Assessing spatial and attribute errors in large national datasets for population distribution models: a case study of Philadelphia county schools

Geospatial technologies and digital data have developed and disseminated rapidly in conjunction with increasing computing efficiency and Internet availability. The ability to store and transmit large datasets has encouraged the development of national infrastructure datasets in geospatial formats. National datasets are used by numerous agencies for analysis and modeling purposes because these datasets are standardized and considered to be of acceptable accuracy for national scale applications. At Oak Ridge National Laboratory a population model has been developed that incorporates national schools data as one of the model inputs. This paper evaluates spatial and attribute inaccuracies present within two national school datasets, Tele Atlas North America and National Center of Education Statistics (NCES). Schools are an important component of the population model, because they are spatially dense clusters of vulnerable populations. It is therefore essential to validate the quality of school input data. Schools were also chosen since a validated schools dataset was produced in geospatial format for Philadelphia County; thereby enabling a comparison between a local dataset and the national datasets. Analyses found the national datasets are not standardized and incomplete, containing 76 to 90 percent of existing schools. The temporal accuracy of updating annual enrollment values resulted in 89 percent inaccuracy for 2003. Spatial rectification was required for 87 percent of NCES points, of which 58 percent of the errors were attributed to the geocoding process. Lastly, it was found that by combining the two national datasets, the resultant dataset provided a more useful and accurate solution.     

GLDAS和CMIP5产品的中国土壤湿度-降水耦合分析及变化趋势

利用GLDAS同化产品和12个CMIP5模式的输出结果,从土壤湿度对降水影响的两个中间环节出发,通过分析陆面耦合指数ILH、潜热通量—抬升凝结高度耦合指数ILCL以及抬升凝结高度ZLCL间接研究中国区域土壤湿度与降水间耦合特征,并对1958~2013年及RCP4.5辐射强迫情景下50年(2006~2055年)的4个代表性区域夏季耦合强度的年代际变化特征进行分析。研究发现:1958~2013年期间,内蒙古阴山山脉附近、新疆和青海的部分地区为夏季中国土壤湿度与降水耦合的最强区域;陆面耦合指数ILH变化幅度从高到低依次出现在华北、华南、内蒙古中部和西北地区,并在20世纪70年代中到80年代中发生转折。2006~2055年的平均而言,预估内蒙古阴山山脉附近仍为耦合最强区;与历史时期(1958~2005年)比较,新疆中部和内蒙古阴山山脉附近的耦合指数ILH增大,而广西和广东地区的则减小;对于耦合指数ILH的年代际变化(2006~2055年),2026~2035年间华北最大而华南最小,西北地区变化不大,而内蒙古中部地区的耦合强度逐渐增大。     

伊犁河谷和天山北坡暴雨过程水汽特征分析

选取4次伊犁河谷、天山北坡暴雨天气过程,利用地面逐时降水、常规、NCEP/NCAR 1°×1°再分析及地基GPS遥感的大气水汽总量资料(GPS-PWV),通过合成分析方法得到暴雨期间大气环流的基本配置,阐明了伊犁河谷、天山北坡地区强降水期间环流形势及水汽输送的异同,结果表明:(1)强降水过程中暴雨区上空200 h Pa强辐散气流、500 h Pa槽前正涡度平流、西南气流利于垂直运动的发展,低层偏西、偏东和偏北气流为暴雨区提供水汽和不稳定能量,低层辐合、高层辐散,配合地形辐合抬升,上升运动进一步增强,造成强降水发生;(2)深厚的西西伯利亚低涡低槽系统移速缓慢,停滞时间长,造成强降水前暴雨站增湿时间更长,比较发现强降水发生前暴雨站GPS-PWV均存在1~3 d的增湿过程,暴雨期间测站GPS出现明显跃变,峰值可达到气候平均值的2倍左右;(3)GPS大气可降水量的演变与大尺度的水汽输送、聚集有较好的对应关系,但GPS高值区并不代表降水大值区,还应和动力热力等条件综合判断降水的强弱。     

丘陵地区边界层风廓线雷达数据统计特性分析

采用数据获取率来分析和评价风廓线雷达的探测能力, 对通过2012年的风廓线数据进行统计分析。结果表明:数据获取率和信噪比都随季节变化, 夏季探测能力大于冬季。按照数据获取率达到80%的要求, 确定边界层风廓线雷达无降雨天气有效探测高度为3 km, 并确定低模和高模最佳衔接高度为0.6 km, 能够获得更好的数据获取率。在无降雨天气, 信噪比随高度呈现对数函数单调递减的变化规律, 夏季信噪比的衰减程度比冬季大;在降雨天气, 信噪比随高度呈现一次函数的变化规律, 其斜率范围在-10.44~-2.47之间, 而夏季信噪比的衰减程度比冬季小。     

气象卫星低分辨率资料传输的数字化

气象卫星低分辨率模拟资料传输WEFAX即将数字化为LRIT，阐述了LRIT(低分辨率信息传输)内容、LRIT数据传输模式和系统结构以及各卫星运行国LRIT传输比较。     

自研透射式能见度测量系统性能分析

从系统测量原理、组成结构、计算过程及测量效果等方面介绍了一种自行研制的透射式能见度测量系统。该系统使用白色LED光源,实现发散角为1mrad的平行光路;利用积分球进行分光监控以补偿光能量变化;使用非球面镜实现全光斑接收。系统与积分浊度计在2～10km量程内能见度测试误差小于10%。从透射式能见度测量原理与计算过程,分析了影响系统测量性能的因素。结果显示定标准确性、测量线性度与系统稳定性是影响系统测量性能的主要因素,同时给出了该系统的定标准确性、测量线性度与系统稳定性的评估方法及评估数据,验证了该系统的测量性能。     

CC天气雷达数据流传输业务台站级监控报警系统的设计与实现

利用UDP组播通信、进程监控、文件监控、网络监控等技术,研发了CC天气雷达数据流传输业务台站级监控报警系统,较早、较好地实现了雷达扫描状态、数据流上行传输、标准格式基数据本地存储、基数据补传、软件运行和网络运行状态的实时监控和短信报警。实践表明,软件运行较稳定,能对数据流传输业务进行有效监控,短信报警准确及时,报警阈值从6min缩短到40s,提升了故障的发现和处理效率,提高了天气雷达业务可用性和数据传输质量,减轻了雷达台站业务人员的值守压力。     

集合Kalman滤波同化理论及其数值试验

集合Kalman滤波用于数值试验有着坚实的理论基础.本文介绍了集合Kalman滤波理论及其技术实现, 在此基础上搭建了集合Kalman滤波同化系统, 用MM5模式同化了实测探空资料并作了48 h的预报试验, 并将预报结果与实测值及4D VAR同化的结果作了比较.试验结果表明: 集合Kalman滤波同化探空资料可以改进MM5模式的预报效果, 且集合Kalman滤波同化后模式的预报效果明显优于4D VAR同化后模式的预报效果.     

中国数字地震台网（CDSN）数据文件系统：—CDSN应用系列论文一

中国数字地震台网(CDSN)观测并生成的数字地震资料是开展数字地震学研究必不可少的高质量数据源。为了使科学家们更好地使用这些数据,本文主要从数字地震资料产生出的各个环节、数据结构与格式、数据物理量之间的换算向读者作概括的介绍.希望读者对数字化地震资料的数据文件、数据记录、数据字均能有透彻的理解,从而节省时间和精力,提高资料的使用率。     

The Ensemble Kalman Filter: theoretical formulation and practical implementation

The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.Responsible Editor: Jörg-Olaf Wolff