后通过理论模型和实际资料的处理验证了该方法的应用效果.     

京津冀地区地下流体数字化观测数据完整率及其地震前兆监测有效性的调查与分析

在北京、天津、河北二市一省部分地区抽样调查了13口井水位、11口井水温、5口井气氡、2口井气汞、2口井氦气数字化观测现状,统计分析了其数据完整率及观测断记次数与数据缺失量;在调查观测数据断记及其原因的基础上,进一步统计分析了数据缺失的主要原因,分析了连续完整的数据系列在地震前兆监测中的有效性。研究结果表明,除了氦气之外,水位、水温、气氡与气汞4大主要测项的运行,总体上是正常的;但多数井多数测项存在断记与数据缺失的问题,其主要原因是仪器故障与运行不正常,其次是停电、通信线路故障与雷击,此外还存在原因不明的断记与缺数的问题;以井统计,约有1/2的水位与水温观测井可在地震中期与短临前兆中发挥作用,而气氡、气汞等化学量观测只在地震短临前兆监测中,约有一半的井有可能发挥一定效能。     

Analysis and modeling of the seasonal South China Sea temperature cycle using remote sensing

The present paper describes the analysis and modeling of the South China Sea (SCS) temperature cycle on a seasonal scale. It investigates the possibility to model this cycle in a consistent way while not taking into account tidal forcing and associated tidal mixing and exchange. This is motivated by the possibility to significantly increase the model’s computational efficiency when neglecting tides. The goal is to develop a flexible and efficient tool for seasonal scenario analysis and to generate transport boundary forcing for local models. Given the significant spatial extent of the SCS basin and the focus on seasonal time scales, synoptic remote sensing is an ideal tool in this analysis. Remote sensing is used to assess the seasonal temperature cycle to identify the relevant driving forces and is a valuable source of input data for modeling. Model simulations are performed using a three-dimensional baroclinic-reduced depth model, driven by monthly mean sea surface anomaly boundary forcing, monthly mean lateral temperature, and salinity forcing obtained from the World Ocean Atlas 2001 climatology, six hourly meteorological forcing from the European Center for Medium range Weather Forecasting ERA-40 dataset, and remotely sensed sea surface temperature (SST) data. A sensitivity analysis of model forcing and coefficients is performed. The model results are quantitatively assessed against climatological temperature profiles using a goodness-of-fit norm. In the deep regions, the model results are in good agreement with this validation data. In the shallow regions, discrepancies are found. To improve the agreement there, we apply a SST nudging method at the free water surface. This considerably improves the model’s vertical temperature representation in the shallow regions. Based on the model validation against climatological in situ and SST data, we conclude that the seasonal temperature cycle for the deep SCS basin can be represented to a good degree. For shallow regions, the absence of tidal mixing and exchange has a clear impact on the model’s temperature representation. This effect on the large-scale temperature cycle can be compensated to a good degree by SST nudging for diagnostic applications.     

Analysis of Fog Probability from a Combination of Satellite and Ground Observation Data

The Cloud Type product, developed by the Satellite Application Facility to support to nowcasting and very short-range forecasting (SAFNWC) of EUMETSAT and based on Météosat-8/SEVIRI, identifies cloud categories, and especially low and very low clouds which are first estimates of areas where fog is likely to occur. This cloud type is combined with precipitation information from radar data and with hourly diagnostic analyses of 2-metre relative humidity and 10-metre wind to elaborate an hourly analysis of fog probability. This analysis provides four levels of fog probability with a 3-kilometre horizontal resolution: No risk, low-level risk, medium-level risk and high-level risk. An evaluation of such fog probability analyses versus a one-year set of French hourly SYNOP reports shows encouraging results (potential of detection = 0.73 for low and medium and high-level risks), even if false alarm ratios remain high. Most of the non-detections occur at twilight and are due to satellite non-detections. Eventually, we show case studies that clearly illustrate the high potential of the method.     

台湾西南海域地震数据处理及天然气水合物地震属性

对台湾西南海域增生楔部位长排列多道地震数据进行地震成像、速度分析、AVO分析、AVO反演处理,获得了天然气水合物多属性地震特征.在偏移剖面上,BSR与海底近似平行,极性与海底相反,穿越沉积层.AVO分析显示,强BSR振幅部位,BSR振幅随偏移距增大而增大.精细速度分析表明强BSR振幅下方存在纵波低速层.对应于强BSR振幅部位,AVO反演的P波、G波为相对高负值区,位于P、G交会图的第三象限,该部位泊松比变化率为负值,横波反射系数接近于零.以上多属性地震特征均预示着该区域可能存在天然气水合物层,且天然气水合物层下方可能存在游离甲烷气层.     

基于网络的煤田地质资料信息管理系统的设计与开发

煤田地质资料是地质信息资源的载体，传统的资料管理模式已不能满足当代数字化和信息化社会的发展需求。利用SqlServer数据库，在ASP．net技术的支持下，借助MapXtreme2004平台，建立了青海省煤田地质资料信息管理系统。该系统采用B／S结构，实现了煤田地质资料的属性和图形的联合查询，以及各种类型的资料在Web浏览器中查阅。     

对建设水文数据仓库的初步研究

本文根据目前对水文信息的应用需求,提出了建设水文数据仓库的必要性。对数据仓库及相关技术作了简要介绍,结合水文数据实际状况和应用主题,提出了建设水文数据仓库的数据组织、基本体系结构和建设步骤等相关内容。     

数据挖掘技术在水文预报中的应用及水文预报发展趋势研究

数据挖掘作为知识发现过程中的重要步骤,是从大型数据库中提取未知的、有价值的和可操作性的关系、模式和趋势用于决策支持的过程。我国目前在防洪领域存在着大量水文数据,如何充分有效地利用各种智能算法对这些数据进行分析与挖掘,以形成相应的水文预报模型进行准确的水文预报是防洪决策支持系统完善和发展的重要方面。本文首先全面地介绍数据挖掘的功能分类及以数据挖掘为基础的水文预报体系,然后对数据挖掘技术在水文预报中的应用进行了探讨和研究。     

International Association of Geoanalysts' Protocol for the Certification of Geological and Environmental Reference Materials: A Supplement

The International Association of Geoanalysts (IAG) published a protocol for the certification of reference materials in close accord with the International Organisation for Standardisation (ISO) guidelines (Kane et al. 2003). This article supplements that protocol, providing additional discussion of best approaches for pre-selecting laboratories for participation in certification projects. This discussion also makes a distinction between inter-laboratory certifications, where n = 15 is the general standard, and expert laboratory certifications, where a much smaller number of laboratories will be deemed qualified to provide data of the quality needed for certification.