9406号台风登陆造成华南及长江中游暴雨过程的数值模拟试验

本文应用有限区域数值预报模式，并根据不同的积云参数化方案对１９９４年第６号台风登陆后低压的移动规律及其对应降水分布进行了数值模拟试验，结果表明积云对流参数化对于台风移动及其降水分布影响极大，是作出台风暴雨预报的关键过程。     

黑风暴的沙尘形成与输送参数化及中尺度数值试验

西北地区典型黑风暴和强沙尘暴都是在特定大尺度环流背景和中尺度系统相互作用下发生和发展的，而中、低空强锋区相伴的强冷锋移经沙源充足的大沙漠区是黑风暴和强沙尘暴形成和发展的必要条件。为了研究黑风暴和沙尘暴的沙尘形成、输送及沉降机制，本文提出了一种沙尘源、汇项的参数化方案和一个沙尘输送方程，进而引入已有的ＭＭ４中尺度数值模式模拟系统；应用这个改进和发展的模式模拟系统基本成功地模拟了“９３．５”黑风暴的天气系统演变及其沙尘浓度的近地层和垂直分布以及沙尘的沉降与输送。模拟结果分析表明，用包括沙尘输送方程及其沙尘源、汇项参数化方案的中尺度数值模式来研究黑风暴的沙尘形成、输送和沉降机制是一种具有应用前景的方法。     

主成分与主成分估计

在测量数据处理中,当设计阵存在复共线时,最小二乘估计的性质将变得不好,本文应用主成分估计来改进最小二乘估计。一方面是因为主成分估计具有一些好的性质,另一方面与岭估计和广义岭估计相比,主成分估计的偏参数选取要简便得多,从而大大提高了实用价值。     

GPS水准计算的非参数回归法

非参数回归是一种广义的回归方法,它具有直观,对模型要求不严密,计算简单的优点。本文介绍非参数回归的原理及其左GPS水准计算中的应用,通过对两个测区的试算,得出了一些有益的结论。     

三维网平差的方差分量估计

本文将方差分量估计理论运用于三维网平差中,推导出了含定向角未知数及消去定向角未知数的方差分量估计公式,并进行了模拟和实例计算,从而建立了合理的三维网平差随机模型。     

灰色系统GM(n,m)模型参数的递推估计和时变估计

本文给出灰色系统GM(n,m)模型参数的递推最小二乘估计和时变参数估计,前者的优点是可以避免反复求逆矩阵,因而使计算简便,同时克服了文献1中给出的估计方法当观察数据多、矩阵线数高、分配单元增加时,微型机容量不够的弱点,而且随着新数据的到来,通过递推算法自动对系统参数加以修正,提高了模型的自适应性;时变参数估计可以缩小系统的时变性与模型参数非时变性所产生的差异。     

工程岩体强度的估算方法

岩体是由地质过程中形成的岩块和结构面网络组成。由于试件制备、加荷等均极困难,且昂贵而费时,难于像岩块那样进行大量试验来确定岩体之强度。所以,如何通过室内小试件试验来估算大岩体的强度成为工程地质工作者所关注的问题。本文介绍了两种用小试件资料估算大岩体强度的方法及计算实例。     

Ecological requirements of Ostracoda (Crustacea) in three types of springs in Turkey

Seasonal occurrence of six ostracod species (Psychrodromus olivaceus, Potamocypris villosa, Ilyocypris inermis, Candona candida, Candona neglecta, and Cypridopsis vidua) varied from May 2003 to June 2004 in three types of spring (Limnocrene, Helocrene, Rheocrene). When I. inermis was only found in the limnocrene spring each month, P. olivaceus was common in all types of springs. The other four ostracods were found in the helocrene spring in fall, winter, and spring seasons. The unweighted pair group mean averages dendrogram separated three main clusters. The first cluster includes two species (C. vidua, C. candida) while I. inermis was found in the second cluster and P. olivaceus, C. neglecta, and P. villosa were found in the third. The occurrence of P. olivaceus and C. neglecta and P. villosa and C. candida was strongly correlated to each other (r=0.750 and 0.850, respectively). The Pearson correlation analyses showed a strong negative relationship between C. neglecta and water temperature (r=−0.607), but other species did not show any significant correlation to any of the environmental variables used (P>0.05). Canonical correspondence analyses (CCA) displayed all species closer to the center of the dendrogram, indicating high levels of species tolerances to environmental variables. Thus, the first axis of the CCA diagram explained 80% of the relationship between six species and five environmental variables.     

Lognormal distribution of the observed and modelled neutral thermospheric densities

For analyzing measurements of any kind, it is important to estimate the probability distribution of the measurement errors. When modelling the observations using least-squares fitting, the distribution of the errors plays a vital role in choosing the merit function to be minimized, as unnormally distributed errors (e.g. outliers, or displaying asymmetry around the mean) may substantially skew a least-squares fit of estimated model parameters. Using the CACTUS accelerometer data covering heights of 230–750 km, we will show that the statistical relationship between the commonly used semi-empirical models of neutral thermospheric density (MSIS, DTM) and the observed densities is consistent with lognormal distribution, i.e. the logarithm of the ratio of the measurements to the predictions is approximately normally distributed. This experimental fact may be applied in modelling the neutral thermospheric density. bezdek@asu.cas.cz     

一种激光扫描数据与数码照片的配准方法

提出了一种激光扫描数据和数字图像配准的方法。该方法基于立体像对匹配点与三维扫描点云的最近邻迭代配准。配准中，采用M-估计的选择权迭代在最邻近点搜索算法中逐步消除立体像对误匹配粗差点的影响，得到正确的收敛结果，并基于地面实验证明此方法是可行的和有效的。