差分观测与伪距观测的定位精度

严格论证了在对空间或地面目标的定位中,利用伪距测量观测模型的几何因子大于用台站间一次差分观测模型的几何因子.此外,台站间完全差分测量观测的定位精度优于不完全测量情形的定位精度.这些结果给人们在实际工作中采取何种定位方式提供了可靠的理论依据.     

REVIEWS OF GEOGRAPHIC SOFTWARE

Reviews of geographic software in this article: DEMO-GRAPHICS: WORLD POPULATIONS AND PROJECTIONS. ESP GAUSS. CEMODEL S. Damus LIMDEP. William H. Greene MICROSTAT 4.1 OTIS PCIPS. (Personal Computer Image Processing System) . H.J. Meyers and R. Bernstein. REGRESSION ANALYSIS OF TIME SERIES (RATS) SPSS/PC+ URBAN DATA MANAGEMENT SOFTWARE (UDMS)     

Application of stress release models to historical earthquakes from North China

Univariate and multivariate stress release models are fitted to historical earthquake data from North China. It is shown that a better fit is obtained by treating separately the Eastern part of the region, including the North China Plain and Bohai Sea, and the Western part of the region, including the Ordos Plateau and its Eastern boundary. Further improvement is obtained by fitting the large events (M7.6) and smaller events in the Western region by different stress release models. The comparisons are made by computing the likelihoods of the fitted models and discounting the number of parameters used by Akaike's AIC criterion. The models are used to develop long-term risk scenarios for the East and West regions.     

基于分布式水文模拟的三峡区间洪水预报(Ⅰ)——模型构建及验证

长江三峡区间因暴雨形成的洪水峰高量大,对三峡水库的防洪安全和运行调度的影响很大.本论文依据三峡地区的地形地貌特征,采用基于GIS的机理性分布式水文模型,来模拟三峡区间入库洪水,以尽量减少洪水预报中的不确定性.利用近期建成的78个自动雨量站网监测的小时降雨信息作为模型的输入,对模型参数进行了率定和验证,结果表明:大多数洪水过程的模拟精度较好,但也有的模拟结果较差,其中降雨信息缺失是洪水预报不确定性的主要来源.     

Study on short-range numerical forecasting of ocean current in the East China Sea——Ⅰ Basic problems of ocean current forecasting and structure of the models

Ocean current forecasting is still in explorative stage of study. In the study, we face some problems that have not been met before. The solving of these problems has become fundamental premise for realizing the ocean current forecasting. In the present paper are discussed in depth the physical essence for such basic problems as the predictability of ocean current, the predictable currents, the dynamical basis for studying respectively the tidal current and circulation, the necessity of boundary model, the models on regions with different scales and their link. The foundations and plans to solve the problems are demonstrated. Finally a set of operational numerical forecasting system for ocean current is proposed.     

1990年12月14日台湾强震的预报判据

本文运用福建省沿海气象要素的异常变化,作台湾省的中、短期地震预报,取得了成功的效果。采用长乐历年各月14时最低气压的距平值,作台湾省未来4～7个月内出现强震的预报依据,并采用热异常进行短临跟踪。当秋冬季节连续4d 长乐、福州、台北的气温均比广州累计高出10℃时,预报未来1～5d 台湾省出现7级强震。又根据近百年来台湾发生的强震,统计其活动季节,得到近20年来7级地震发生的时间,绝大部分在9～12月。     

莱州湾温带风暴潮预报研究

本文依据莱州湾羊角沟、夏营两站建国以来的风暴增水资料，对莱州湾建国后发生的风暴潮进行了统计分析，并探讨了温带风暴潮产生的物理机制，此外还对莱州湾温带风暴增水以及诱发增水的天气形势进行了分析分类。在此基础上建立了莱州湾温带风暴潮统计预报方法，并在作业预报中对模型进行了检验，取得较为理想的效果。     

A Compact Explicit Difference Scheme of High Accuracy for Extended Boussinesq Equations

Presented here is a compact explicit difference scheme of high accuracy for solving the extended Boussinesq equations.For time discretization,a three-stage explicit Runge-Kutta method with TVD property is used at predicting stage,a cubic spline function is adopted at correcting stage,which made the time discretization accuracy up to fourth order;For spatial discretization,a three-point explicit compact difference scheme with arbitrary order accuracy is employed.The extended Boussinesq equations derived by Beji and Nadaoka are solved by the proposed scheme.The numerical results agree well with the experimental data.At the same time,the comparisons of the two numerical results between the present scheme and low accuracy difference method are made,which further show the necessity of using high accuracy scheme to solve the extended Boussinesq equations.As a valid sample,the wave propagation on the rectangular step is formulated by the present scheme,the modelled results are in better agreement with the experimental data than those of Kittitanasuan.     

Neural network for wave forecasting among multi-stations

Unlike in the open sea, the use of wind information for forecasting waves may encounter more ambiguous uncertainties in the coastal or harbor area due to the influence of complicated geometric configurations. Thus this paper attempts to forecast the waves based on learning the characteristics of observed waves, rather than the use of the wind information. This is reported in this paper by the application of the artificial neural network (ANN), in which the back-propagation algorithm is employed in the learning process for obtaining the desired results. This model evaluated the interconnection weights among multi-stations based on the previous short-term data, from which a time series of waves at a station can be generated for forecasting or data supplement based on using the neighbor stations data. Field data are used for testing the applicability of the ANN model. The results show that the ANN model performs well for both wave forecasting and data supplement when using a short-term observed wave data.