统计评估人工增雨效果的一些问题研究

雨量是大气降水的量度，还是人工增雨效果评估的重要参量。由于大气降水天气系统出现频率、雨区形状、大小、降雨持续时间、雨区中雨强分布等各年、月不同，被雨区覆盖的雨量站的雨量也是不断地变化的；站间雨量将不是一一对应的确定关系，而呈现统计相关关系。相关的程度又受多种因素制约，其中站点间的距离、降雨时间长度是重要因子。因此，研究它们对相关的影响对于人工增雨效果评估的科学性有十分重要的作用。     

层状云中对流泡特征及其在降水场中的作用

层状云中夹有对流泡对整个雨系降水的启动、发展以及降水场的分布、变化有很大作用，对寻找人工增雨最佳人工影响潜力区也有特殊意义。该文在总结大量历史资料的基础上，利用雷达、卫星、地面实况、天气、机载云雨探测和数值模拟等各种手段，对层状云中夹着的对流泡进行系统深入地研究，进而为人工增雨作业提供依据。     

统计分析软件包在测震学中的初步应用

利用SPSS9．0，以华北地区自1970年以来的地震记录为研究对象，对常用的10个测震学参量进行相关分析和聚类分析，结果表明：地震震前参量形态变化视区域不同而不同，并且某些测震学参量相关性很大。     

The Statistical Prediction Of Offshore Winds From Land-Based Data For Wind-Energy Applications

Land-based meteorological measurements at two locations on the Danish coast are used to predict offshore wind speeds. Offshore wind-speed data are used only for developing the statistical prediction algorithms and forverification. As a first step, the two datasets were separated into ninepercentile-based bins, with a minimum of 30 data records in each bin. Next, the records were randomly selected with approximately 70% of the data in each bin being used as a training set for development of the prediction algorithms, and the remaining 30% being reserved as a test set for evaluation purposes. The binning procedure ensured that both training and test sets fairly represented the overall data distribution.To base the conclusions on firmer ground, five permutations of these training and test sets were created. Thus, all calculations were based on five cases, each one representing a different random selection from the same data, but maintaining the (approximate) 70-30 split in each bin. This procedure served to ensure that conclusions were not based on a single randomly-selected case. Two statistical methods are employed:multiple linear regression (MLR), and Classification and Regression Trees(CART). MLR produces excellent results using only land-based predictors.The CART results are similar to those from MLR, and tend to be slightly better.Retired     

近、现代黄河三角洲统计分布特征浅析

1855年以来建造的近、现代黄河三角洲是我国三大河口三角洲之一,由7个亚三角洲堆积体组成。在缺少实验室数据的情况下,尝试利用陆地卫星TM遥感数据,进行比值和主成份分析,增强含铁氧化物光谱信息同时分析了7个亚三角洲堆积体的频率分布直方图和统计特征值(均值、标准离差)。在此基础上,简要论述了近、现代黄河三角洲地表环境的差异,为利用遥感技术解决地学问题提供了一条有益的思路.     

最优分段法在静探试验数据处理中的应用

在研究盾构法隧道施工对地层扰动影响的课题中，采用了静力触探仪进行原位测试，测定了盾构动态推进引起周围土体的比贯入阻力Ps值的变化。针对测试时间、范围、数量有限的特点，利用最优分段法对试验数据进行了聚类处理，分析结果表明该方法在地层受盾构施工扰动的一般规律认识上具有参考意义。     

High-Frequency Sequence Stratigraphy Using Syntactic Methods and Clustering Applied to the Upper Limestone Coal Group (Pendleian, E1) of the Kincardine Basin, United Kingdom

We define a distance between sedimentary successions to compare their dissimilarity formally. Distance definition is based on attributed syntactic representation. One-dimensional successions can be represented by a string of lithofacies symbols sequentially or vertically. Each symbol can also have a vector of attributes that can provide other information on lithofacies such as thickness. The distance of any two successions is then defined consisting of its syntactic and attribute subdistances. Syntactic distance measures difference of vertical lithofacies change between two successions and attribute distance measures difference of thickness of corresponding lithofacies. Clustering is used to test validity of distance definition and its potential application to analysis of cycle-dominated sedimentary successions. Example is from the Namurian-A succession in Kincardine basin, central Scotland. There are 56 cycles in intervals of about 300 m each in two boreholes. Recognition of intermediate cycles depends on correctly determining of types of these short cycles and their vertical stacking pattern. Intermediate cycles have better potential in high-resolution stratal correlation regionally. Syntactic clustering results show that 56 short cycles can be classified into four groups with distinctive geological interpretation, which further helps reveal hierarchical cyclic architecture of the whole succession.     

1998年夏季西南低涡活动与长江上游暴雨

应用天气学和统计学方法，分析了1998年盛夏西南低涡活动的主要特征。指出该年夏季西南低涡活动偏强，该年长江上游暴雨偏多与此有关。     

Influence of averaging interval on shear velocity estimates for aeolian transport modeling

Recent investigations of aeolian transport have focused on increasingly short time scales because of growing recognition that wind unsteadiness is a major factor in the dynamics of sediment transport. However, the statistical reliability of shear velocity (u_*) estimates becomes increasingly uncertain as averaging interval is decreased. This study provides an empirical assessment of the influence of averaging interval on the reliability of u_* estimates. The data consist of 15-min wind-speed profiles (1 Hz sampling) collected at four coastal sites. Each profile was subdivided into progressively shorter fixed-length time intervals, and estimates of u_* and the 95% confidence interval for u_* were determined for each time-block using standard statistical techniques.The logarithmic model accurately represents the measured wind-speed profiles, even with relatively brief averaging intervals. Mean r² values remain robust down to block lengths as short as 10–20 s, typically retaining better than 98% of the r² value found for the full-length data sets. Fewer than 2% of the individual 10-s blocks had r² values less than 0.9. However, mean confidence intervals typically expanded by 70–80% of the full-record value as block length decreased from 900 to 10 s. For highly log-linear profiles, this amounted to an absolute increase from about ±8% to only ±14% of u_*, so that the additional information gained through the use of shorter averaging intervals may outweigh the increase in statistical uncertainty. Nevertheless, given that rates of aeolian transport are generally modeled as a function of u_*³, this increase in uncertainty may be significant for transport modeling. Thus, very short averaging intervals should be used with caution when predicting aeolian sediment flux. It is proposed that transport modeling should incorporate the shear velocity confidence interval as an indicator of the potential error associated with this source of uncertainty.     

对强震迁移的统计分析--以华北地区为例

目前对强震迁移的研究多是集中在发现迁移现象方面，一些总结迁移规律的尝试则较为主观。本文认为，强震迁移如果具有规律性则其迁移指标应具有某种统计意义，并且对整体数据集的统计分析可避免传统迁移分析方法中的问题。通过对华北地区强震迁移的3个指标(迁移方位、迁移距离、迁移时间)的统计分析，表明研究地区存在较明显的优势迁移方向(西偏南—东偏北方向)、优势迁移距离(100km内以及300～700km范围)和优势迁移时间间隔(1年内以及3～4年内)，不同震级范围以及不同活跃期内的迁移特征略有区别。