多普勒雷达观测在北京7.21暴雨数值模拟中的三维变分同化研究

基于背景误差的特征长度理论,研究调整背景误差水平分辨率对多普勒雷达资料三维变分同化的影响。首先利用NMC方法针对暴雨落区统计不同水平分辨率的背景误差协方差,分析两种不同分辨率的背景误差的结构特征,研究水平分辨率对背景误差特征长度的影响。将其应用于雷达资料同化中,研究背景误差水平分辨率变化对雷达资料同化的影响。结果表明:背景误差水平分辨率由27 km提高到3 km时,在大气低层体现出更细致的动力场信息,其动力场水平特征长度按水平分辨率的二次根递减,而温度场与水汽场水平特征长度变化不明显。在将不同分辨率的背景误差用于三维变分同化时,更高分辨率的背景误差可以在分析场增量中体现更细致的中小尺度信息,能够明显改善雷达径向速度资料同化效果,并在随后的暴雨数值模拟中雨量及其分布形态更接近实况。     

基于部分最小二乘岭估计的粗差定值定位

在利用部分最小二乘原理进行粗差定值定位时,模型的法方程矩阵可能存在病态性,使得到的粗差定值定位结果不可靠。文中针对观测数据包含多个粗差且法方程病态问题,利用岭估计处理病态问题,建立部分最小二乘岭估计的粗差定值定位方法,给出粗差搜索步骤,利用迭代算法实现多个粗差的定值和定位。通过模拟算例分析部分最小二乘法、部分最小二乘岭估计在粗差搜索方面的效果,从另一个角度探讨粗差处理方法,推广现有的误差理论,证明文中方法的有效性。     

一种提高精密单点定位实时性的方法

由于要获取PPP需要的精密钟差文件至少有2d的时间延迟,因此通过提取IGS当天发布的超快星历中的卫星钟差数据,并对钟差数据进行插值,将插值结果做成标准格式钟差数据文件应用到PPP中,可以将精密单点定位的实时性提高为3~9h。基于Bernese软件,采用生成的钟差文件以及当天的超快星历文件对大量实测数据进行PPP。结果表明,对于4h的观测数据,该方法解算精度达到厘米级;当观测时间大于6h时,解算精度基本能够稳定在1~5cm。     

重力场数学拟合模型解的影响因素探究

为了提高地球重力场模型不适定方程求解的精度,该文采用谱分析方法从级数展开阶数、数据采样率及数据缺失量3个方面探索影响数学拟合效果的根本因素:从常用的三角级数及勒让德级数模型出发,引出重力场拟合模型球谐函数模型,观察在改变级数展开阶数、数据采样率及数据缺失量等情况下所对应设计矩阵谱结构的变化,并从微观上研究影响误差分配的有关因素及最小奇异值对误差的决定性作用,为探求重力场模型解不准的原因及实现更高精度的全球重力场模型的建立提供参考。     

港珠澳大桥沉管隧道贯通误差预计

针对港珠澳大桥沉管隧道的安全贯通问题,该文从隧道外GPS网的布设及施测方法出发,通过多期复测数据评价GPS网具有可靠的测量精度;通过对GPS网点的稳定性分析,阐明了沉管隧道地面控制点位无法长期保留、稳定性差的特点;最后就GPS网引起的贯通误差影响值进行了估算。     

国产抛弃式温度剖面仪(XBT)资料质量分析

国家海洋技术中心根据科研需求研发了抛弃式温度剖面仪(XBT)等一系列抛弃式产品.针对2014年8月份在西太平洋海域投放的XBT和XCTD所获取的温度数据进行对比分析,单剖面结果显示两者相关系数达到了0.95,在温跃层处出现温度差,断面标准差分析结果为200 m以上温跃层处较大而200m以下标准差较小,最大和最小标准差值分别为0.39和0.08.温度断面分析结果显示两者在同样的位置出现等值线的凹凸现象,对大洋水团特殊物理海洋现象描述基本一致.分析温跃层处两者温度存在偏差的原因有3个:不同传感器的不同响应时间引起的误差、深度测量公式的误差以及传感器本身的测量误差影响.国产XBT的数据质量较好,总体上性能能满足对环境复杂海域的快速走航观测,数据质量准确度和可靠性都较好.     

Why GPS makes distances bigger than they are

Global navigation satellite systems such as the Global Positioning System (GPS) is one of the most important sensors for movement analysis. GPS is widely used to record the trajectories of vehicles, animals and human beings. However, all GPS movement data are affected by both measurement and interpolation errors. In this article we show that measurement error causes a systematic bias in distances recorded with a GPS; the distance between two points recorded with a GPS is – on average – bigger than the true distance between these points. This systematic ‘overestimation of distance’ becomes relevant if the influence of interpolation error can be neglected, which in practice is the case for movement sampled at high frequencies. We provide a mathematical explanation of this phenomenon and illustrate that it functionally depends on the autocorrelation of GPS measurement error (C). We argue that C can be interpreted as a quality measure for movement data recorded with a GPS. If there is a strong autocorrelation between any two consecutive position estimates, they have very similar error. This error cancels out when average speed, distance or direction is calculated along the trajectory. Based on our theoretical findings we introduce a novel approach to determine C in real-world GPS movement data sampled at high frequencies. We apply our approach to pedestrian trajectories and car trajectories. We found that the measurement error in the data was strongly spatially and temporally autocorrelated and give a quality estimate of the data. Most importantly, our findings are not limited to GPS alone. The systematic bias and its implications are bound to occur in any movement data collected with absolute positioning if interpolation error can be neglected.     

The Relationship between Deterministic and Ensemble Mean Forecast Errors Revealed by Global and Local Attractor Radii

It has been demonstrated that ensemble mean forecasts, in the context of the sample mean, have higher forecasting skill than deterministic(or single) forecasts. However, few studies have focused on quantifying the relationship between their forecast errors, especially in individual prediction cases. Clarification of the characteristics of deterministic and ensemble mean forecasts from the perspective of attractors of dynamical systems has also rarely been involved. In this paper, two attractor statistics—namely, the global and local attractor radii(GAR and LAR, respectively)—are applied to reveal the relationship between deterministic and ensemble mean forecast errors. The practical forecast experiments are implemented in a perfect model scenario with the Lorenz96 model as the numerical results for verification. The sample mean errors of deterministic and ensemble mean forecasts can be expressed by GAR and LAR, respectively, and their ratio is found to approach2~(1/2) with lead time. Meanwhile, the LAR can provide the expected ratio of the ensemble mean and deterministic forecast errors in individual cases.     

GPS卫星定位误差概论

GPS测量中包含多种误差,只有深刻理解这些误差源的性质及其影响,才能在制定技术方案和实际作业时,采取必要的措施消除或消弱这些影响,提高成果的可靠性和精确性。本文按其产生的来源、性质、大小及对测量产生的影响等进行了介绍和分析,并提出了相应的措施以便消除或削弱它们对测量结果的影响。     

测量不确定度的讨论

以往我们都用“误差”来评定测量结果的好坏,随着生产和科学技术的发展,这一评定方法已不适应现今形势,故而引出用“测量不确定度”来评定测量结果。我国1999年就发布了国家计量技术规范JJG1059—1999《测量不确定度评定与表示》,本文根据相关的测量规范,就二者的区别和不确定度表示方法评定做一简单的分析和探讨。