改进的精细分辨率雷达探测强对流效果评估

简要介绍了改进精细分辨率雷达所涉及的提高空间分辨率和智能化、快速扫描等技术。利用改进后的雷达精细分辨率数据和原始分辨率数据,对不同强天气类型的探测效果进行了对比分析,结果表明：精细分辨率数据可获得比原始分辨率数据更大的相对径向速度,辐合辐散和速度极值也更明显;获取更为清晰的超级单体结构以及龙卷涡旋特征和龙卷碎片特征等,更早识别出对流单体和雷暴云团;采用精细分辨率数据进行定量降水估计的精度与原始分辨率数据相当或略有提升。改进后精细分辨率数据具有更高的空间分辨率（双偏振）雷达观测特征,在对中小尺度强对流回波监测和识别的实际业务中具有较明显优势。     

Optimized Sample Schemes for Geostatistical Surveys

Sample schemes used in geostatistical surveys must be suitable for both variogram estimation and kriging. Previously schemes have been optimized for one of these steps in isolation. Ordinary kriging generally requires the sampling locations to be evenly dispersed over the region. Variogram estimation requires a more irregular pattern of sampling locations since comparisons must be made between measurements separated by all lags up to and beyond the range of spatial correlation. Previous studies have not considered how to combine these optimized schemes into a single survey and how to decide what proportion of sampling effort should be devoted to variogram estimation and what proportion devoted to kriging An expression for the total error in a geostatistical survey accounting for uncertainty due to both ordinary kriging and variogram uncertainty is derived. In the same manner as the kriging variance, this expression is a function of the variogram but not of the sampled response data. If a particular variogram is assumed the total error in a geostatistical survey may be estimated prior to sampling. We can therefore design an optimal sample scheme for the combined processes of variogram estimation and ordinary kriging by minimizing this expression. The minimization is achieved by spatial simulated annealing. The resulting sample schemes ensure that the region is fairly evenly covered but include some close pairs to analyse the spatial correlation over short distances. The form of these optimal sample schemes is sensitive to the assumed variogram. Therefore a Bayesian approach is adopted where, rather than assuming a single variogram, we minimize the expected total error over a distribution of plausible variograms. This is computationally expensive so a strategy is suggested to reduce the number of computations required     

两种地图点群综合算法的比较

通过搭建实验程序,分别对基于非加权Voronoi图和加权Voronoi图的点群自动综合算法进行验证,详细对比和分析两种算法计算结果对点群的统计信息、拓扑信息、度量信息和专题信息的传递情况,计算部分结果的相似度,从而得出加权Voronoi图点群综合算法更优的结论。     

Soil depth estimation through soil-landscape modelling using regression kriging in a Himalayan terrain

Soil formation depends upon several factors such as parent material, soil biota, topography and climate. It is difficult to use conventional soil survey methods for mapping the depth of soil in complex mountainous terrains. In this context, the present study aimed to estimate the soil depth for a large area (330.35 km²) using different geo-environmental factors through a soil-landscape regression kriging (RK) model in the Darjeeling Himalayas. RK with seven predictor variables such as elevation, slope, aspect, general curvature, topographic wetness index, distance from the streams and land use, was used to estimate the soil depth. While topographic parameters were derived from an 8-m resolution digital elevation model, the ortho-rectified Cartosat-1 satellite image was used to prepare the land use map. Soil depth measured at 148 sites within the study area was used to calibrate and validate the RK model. The result showed that the RK model with the seven predictors could explain 67% spatial variability of soil depth with a prediction variance between 0.23 and 0.42 m at the test site. In the regression analysis, land use (0.133) and slope (–0.016) were identified as significant determinants of soil depth. The prediction map showed higher soil depth in south-facing slopes and near valleys in comparison to other areas. Mean, mean absolute and root mean-square errors were used to access the reliability of the prediction, which indicated a goodness-of-fit of the RK model.     

日降水量的空间插值方法与应用对比分析——以深圳市为例

综合分析了四种空间插值方法,即距离权重倒数法、局部多项式法、普通克里金法和考虑海拔的协克里金法的特点,并以深圳市36个雨量站2006年雨季27天的日累计降水量数据为实例进行了研究和验证,采用交叉检验的方法对插值结果进行比较。研究表明,四种方法均能反映降水总体情况,但插值曲面相对真实曲面较平滑,距离权重倒数法的插值曲面最为平滑;多项指标比较显示,克里金法优于距离权重倒数法和局部多项式法。与普通克里金法相比,考虑海拔的协克里金法对插值精度没有明显提高。依照雨量站海拔、日均降水量分别对插值结果数据分组统计比较表明,海拔高的雨量站插值结果普遍大于实测结果,海拔低的雨量站则相反;日均降水量较大时(>50mm),插值误差明显增大。     

Geostatistics for Power Models of Gaussian Fields

This paper introduces geostatistical approaches (i.e., kriging estimation and simulation) for a group of non-Gaussian random fields that are power algebraic transformations of Gaussian and lognormal random fields. These are power random fields (PRFs) that allow the construction of stochastic polynomial series. They were derived from the exponential random field, which is expressed as Taylor series expansion with PRF terms. The equations developed from computation of moments for conditional random variables allow the correction of Gaussian kriging estimates for the non-Gaussian space. The introduced PRF geostatistics shall provide tools for integration of data that requires simple algebraic transformations, such as regression polynomials that are commonly encountered in the practical applications of estimation. The approach also allows for simulations drawn from skewed distributions.     

纯时间域多元信息地质统计学

随着人们动态地认识客观世界的要求日益增加,时空域中的多元信息地质统计学技术研究受到重视。本文在时间域内对几种纯时间域克立格技术进行了研究,重点对纯时间域中的普通克立格（ＴＯＫ）、简单克立格（ＴＳＫ）及泛克立格（ＴＵＫ）进行了论述,也对纯时间域中的协同克立格（ＴＣＯＫ）和指示克立格（ＴＩＫ）作了简要的概括。