Operational Evaluation of the Quantitative Precipitation Estimation by a CINRAD-SA Dual Polarization Radar System

In this paper, the quantitative precipitation estimation based on hydrometeor classification (HCA-QPE) algorithm was proposed for the first operational S band dual-polarization radar promoted by the CINRAD/SA radar of China. The HCA-QPE algorithm, the localized Colorado State University-Hydrometeor Identification of Rainfall (CSU-HIDRO) and Joint Polarization Experiment (JPOLE) algorithms, and the dynamic Z-R relationships based on variational correction QPE (DRVC-QPE) algorithm were evaluated with the rainfall events from March 1 to October 30, 2017 in the Guangdong Province. The results indicated that even though the HCA-QPE algorithm did not use the observed rainfall data for correction, its estimation accuracy was better than that of the DRVC-QPE algorithm when the rainfall rate was greater than 5mm h^(-1); and the stronger the rainfall intensity, the greater the QPE improvement. And the HCA-QPE algorithm worked better than the localized CSU-HIDRO and JPOLE algorithms. This study preliminarily verified the improved accuracy of QPE by a dual-polarization radar system modified from CINRAD-SA radar.     

一种两步抗差估计的设计及其解算

抗差估计的关键是选择适当的权函数和合理的调制因子,针对这两个重要问题,在研究当前调制因子取值方法的基础之上,提出了可动性调制因子这一新概念,并基于可动性调制因子、IGG方案权函数,设计了两步抗差估计。两步抗差估计解决了抗差估计中传统的调制因子、方差因子、初值三者取值时存在的一系列问题,尤其当三者取值不能协调配制时出现的秩亏问题,从而使抗差估计方法更具有实际意义和广泛意义。     

基于逆算子估计的AVO反演方法研究

传统反演算法以优化算法为主,而基于逆算子估计的AVO反演算法则利用了直接求逆的思路.算法的关键在于寻找存在逆函数的子域,进而可以在子域内直接求逆,这种解决反问题的思路不同于一般的优化类算法所采用的直接搜索解的方式,具有更高的效率.AVO反演利用了振幅随着偏移距的变化特征,反演的精度受到地震资料质量的影响,通过加入L1范数约束以及合理的初始模型有助于提高反演的稳定性以及准确度.模型测算和实际应用表明,基于逆算子估计的AVO反演方法具有较高的精确程度和可靠性.     

A Comparison of De-noising Methods for Differential Phase Shift and Associated Rainfall Estimation

Measured differential phase shift ΦDP is known to be a noisy unstable polarimetric radar variable, such that the quality of ΦDP data has direct impact on specific differential phase shift KDP estimation, and subsequently, the KDP-based rainfall estimation. Over the past decades, many ΦDP de-noising methods have been developed; however, the de-noising effects in these methods and their impact on KDP-based rainfall estimation lack comprehensive comparative analysis. In this study, simulated noisy ΦDP data were generated and de-noised by using several methods such as finite-impulse response(FIR), Kalman, wavelet,traditional mean, and median filters. The biases were compared between KDP from simulated and observedΦDP radial profiles after de-noising by these methods. The results suggest that the complicated FIR, Kalman,and wavelet methods have a better de-noising effect than the traditional methods. After ΦDP was de-noised,the accuracy of the KDP-based rainfall estimation increased significantly based on the analysis of three actual rainfall events. The improvement in estimation was more obvious when KDP was estimated with ΦDP de-noised by Kalman, FIR, and wavelet methods when the average rainfall was heavier than 5 mm h-1.However, the improved estimation was not significant when the precipitation intensity further increased to a rainfall rate beyond 10 mm h-1. The performance of wavelet analysis was found to be the most stable of these filters.     

