利用正交变换方法计算协方差分析的统计量

证明用Givens—Gentleman正交变换给出的加仅最小二乘解与统计定轨理论求得的解一致．采用正交变换方法计算其它的一些重要的统计量,如考察协方差矩阵、摄动矩阵等,并计算这些量随时间的传播．这种算法的优点是通过降低法方程的条件数提高计算的稳定性,同时可以方便地对不同的参数组合情况求解而不需多次解算法方程．     

On the colocation iterative solution model and algorithm for gravity anomaly

ＯｎｔｈｅｃｏｌｏｃａｔｉｏｎｉｔｅｒａｔｉｖｅｓｏｌｕｔｉｏｎｍｏｄｅｌａｎｄａｌｇｏｒｉｔｈｍｆｏｒｇｒａｖｉｔｙａｎｏｍａｌｙＹＵＡＮ－ＸＩＹＡＮＧ（杨元喜）ａｎｄＣＨＡＮＧ－ＪＩＡＮＬＩＵ（刘长建）ＺｈｅｎｇｚｈｏｕＩｎｓｔｉｔｕｔｅｏｆＳ...     

Spatial continuity measures for probabilistic and deterministic geostatistics

Geostatistics has traditionally used a probabilistic framework, one in which expected values or ensemble averages are of primary importance. The less familiar deterministic framework views geostatistical problems in terms of spatial integrals. This paper outlines the two frameworks and examines the issue of which spatial continuity measure, the covarianceC (h) or the variogram (h), is appropriate for each framework. AlthoughC (h) and (h) were defined originally in terms of spatial integrals, the convenience of probabilistic notation made the expected value definitions more common. These now classical expected value definitions entail a linear relationship betweenC (h) and (h); the spatial integral definitions do not. In a probabilistic framework, where available sample information is extrapolated to domains other than the one which was sampled, the expected value definitions are appropriate; furthermore, within a probabilistic framework, reasons exist for preferring the variogram to the covariance function. In a deterministic framework, where available sample information is interpolated within the same domain, the spatial integral definitions are appropriate and no reasons are known for preferring the variogram. A case study on a Wiener-Levy process demonstrates differences between the two frameworks and shows that, for most estimation problems, the deterministic viewpoint is more appropriate. Several case studies on real data sets reveal that the sample covariance function reflects the character of spatial continuity better than the sample variogram. From both theoretical and practical considerations, clearly for most geostatistical problems, direct estimation of the covariance is better than the traditional variogram approach.This paper was presented at MGUS 87 Conference, Redwood City, California, 14 April 1987.     

Estimating monthly streamflow values by cokriging

Cokriging is applied to estimation of missing monthly streamflow values in three records from gaging stations in west central Virginia. Missing values are estimated from optimal consideration of the pattern of auto- and cross-correlation among standardized residual log-flow records. Investigation of the sensitivity of estimation to data configuration showed that when observations are available within two months of a missing value, estimation is improved by accounting for correlation. Concurrent and lag-one observations tend to screen the influence of other available observations. Three models of covariance structure in residual log-flow records are compared using cross-validation. Models differ in how much monthly variation they allow in covariance. Precision of estimation, reflected in mean squared error (MSE), proved to be insensitive to this choice. Cross-validation is suggested as a tool for choosing an inverse transformation when an initial nonlinear transformation is applied to flow values.     

基于移动开窗法协方差估计和方差分量估计的自适应滤波

基于移动窗口协方差估计和方差分量估计，提出了一种新的自适应Kalman滤波技术。计算结果证实，该方法能有效地控制观测异常和载体状态扰动异常对动态系统参数估值的影响。     

New anisotropic covariance models and estimation of anisotropic parameters based on the covariance tensor identity

 Many heterogeneous media and environmental processes are statistically anisotropic. In this paper we focus on range anisotropy, that is, stochastic processes with variograms that have direction dependent correlation lengths and direction independent sill. We distinguish between two classes of anisotropic covariance models: Class (A) models are reducible to isotropic after rotation and rescaling operations. Class (B) models can be separated into a product of one-dimensional functions oriented along the principal axes. We propose a new Class (A) model with multiscale properties that has applications in subsurface hydrology. We also present a family of Class (B) models based on non-Euclidean distance metrics that are generated by superellipsoidal functions. Next, we propose a new method for determining the orientation of the principal axes and the degree of anisotropy, i.e., the ratio(s) of the correlation lengths. This information reduces the degrees of freedom of anisotropic variograms and thus simplifies the estimation procedure. In particular, Class (A) models are reduced to isotropic and Class (B) models to one-dimensional functions. Our method is based on an explicit relation between the second-rank slope tensor (SRST), which can be estimated from the data, and the covariance tensor. The procedure is conceptually simple and numerically efficient. It is more accurate for regular (on-grid) data distributions, but it can also be used for sparse (off-grid) spatial distributions. In the case of non-differentiable random fields the method can be extended using generalized derivatives. We illustrate its implementation with numerical simulations.     

