大气层对GPS信号传播影响的规律之探讨──关于广州地区大气层对GPS系统定位定时影响问题研究之二

大气层对ＧＰＳ信号的传播有时间延迟作用，时廷将影响ＧＰＳ系统的定位和定时精度，且随气象因素的变化而变化．本文根据３年有关的气象资料，采用大气指数模型分析了广州地区大气层随昼夜变化、季节变化和太阳活动变化对ＧＰＳ信号传播时延影响的变化规律．分析得知，在信号垂直传播时，大气层对ＧＰＳ信号传播的影响，用距离表示．最大时为２．６９１ｍ，最小时也会产生１．９９３ｍ的误差；如果信号斜传播，误差因仰角因素将更大．     

Travel time based approach for the assessment of vulnerability of karst groundwater: the Transit Time Method

Karst aquifers represent important water resources in many parts of the world. Unfortunately, karst aquifers are characterised by high contamination risks. This paper presents a travel time based method for the estimation of karst groundwater vulnerability. It considers (1) physics-based lateral flow within the uppermost weathered zone (epikarst) in a limestone-dominated region and (2) high velocities of vertical infiltration at discrete infiltration points (e.g. sinkholes) or lines (e.g. dry valleys, faults). Consequently, the Transit Time Method honours the actual flow path within the unsaturated zone of a karst aquifer system. A test site in Northern Jordan was chosen for the demonstration of the assessment technique, i.e. the catchment area of the Qunayyah Spring north of the capital Amman. The results demonstrate that zones of highest vulnerability lie within valleys and nearby main fault zones. It also reveals that regions, categorised as protected areas by other methods due to thick unsaturated zones, contribute to a major degree to the total risk.     

气溶胶光学厚度的时空变化

在大气中气溶胶微粒是一种重要的大气微量成分。气溶胶光学厚度也是大气校正所需的重要大气参数，同时也是海洋水色卫星主要的数据产品。由于气溶胶光学厚度的时空变化较大，所以如何准确获取大气校正和卫星数据产品真实性检验所需的气溶胶光学厚度则是至关重要的。在简述气溶胶光学性质的基础上，并结合2002年6月HY—1南海实验数据来阐述现场气溶胶光学厚度的准确获取。     

Time domain modelling of the transient asymmetric flooding of Ro-Ro ships

This work aims at contributing to improve knowledge on transient asymmetric flooding through theoretical and experimental research. First, a time domain theoretical model of ship motions and flooding is described. Results from experimental work are presented evidencing that transient asymmetric flooding may cause the capsizing of a Ro-Ro shaped barge. The theoretical model is used to predict the capsize of the Ro-Ro shaped barge. Reasonable agreement between experimental and theoretical results was found. Finally, a review of the European Gateway accident is given and the theoretical model is applied to the study of this type of accident. The conclusion is that this theoretical model, together with an accurate modelling of the flooding of machinery compartments, reproduces successfully the capsizing of the European Gateway due to transient asymmetric flooding. Therefore, the internal arrangement of Ro-Ro ships should be carefully studied at the design stage in order to avoid this phenomenon.     

Prediction of UT1–UTC,LOD and AAM χ<Subscript>3</Subscript> by combination of least-squares and multivariate stochastic methods

This article presents the application of a multivariate prediction technique for predicting universal time (UT1–UTC), length of day (LOD) and the axial component of atmospheric angular momentum (AAM χ ₃). The multivariate predictions of LOD and UT1–UTC are generated by means of the combination of (1) least-squares (LS) extrapolation of models for annual, semiannual, 18.6-year, 9.3-year oscillations and for the linear trend, and (2) multivariate autoregressive (MAR) stochastic prediction of LS residuals (LS + MAR). The MAR technique enables the use of the AAM χ ₃ time-series as the explanatory variable for the computation of LOD or UT1–UTC predictions. In order to evaluate the performance of this approach, two other prediction schemes are also applied: (1) LS extrapolation, (2) combination of LS extrapolation and univariate autoregressive (AR) prediction of LS residuals (LS + AR). The multivariate predictions of AAM χ ₃ data, however, are computed as a combination of the extrapolation of the LS model for annual and semiannual oscillations and the LS + MAR. The AAM χ ₃ predictions are also compared with LS extrapolation and LS + AR prediction. It is shown that the predictions of LOD and UT1–UTC based on LS + MAR taking into account the axial component of AAM are more accurate than the predictions of LOD and UT1–UTC based on LS extrapolation or on LS + AR. In particular, the UT1–UTC predictions based on LS + MAR during El Niño/La Niña events exhibit considerably smaller prediction errors than those calculated by means of LS or LS + AR. The AAM χ ₃ time-series is predicted using LS + MAR with higher accuracy than applying LS extrapolation itself in the case of medium-term predictions (up to 100 days in the future). However, the predictions of AAM χ ₃ reveal the best accuracy for LS + AR.     

Modeling the cyclic swelling pressure of mudrock using artificial neural networks

The stochastic nature of the cyclic swelling behavior of mudrock and its dependence on a large number of interdependent parameters was modeled using Time Delay Neural Networks (TDNNs). This method has facilitated predicting cyclic swelling pressure with an acceptable level of accuracy where developing a general mathematical model is almost impossible. A number of total pressure cells between shotcrete and concrete walls of the powerhouse cavern at Masjed–Soleiman Hydroelectric Powerhouse Project, South of Iran, where mudrock outcrops, confirmed a cyclic swelling pressure on the lining since 1999. In several locations, small cracks are generated which has raised doubts about long term stability of the powerhouse structure. This necessitated a study for predicting future swelling pressure. Considering the complexity of the interdependent parameters in this problem, TDNNs proved to be a powerful tool. The results of this modeling are presented in this paper.     

时间序列转折突变点检测的线性函数方法

根据转折突变的定义，在引入线性半截多项式的前提下，提出检测时间序列转折突变点的一种新方法。此方法不仅能找出时间序列中存在的多个转折突变点，而且使得检测到的突变点通过统计显著性检验。应用此方法对北半球1851—1990年年平均气温距平及其11年滑动平均序列，1901—1999年昆明5月降水及其11年滑动平均的降水序列分别进行了检测。发现北半球年平均气温距平在1879、1889、1939和1973年附近出现了年际转折突变，在1878、1888和1941年以及1972年出现了年代际尺度的转折突变；昆明5月雨量不存在年际转折突变点，但昆明5月雨量在1918、1966以及1978年附近出现了年代际尺度转折突变。