速度差对井间走时层析成像质量的影响及其改进方法

在井间地震初至走时层析成像中,随着相邻地质体速度差的增大,使得射线分布不均匀,以及网格剖分不合适,导致层析成像结果不理想.物理和数值模型的井间走时层析成像表明：当速度差超过30.0%时,层析结果畸变较大;在30.0%～15.0%之间时,层析结果较好;低于15.0%时,层析结果好.在此基础上,提出了井间多尺度初至走时层析成像方法,即对同一模型采用多种网格剖分来同时进行层析成像,以获得研究区域的速度图像.数学和物理模型的井间多尺度走时层析结果表明：该方法很好地兼顾了层析成像的分辨率和精度,极大地改善了井间地震层析成像的质量.即使速度差超过30%,其多尺度的层析结果仍然较好.因此,这种方法具有实际应用的潜力.     

歧口凹陷深层地震岩石物理特征分析及应用

为明确歧口凹陷深层的岩石物理及AVO响应特征,分析歧口地区全波测井资料,优选该区敏感岩石物理参数;根据分岩性拟合求取纵横波转换经验公式,并采用流体置换原理进行叠前地震道集正演后提取AVO属性.结果表明:泊松比、纵横波速度比为该区有利储层预测的敏感参数,含气砂岩与含水砂岩的数值范围差异明显;歧口深层AVO响应特征可划分为3类:第一类是与气层相对应的反射振幅随着偏移距的增大而负向急剧增大;第二类是与油气同层相对应的反射振幅随着偏移距的增大而负向缓慢增大;第三类是与油水层及干层相对应的反射振幅随着偏移距的增大而负向减小.该结果可为歧口凹陷深层开展流体预测可行性提供依据.     

基于抗差估计的GPS／CoMPASS组合实时差分定位算法

在GPS／cOMPASS组合差分定位基础上,引入抗差估计方法,通过降权调整合有粗差观测值对定位的影响,利用路测试验,对比RTK的厘米级定位,结果表明：抗差GPS／COMPASS组合实时差分定位优于非抗差定位,平面精度在2．0m左右。     

Variogram Model Selection via Nonparametric Derivative Estimation

Before optimal linear prediction can be performed on spatial data sets, the variogram is usually estimated at various lags and a parametric model is fitted to those estimates. Apart from possible a priori knowledge about the process and the user's subjectivity, there is no standard methodology for choosing among valid variogram models like the spherical or the exponential ones. This paper discusses the nonparametric estimation of the variogram and its derivative, based on the spectral representation of positive definite functions. The use of the estimated derivative to help choose among valid parametric variogram models is presented. Once a model is selected, its parameters can be estimated—for example, by generalized least squares. A small simulation study is performed that demonstrates the usefulness of estimating the derivative to help model selection and illustrates the issue of aliasing. MATLAB software for nonparametric variogram derivative estimation is available at http://www-math.mit.edu/~gorsich/derivative.html. An application to the Walker Lake data set is also presented.     

长江流域沿江镉异常源追踪与定量评估的方法技术研究:以长江流域安徽段为例

长江全流域性的Cd异常是被中国正在进行的多目标地球化学调查发现的重大生态环境问题。以长江流域安徽段为研究对象,对沿江镉异常源追踪与定量评估的方法技术进行了系统研究。通过对安徽段长江干流及其主要支流悬浮物中元素含量的测量查明:悬浮物是流域内重金属元素大跨度迁移的主要载体;Cd在悬浮物中的富集程度远远大于其他重金属元素,这或许正是Cd可以形成沿江流域性异常的主要原因;长江干流悬浮物中重金属元素含量的变化明显受到沿江支流的影响。安徽段长江干流及其主要支流重金属元素输出通量定量计算结果表明:秋蒲河是安徽段重金属元素输出通量最大的支流,每年在安徽段长江两岸土壤中沉积下约4.45t的Cd。利用悬浮物加密测量、1∶5万土壤测量和岩石测量对顺安河流域Cd异常源追踪结果显示:内生金属矿床特别是铅锌矿是悬浮物中Cd的最大的供应源。采用河漫滩沉积物分层采样技术和同位素测年技术,初步恢复了研究区Cd等重金属元素沉积和污染的地球化学历史,对研究区Cd等重金属元素异常的未来演变趋势进行了预警预测。