基于噪声随机模型的加权观测融合方法

信息融合技术中,在各局部传感器的有色观测噪声为一阶AR模型的情况下,可以利用观测扩增方法消除有色噪声的影响,得到最优加权观测融合方程,从而实现状态的最优滤波解。对于有色观测噪声为MA或ARMA模型的情况,观测扩增方法不再适用。提出了基于有色观测噪声随机模型级数展开的方法,求解出各局部传感器有色观测噪声的方差,并利用该方差对加权观测融合滤波器进行了构造。通过计算实例证明,该方法不仅适用于观测噪声为AR模型,同时适用于噪声MA或ARMA模型。     

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A Nonlinear Representation of Model Uncertainty in a Convective-Scale Ensemble Prediction System

How to accurately address model uncertainties with consideration of the rapid nonlinear error growth characteristics in a convection-allowing system is a crucial issue for performing convection-scale ensemble forecasts. In this study, a new nonlinear model perturbation technique for convective-scale ensemble forecasts is developed to consider a nonlinear representation of model errors in the Global and Regional Assimilation and Prediction Enhanced System(GRAPES)Convection-Allowing Ensemble Predi...     

Errors and correction of precipitation measurements in China

In order to discover the range of various errors in Chinese precipitation measurements and seek a correction method, 30 precipitation evaluation stations were set up countrywide before 1993. All the stations are reference stations in China. To seek a correction method for wind-induced error, a precipitation correction instrument called the ＂horizontal precipitation gauge＂ was devised beforehand. Field intercomparison observations regarding 29,000 precipitation events have been conducted using one pit gauge, two elevated operational gauges and one horizontal gauge at the above 30 stations. The range of precipitation measurement errors in China is obtained by analysis of intercomparison measurement results. The distribution of random errors and systematic errors in precipitation measurements are studied in this paper. A correction method, especially for wind-induced errors, is developed. The results prove that a correlation of power function exists between the precipitation amount caught by the horizontal gauge and the absolute difference of observations implemented by the operational gauge and pit gauge. The correlation coefficient is 0.99. For operational observations, precipitation correction can be carried out only by parallel observation with a horizontal precipitation gauge. The precipitation accuracy after correction approaches that of the pit gauge. The correction method developed is simple and feasible.     

地理数据的不确定性研究

目前地理数据不确定性是制约遥感(RS)与地理信息系统(GIS)发展的主要因素之一,直接影响地理数据分析的空间决策支持系统输出的可信度。如何识别、量化、跟踪、减少、可视化表达地理数据不确定性,已引起地理信息科学领域专家的广泛重视,成为3S领域新的研究热点。本文先阐述地理数据不确定性研究的重要性,然后分析地理数据不确定性产生的根源,最后提出开展地理数据不确定性研究的方法及地理数据不确定性的优先研究领域。     

可达性度量方法及应用研究进展评述

可达性一直是地理学、土木建筑工程设计、交通运输经济学等学科的研究热点。已有的各 种可达性度量方法目前已广泛应用于交通网络与城镇发展研究、交通基础设施的区域经济效应 评价、选址分析、园林景观规划、社会文化等多个研究领域。随着应用需求的持续加大和技术研究 的不断深入, 可达性度量方法也在快速发展, 其度量体系正在形成。本文首先从两个层面对可达 性的涵义进行全面阐述; 在此基础上, 从网络特性的角度对拓扑法、距离法、累积机会法、等值线 法、重力模型法、平衡系数法、时空法、效用法等目前常用的可达性度量方法进行系统分类, 并且 从可达性影响因素入手对各种度量方法进行综合比较与评述; 然后, 针对不同的应用领域, 对各 种度量方法的应用研究现状进行详细论述与剖析; 最后, 对可达性研究的发展方向进行深入讨论 与展望。     

倾斜实景模型和LiDAR点云数据相融合的不动产测量新方法

不动产地籍测量是一项基础性的测绘工作,地籍测量技术与方法的良性发展不仅能够最大限度地提升我国土地利用率,还能为获取高精度的空间数据提供高效便捷的手段.针对传统全站仪与GPS RTK组合地籍测量作业效率低、人力财力耗费大的缺点,本文依托陕南某地的地籍和不动产权籍调查项目,提出了一种地面三维激光扫描技术和倾斜摄影测量技术相...     