青海湖高寒湿地生态系统生长季CH4通量

利用涡度相关法研究青海湖高寒湿地生态系统2015-2016年生长季CH₄通量。结果显示：生长季CH₄通量表现为白天排放、夜间微弱吸收或排放的日变化特征,其中2015年CH₄通量日平均值为56.67 mg·m^-2,2016年CH₄通量日平均值为35.92 mg·m^-2。7月和8月排放量最大,生长季前期和后期排放较弱,2015年最大排放量出现在7月,为3.76 g·m^-2,2016最大排放量出现在8月,为1.67 g·m^-2。温度、电导率、土壤体积含水量与CH₄通量显著相关,气温和CH₄通量线性正相关。生态系统总初级生产力和呼吸及水热通量与CH₄通量也存在显著的相关关系,其中生态系统总初级生产力和呼吸是影响甲烷动态变化的主要因子。     

Long-term analysis of measured and simulated evapotranspiration and soil water content

In our study, we analysed a period from 2003 to 2012 with micrometeorological data measured at a boundary-layer field site operated by the Lindenberg Meteorological Observatory – Richard-Aßmann-Observatory of the German Meteorological Service (DWD). Amongst others, these data consist of real evapotranspiration (ETr) rates measured by eddy covariance and soil water contents determined by time domain reflectometry. Measured ETr and soil water contents were compared with those simulated by a simple soil–vegetation–atmosphere transfer (SVAT) scheme consisting of the FAO56 Penman-Monteith equation and the soil water flux model Hydrus-1D. We applied this SVAT scheme using uncompensatory and compensatory root water uptake (RWU). Soil water contents and ETr rates calculated using uncompensatory RWU showed an acceptable fit to the measured ones. In comparison, the use of compensatory RWU resulted in lower model performance due to higher deviations between measured and simulated soil moisture values and ETr rates during dry summer periods.     

塔克拉玛干沙漠北缘夏季典型晴天近地层湍流能谱特征

利用塔克拉玛干沙漠北缘肖塘地区涡动相关系统三维方向风速（u,v,w）、气温、CO₂、H₂O等观测数据,分析了夏季典型晴天不同大气稳定度条件下湍流功率谱和协谱。结果表明：大部分情况下湍流速度谱分布满足-2/3幂指数率,垂直方向高频段惯性副区符合程度更高,水平方向次之;CO₂和H₂O浓度则符合程度较低;温度谱与无因次频率总体上都具有很好的相关性。垂直风速与径向风速u的协谱斜率拟合值大多数情况下更接近-1,而在近中性层结条件下更符合-4/5斜线。稳定层结条件下的协谱峰值比不稳定层结时更大,且约大一个量级;不稳定层结条件下高频段协谱近直线型下降。u谱对应的谱峰波长随稳定度增加而减小,v谱和T谱对应的谱峰波长随稳定度的增加没有规律性增减;u、v、w、T谱谱峰波长约67~827、69~2417、4~54、12~661 m。     

多云条件有利于亚热带人工针叶林不同季节净生态系统碳吸收（英文）

太阳辐射的动态变化对生态系统固碳有重要影响,而不同天气条件下太阳辐射的改变对森林净生态系统碳交换(NEE)的影响还不明确。本研究利用亚热带人工针叶林生态系统2012年的通量数据和气象数据,分析了晴天、多云、阴天三种天气对NEE的影响。基于一年数据的研究结果表明:在不同季节中,不同天气下光响应曲线的变化没有季节性差异。和晴天条件相比,多云条件下的表观量子效率(?),150和750 W m^–2光强下的潜在光合速率(P₁₅₀和P₇₅₀)分别平均提高了82.3%、217.7%、22.5%;阴天条件下的α和P₁₅₀分别平均提高了118.5%和301%。中等辐射条件有利于NEE达到最大值,但低辐射条件对NEE有抑制作用。在大多数情况下,与晴天相比,多云下NEE的相对改变量(%NEE)为正,但阴天下为负。多云条件下最大%NEE的平均值在春夏秋冬分别为42.4%、34.1%、1.6%、-87.3%。本研究表明多云天气促进亚热带人工针叶林的潜在光合速率和NEE。