引入Himawari-8卫星数据协变量的能见度样条插值方法

在ANUSPLIN薄盘光滑样条插值中,高相关协变量的选取决定了插值结果的精确性。本文选取2017—2019年大雾和霾能见度较差的天气过程,利用183个能见度观测站点对能见度进行插值,引入Himawari-8卫星的通道数据和DEM数据作为协变量对能见度的插值结果进行改进,并对能见度插值结果进行对比分析。研究表明,引入Himawari-8数据和DEM数据作为协变量的能见度插值结果在精度上有显著提高,尤其对雾区和霾区的边界范围和纹理的反演更为准确,基于Himawari-8卫星数据和气象监测站点的观测数据,使用协变量的方法进行能见度插值可以做为能见度监测网格化的一种有效途径。     

On solution of the inverse problem for confined aquifer flow via maximum likelihood

Joint estimation of transmissivity (T) and storativity (S) in a confined aquifer is done via maximum likelihood (ML). The differential equation of groundwater flow is discretized by the finite-element method, leading to equation _t+x _t=u _t. Elements of matrices and , as well as estimated covariance matrix of noise termu _t, are functions of T and S. By minimizing the negative loglikelihood function corresponding to discretized groundwater flow equation with respect to T and S, ML estimators are obtained. The ML approach is found to yield accurate estimates of T and S (within 9 and 10% of their actual values, respectively) and showed quadratic convergence in Newton's search technique. Prediction of aquifer response, using ML estimators, results in estimated piezometric heads accurate to ±0.5 m from their actual, exact values. Statistical properties of ML estimators are derived and some basic results for statistical inference are given.     

Statistical Downscaling Based on Dynamically DownscaledPredictors： Application to Monthly Precipitation in Sweden

A prerequisite of a successful statistical downscaling is that large-scale predictors simulated by the General Circulation Model (GCM) must be realistic. It is assumed here that features smaller than the GCM resolution are important in determining the realism of the large-scale predictors. It is tested whether a three-step method can improve conventional one-step statistical downscaling. The method uses predictors that are upscaled from a dynamical downscaling instead of predictors taken directly from a GCM simulation. The method is applied to downscaling of monthly precipitation in Sweden. The statistical model used is a multiple regression model that uses indices of large-scale atmospheric circulation and 850-hPa specific humidity as predictors. Data from two GCMs (HadCM2 and ECHAM4) and two RCM experiments of the Rossby Centre model (RCA1) driven by the GCMs are used. It is found that upscaled RCA1 predictors capture the seasonal cycle better than those from the GCMs, and hence increase the reliability of the downscaled precipitation. However, there are only slight improvements in the simulation of the seasonal cycle of downscaled precipitation. Due to the cost of the method and the limited improvements in the downscaling results, the three-step method is not justified to replace the one-step method for downscaling of Swedish precipitation.     

Glacier development and topographic context

This paper analyses the topographic context of the remaining glaciated areas in the Maladeta Massif (Central Spanish Pyrenees). These ice‐covered surfaces have been incorporated into a geographic information system (GIS) in an attempt at correlating the presence of ice with a range of topographic variables obtained from a digital elevation model. The use of generalized additive models and binary regression tree models enabled us (i) to quantify the spatial variability in the distribution of glaciers attributable to characteristics of the local terrain, (ii) to investigate the interaction between the variables that account for the ice cover distribution and (iii) to map the probability of glacier development. Our results show that although the development of glaciers depends on regional climate conditions, the topographic context is of paramount importance in determining the location, extent, shape and recent evolution of each glacial body. Thus, the joint effect of altitude, exposure to incoming solar radiation, slope and mean curvature is able to explain more than 70 per cent of the observed variance. Copyright © 2006 John Wiley & Sons, Ltd.     

基于改进的Elman神经网络的中长期径流预报

径流中长期预报长期以来一直都是人们关注的热点研究问题。现行的径流预报方法很多,传统的有时间序列法,多元回归分析法等,这些方法虽然简单易用,但是如果预报对象提供的样本容量偏小或者因子选择不够合理,都会造成预报精度偏差过大,难于有效的指导工程应用。鉴于此,本文提出一种改进的采用局部回归的Elman神经网络方法。并应用到凤滩水库优化调度的径流预报中。结果表明,与回归分析法、BP网络相比较,该方法不仅提高了算法的效率,而且提高了预报的精度,在径流预报中具有有效性和优越性。     

近50年汾河上中游流域径流对气候变化的响应分析

以汾河上中游干流水文站近50年的气象水文资料为基础,采用多元回归及敏感性分析方法,对径流、降水和气温三者之间变化规律以及区域水文对气候变化的响应进行了定量分析,结果表明气候变暖导致了蒸发的加剧,并一定程度上造成了汾河干流径流量的减少。预估暖干气候条件下引发干旱灾害的可能性将增强。     

数字水准仪与精密光学水准仪测量精度比较

数字水准仪的出现解决了大地测量仪器中水准仪自动读数与记录问题,对当代测量技术产生了积极的影响.文中介绍了如何采用双频激光干涉仪配合45°平面镜检测数字水准仪的方法,对精密光学水准仪和数字水准仪进行综合精度的评定和比较,并对结果进行了分析.     

基于偏最小二乘回归的纹理特征线性组合

基于偏最小二乘回归技术时纹理特征进行线性组合，得到新的纹理特征来进行分类。实验表明，组合后的纹理特征不但提高了纹理分类的性能，而且具有一定的数据自适应能力。     

数字水准仪与精密光学水准仪测量精度比较

数字水准仪的出现解决了大地测量仪器中水准仪自动读数与记录问题,对当代测量技术产生了积极的影响。文中介绍了如何采用双频激光干涉仪配合45°平面镜检测数字水准仪的方法,对精密光学水准仪和数字水准仪进行综合精度的评定和比较,并对结果进行了分析。     

利用EXCEL软件进行线性回归分析

介绍了EXCEL数据处理软件在一元和多元线性回归分析中的应用方法及实现技巧。