On cross-correlating weak lensing surveys

The present generation of weak lensing surveys will be superseded by surveys run from space with much better sky coverage and high level of signal-to-noise ratio, such as the Supernova/Acceleration Probe ( SNAP ). However, removal of any systematics or noise will remain a major cause of concern for any weak lensing survey. One of the best ways of spotting any undetected source of systematic noise is to compare surveys that probe the same part of the sky. In this paper we study various measures that are useful in cross-correlating weak lensing surveys with diverse survey strategies. Using two different statistics – the shear components and the aperture mass – we construct a class of estimators which encode such cross-correlations. These techniques will also be useful in studies where the entire source population from a specific survey can be divided into various redshift bins to study cross-correlations among them. We perform a detailed study of the angular size dependence and redshift dependence of these observables and of their sensitivity to the background cosmology. We find that one-point and two-point statistics provide complementary tools which allow one to constrain cosmological parameters and to obtain a simple estimate of the noise of the survey.     

基于GIS的区域经济统计分析系统的设计与实现

随着经济的发展,区域间经济相互作用和影响的关系越来越密切,忽略空间相互作用的传统区域经济分析手段和方法开始显现出一些明显的不足。而GIS在处理和分析区域地理数据上具有强大的空间分析能力,为此我们引入GIS工具对区域经济进行分析,相较于传统的分析手法有了很大改善。本文以江西省区域经济数据为例,设计了一个基于GIS的区域经济统计分析系统,并利用Arcob-jects二次开发控件结合VB可视化编程语言,实现了大部分区域经济统计分析功能,最后并将结果进行网络发布。研究结果表明将GIS引入到区域经济统计分析中,更能正确、有效的揭示区域经济发展在空间上的联系,为区域经济研究决策提供服务。     

基于广义Kопытов模型及乙型水驱曲线的综合预测法

将广义Kопытов预测模型和乙型水驱曲线方法有机的结合起来，得到了油田开发中后期——递减时期的一种预测水驱开发油田的含水率、产油量、产水量及其相应的累积产量随开发时间变化的方法，此方法克服了在水驱油田预测开发指标中二者所存在的局限性。     

疏勒河流域昌马灌区泉水量预测分析

疏勒河流域农业灌溉主要采用地表水灌溉 ,泉水为该区农业灌溉的主要水源之一 ,该文利用 2 0世纪 90年代的测流资料 ,采用有限差分方法对疏勒河中游泉水量的变化趋势进行预测分析 ,结果显示 ,随着时间的延长 ,泉流量呈逐渐减小的趋势 ,但下降梯度逐渐变小 ,最终趋于稳定     

Statistical tests for regional seismic phase characterizations

In seismic analysis some assumptions are often made aboutthe data, e.g. stationarity and Gaussianity. This is not obvious for all realseismic data. Here, we use statistical tests for characterization of regionalseismic data. We apply tests for stationarity, symmetry, linearity, andtime-reversibility. In the analysis we use twelve regional seismic events inFennoscandia recorded with the seismic small-aperture arrays NORESS,ARCESS and FINESA at hypocentral distances in the range from 160 to1580 km. For the tests we use the regional phases Pn, secondary P, Sn and Lg-phases and the preceding noise. Two of the eventsare explosions, two are rockbursts and eight are earthquakes. Theperformance and possibilities of using statistical tests based on bispectra, asa complementary tool for conventional analysis of seismic phases isdemonstrated. The preceding noise recorded before the first onset of theP-wave for the twelve events is tested to be spatially stationarybetween each channel within each array and temporal stationary in 21consecutive time windows of 3.2 sec each. Also, the preceding noise issymmetric and linear. The seismic phases defined by the symmetry test asnon-Gaussian (not symmetric) are all linear. This means a linear model canbe used to characterize both the noise and the phases. The first P-phase for the two explosions is characterized as non-Gaussian at thethree arrays. For all 36 possibly first P-phase arrivals at the three arraystations, 23 are non-Gaussian. The second P-phase is non-Gaussian at13 of 36 data records, the S-phase at eleven of 36 and the Lg-phase at nine of 36. For all the four phases more than 32 of possible36 are time-reversible.     

月降水量的神经网络混合预报模型研究

以均生函数表征预报量自身周期变化，结合500hPa月平均高度场和月平均海温场预报因子，采用神经网络方法建立了一种新的短期气候预报模型。分别以广西桂北、桂中和桂南6月降水量作为预报对象进行预报试验，结果表明，这种新的预报方法比均生函数回归预报模型及高度场、海温场预报因子的回归预报模型，具有更好的物理基础和预报能力。     

几种空气质量预报方法的预报效果对比分析

目前应用于我国各个城市空气质量预报业务的预报方法主要有三种 :数值模式预报、统计预报和综合经验预报。这几种预报方法都有其各自的优势 ,同时也存在一些不足。应用以上方法对天津市市区进行空气质量业务预报 ,通过实测资料与预报结果进行对比分析 ,给出这几种方法在天津市区空气质量预报中的预报效果客观评价。     

数值预报产品在夏季持续高温预报中的释用

利用 1999～ 2 0 0 2年 6～ 8月 96～ 192h日本数值预报产品 85 0hPa气温与吉林省的日平均气温、阶段性高温及极端最高气温 (长春市 )资料 ,通过线性分析 ,找出了日本数值预报产品的 85 0hPa气温与吉林省地面日平均气温、阶段性高温及极端最高气温的对应关系 :吉林省 6～ 8月日平均气温在 96～ 192h的 85 0hPa日本数值预报长春站日平均值上加 6 6～ 4 1℃ ,6～ 8月的极端最高气温在相应的日本数值预报产品上加 9 3～ 13 0℃。