Pluie ou neige? Dispositif de mesures pluviographiques dans les Andes de Bolivie et interprétation des enregistrements/Rainfall or snowfall? Device for measuring the precipitation phase in the Bolivian Andes and analysis of the records

Abstract

Abstract The knowledge of the precipitation phase, solid or liquid, is important in high mountains, in order to use models of water and energy balances. During an experiment led in the Bolivian Andes, a complete weather station was installed at an altitude close to 4800 m, including two raingauge recorders, the first one with added antifreeze and oil, based on weight measurement, and the other one with tipping buckets. This device allowed a realistic partition of the liquid and solid phases in this region of tropical mountains, where the observed snow pack at the ground level is strongly influenced by the extremely high solar radiation and where the snow cover is ephemeral. The automation of the ?raingauges? method, compared with several other classical methods, shows satisfactory results.     

Assessing uncertainties in a conceptual water balance model using Bayesian methodology / Estimation bayésienne des incertitudes au sein d’une modélisation conceptuelle de bilan hydrologique

Abstract

Abstract The aim of this study was to estimate the uncertainties in the streamflow simulated by a rainfall–runoff model. Two sources of uncertainties in hydrological modelling were considered: the uncertainties in model parameters and those in model structure. The uncertainties were calculated by Bayesian statistics, and the Metropolis-Hastings algorithm was used to simulate the posterior parameter distribution. The parameter uncertainty calculated by the Metropolis-Hastings algorithm was compared to maximum likelihood estimates which assume that both the parameters and model residuals are normally distributed. The study was performed using the model WASMOD on 25 basins in central Sweden. Confidence intervals in the simulated discharge due to the parameter uncertainty and the total uncertainty were calculated. The results indicate that (a) the Metropolis-Hastings algorithm and the maximum likelihood method give almost identical estimates concerning the parameter uncertainty, and (b) the uncertainties in the simulated streamflow due to the parameter uncertainty are less important than uncertainties originating from other sources for this simple model with fewer parameters.     

Uncertainty,entropy, scaling and hydrological stochastics. 1. Marginal distributional properties of hydrological processes and state scaling / Incertitude,entropie, effet d'échelle et propriétés stochastiques hydrologiques. 1. Propriétés distributionnelles marginales des processus hydrologiques et échelle d'état

Abstract

The well-established physical and mathematical principle of maximum entropy (ME), is used to explain the distributional and autocorrelation properties of hydrological processes, including the scaling behaviour both in state and in time. In this context, maximum entropy is interpreted as maximum uncertainty. The conditions used for the maximization of entropy are as simple as possible, i.e. that hydrological processes are non-negative with specified coefficients of variation (CV) and lag one autocorrelation. In this first part of the study, the marginal distributional properties of hydrological variables and the state scaling behaviour are investigated. Application of the ME principle under these very simple conditions results in the truncated normal distribution for small values of CV and in a nonexponential type (Pareto) distribution for high values of CV. In addition, the normal and the exponential distributions appear as limiting cases of these two distributions. Testing of these theoretical results with numerous hydrological data sets on several scales validates the applicability of the ME principle, thus emphasizing the dominance of uncertainty in hydrological processes. Both theoretical and empirical results show that the state scaling is only an approximation for the high return periods, which is merely valid when processes have high variation on small time scales. In other cases the normal distributional behaviour, which does not have state scaling properties, is a more appropriate approximation. Interestingly however, as discussed in the second part of the study, the normal distribution combined with positive autocorrelation of a process, results in time scaling behaviour due to the ME principle.