AN EVALUATION OF SAS/GRAPH SOFTWARE FOR COMPUTER CARTOGRAPHY1

The SAS® computer software system, widely used and respected for its capabilities in statistical analysis and data base management, now includes a new set of graphic and cartographic procedures called SAS GRAPH?. We have used these cartographic procedures in research on mapping ethno-cultural census data from metropolitan areas in Ontario and in undergraduate and graduate courses in computer cartography. On the basis of that experience, we describe and evaluate SAS/GRAPH'S cartographic capabilities and illustrate with maps drawn by various devices.     

SAS/ETS在变形监测数据处理中的应用

在综合考虑数学模型的预测精度与编程实现的可操作性基础上,提出了利用模块对变形监测数据进行时间序列分析,并概括介绍了该模块的3个主要命令使用方法,解决了时间序列分析在监测数据处理中实现起来非常繁琐的问题。最后通过与环境下动态灰色模型综合比较,证明了时间序列分析在变形监测数据处理中操作简单,模拟精度和预测精度都较高。     

一种基于自适应麦克风阵的智能天线实验平台

智能天线是第三代移动通信的关键技术之一,也是当前信号处理和通信领域的研究热点.在对智能天线算法进行理论分析和仿真的基础上,有必要构建一个灵活、通用的实验平台,用以验证各种智能天线算法的有效性和实用性.探讨了一种基于自适应麦克风阵的智能天线实验平台的实现方法,介绍了该系统的原理、结构和各部分的作用.     

主成分分析与聚类分析在青岛夏季气温变化研究中的应用

选用青岛站1951-2010年每年6-8月各月平均气温资料,通过SAS软件进行了主成分分析和聚类分析,分析了近60 a夏季气温的年际气候变化.主成分分析的结果表明,第一主成分反映青岛夏季气温距平,其正（负）方向反映夏季气温的正（负）距平,其强度反映气温偏高（低）的程度;第二主成分则反映同一年内夏季各月间气温的差异,其绝对值越大,表示各月气温差异越大.聚类分析的结果表明,青岛站夏季月平均气温的变化可以分为3类：1）6月、7月气温较低,在8月升温;2）7月平均气温最高,6月、8月相对较低;3）6月气温低,7、8两月气温较高.其中1993、2003年为第一类,2005年为第二类,其余为第三类.     

越南河内市冬作物生长季降水量ARIMA预测模型

考虑了气候系统中一些变量突变时可能对预测关系的改变作用，用ARIMA（Auto-Regressive Integrated Moving Average)动态模型的建摸方法，通过SAS软件的计算，建立河内冬作物生长季降水量预测模型。用1996－1998年的独立资料检验，预测结果与实况接近。     

Constraining water age dynamics in a south-eastern Australian catchment using an age-ranked storage and stable isotope approach

Improving our knowledge of the travel times of water through catchments is critical for the management and protection of water resources and to improve our understanding of fundamental catchment behaviour. In this study we use the age-ranked storage framework StorAge Selection (SAS) to investigate travel times in the Corin catchment, a headwater catchment in the south-east of Australia covered by native Eucalyptus species. Few studies have applied the SAS framework globally and in energy-intensive areas where catchment losses are heavily in favour of evapotranspiration relative to streamflow. A combination of observed and modelled values of oxygen-18 (δ¹⁸O ), the stable isotope in water, are used to constrain storage selection preferences of streamflow and evapotranspiration and the size of the catchment active storage. The highest performing parameter combinations that could reproduce δ¹⁸O in streamflow were dependent on a strong preference for young water in evapotranspiration, and a mixture of weak young and old water preference in streamflow. The mean travel time of streamflow over the study period 2007–2019, weighted by the flow rate, is limited to within a probable range of 2.81–9.77 years. The size of the active storage, a key parameter in the SAS framework, was poorly identified, and in combination with the isotopic inputs into the model, contributed to the uncertainty of the results. We discuss the implications of the results with respect to the study area, as well as within the context of SAS research globally and identify ways to improve the modelling process.     

Nitrate removal and young stream water fractions at the catchment scale

Despite extensive research on nitrate export and removal, nutrient contamination remains a major threat to water bodies worldwide. At the local scale, nitrate removal is governed by biogeochemical conditions that vary in space and time, making integration to entire landscapes critical. Water transit times have often been used to describe solute transport, but the relation between water age and nitrate removal at the catchment scale is still poorly understood. We test the hypothesis that nitrate removal peaks when the fraction of young water in discharge is at its minimum, because nitrate removal occurs mostly under dry conditions where deeper, older groundwater dominates streamflow. We tested this hypothesis by exploring a detailed water quality record from the Kervidy–Naizin catchment (FR) and comparing the dynamics of nitrate to those of a conservative solute (chloride). We find that estimates of nitrate removal are consistent with previous estimates at the site and they show a good (inverse) correlation with the fraction of streamflow that is younger than 2.5 months. However, this young water fraction cannot be used to predict nitrate removal in the winter–spring period, when no removal is observed regardless of streamflow age. While this leads us to reject our hypothesis during the winter period, it also suggests that water age distributions and their correlation with nitrate removal can possibly reveal distinct sources of stream water at different hydrologic regimes and relevant biogeochemical reactions.     

中国农业受灾与成灾面积预测研究

文中运用SAS软件建立了中国农业受灾面积非线性回归预测模型及成灾面积一元回归预测模型。前者运用SAS软件的时间序列方法、回归分析方法和时延神经元网络方法,分别建立了4个农业受灾面积预测模型。在运用各模型进行模拟预测的基础上,运用组合方法建立组合预测模型,得到农业受灾面积的集成预测结果,从而克服了单个预测模型的偶然误差,提高了预测结果的精确性和可靠性。2000年农业受灾面积的预测值为5322.37×10~4hm2;后者根据中国1951～1999年农业受灾、成灾面积资料,用SAS的REG过程拟合受灾面积与成灾面积的关系,预测未来成灾面积。2000年农业成灾面积预测值为2479.47×10~4hm2。经检验,模型预测效果良好,根据预测结果可以采取有针对性的减灾措施,减少灾害损失。     

水产试验设计的SAS实施方法

本文通过两个实例讨论水产试验设计的结果数据在ＳＡＳ系统上实施统计分析的方法。实例一考察不同温度和盐度对鲻鱼总孵化百分率的影响的带有４个丢失单元的５×６因子设计，调用ＲＳＲＥＳ过程作二次响应曲面回归分析，结果表明当温度为２７．０４℃、盐度为３１．９５‰可获得最大总孵化百分率９９．０７％；实例二调用ＮＬＩＮ过程拟合罗氏沼虾的生长曲线，由ＳＡＳ系统直接输出实测值对出生天数和预测值对出生天数的重迭散布图。     

A New X-band Weather Radar System with Distributed Phased-Array Front-ends: Development and Preliminary Observation Results

A novel weather radar system with distributed phased-array front-ends was developed. The specifications and preliminary data synthesis of this system are presented, which comprises one back-end and three or more front-ends. Each front-end, which utilizes a phased-array digital beamforming technology, sequentially transmits four 22.5°-width beams to cover the 0°–90° elevational scan within about 0.05 s. The azimuthal detection is completed by one mechanical scan of0°–360° azimuths within about 12 s volume-scan update time. In the case of three front-ends, they are deployed according to an acute triangle to form a fine detection area(FDA). Because of the triangular deployment of multiple phased-array front-ends and a unique synchronized azimuthal scanning(SAS) rule, this new radar system is named Array Weather Radar(AWR). The back-end controls the front-ends to scan strictly in accordance with the SAS rule that assures the data time differences(DTD) among the three front-ends are less than 2 s for the same detection point in the FDA. The SAS can maintain DTD < 2 s for an expanded seven-front-end AWR. With the smallest DTD, gridded wind fields are derived from AWR data, by sampling of the interpolated grid, onto a rectangular grid of 100 m ×100 m ×100 m at a 12 s temporal resolution in the FDA. The first X-band single-polarized three-front-end AWR was deployed in field experiments in 2018 at Huanghua International Airport, China. Having completed the data synthesis and processing, the preliminary observation results of the first AWR are described herein.