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1.
D. Markovic  M. Koch 《水文研究》2014,28(4):2202-2211
Long‐term variations and temporal scaling of mean monthly time series of river flow, precipitation, temperature, relative humidity, air pressure, duration of bright sunshine, degree of cloud cover, short wave radiation, wind speed and potential evaporation within or in vicinity of the German part of the Elbe River Basin are analyzed. Statistically significant correlations between the 2–15 year scale‐averaged wavelet spectra of the hydroclimatic variables and the North Atlantic Oscillation‐ and Arctic Oscillation index are found which suggests that such long‐term patterns in hydroclimatic time series are externally forced. The Hurst parameter estimates (H) based on the Detrended Fluctuation Analysis (DFA) indicate persistence for discharge, precipitation, wind speed, air pressure and the degree of cloud cover, all having an annual cycle and a broad low‐frequency distribution. Also, DFA H parameter estimates are higher for discharge than for precipitation. The major long‐term quasi‐periodic variability modes of precipitation detected using Singular Spectrum Analysis coincide with those detected in the discharge time series. Upon subtraction of these low‐frequency quasi‐periodic modes, the DFA H parameter estimates suggest absence of the persistence for both precipitation and discharge. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   
2.
With the progress in computational power and seismic acquisition, elastic reverse time migration is becoming increasingly feasible and helpful in characterizing the physical properties of subsurface structures. To achieve high-resolution seismic imaging using elastic reverse time migration, it is necessary to separate the compressional (P-wave) and shear (S-wave) waves for both isotropic and anisotropic media. In elastic isotropic media, the conventional method for wave-mode separation is to use the divergence and curl operators. However, in anisotropic media, the polarization direction of P waves is not exactly parallel to the direction of wave propagation. Also, the polarization direction of S-waves is not totally perpendicular to the direction of wave propagation. For this reason, the conventional divergence and curl operators show poor performance in anisotropic media. Moreover, conventional methods only perform well in the space domain of regular grids, and they are not suitable for elastic numerical simulation algorithms based on non-regular grids. Besides, these methods distort the original wavefield by taking spatial derivatives. In this case, a new anisotropic wave-mode separation scheme is developed using Poynting vectors. This scheme can be performed in the angle domain by constructing the relationship between group and polarization angles of different wave modes. Also, it is performed pointwise, independent of adjacent space points, suitable for parallel computing. Moreover, there is no need to correct the changes in phase and amplitude caused by the derivative operators. By using this scheme, the anisotropic elastic reverse time migration is more efficiently performed on the unstructured mesh. The effectiveness of our scheme is verified by several numerical examples.  相似文献   
3.
GRAPES全球奇异向量方法改进及试验分析   总被引:4,自引:0,他引:4       下载免费PDF全文
李晓莉  刘永柱 《气象学报》2019,77(3):552-562
基于总能量模的奇异向量扰动常用于构造集合预报的初始条件。以建立GRAPES(Global and Regional Assimilation PrEdiction System)全球集合预报系统为目的,基于前期研发的GRAPES全球模式奇异向量方法,在GRAPES全球切线性模式和伴随模式2.0版的框架下,开展了引入线性化边界层方案来改善奇异向量结构,并提高奇异向量计算效率的研究。通过连续试验,从奇异向量的扰动能量结构、扰动能量谱及扰动空间分布等方面,综合分析改进GRAPES全球奇异向量的结构及演变特征。试验结果表明,改进后的GRAPES奇异向量方法有效抑制了之前扰动能量在近地面层不合理的快速增长,同时,奇异向量最优扰动的结构更客观地体现了中高纬度区域大气初始条件中的斜压不稳定扰动及其演变,如在初始时刻奇异向量扰动能量主要位于对流层中层,并呈现出随高度向西倾斜的大气斜压特征;经过线性化演变,扰动能量向较大水平尺度转移,并在垂直结构上表现出向对流层高层上传及向对流层低层下传的特征等。针对GRAPES奇异向量迭代求解中伴随模式计算耗时为主的情况,改进伴随模式中广义共轭余差方案的调用方式,并采用大内存存储法来提高其计算效率,进而将奇异向量总计算时间缩短了25%。总之,改进后的GRAPES奇异向量方法,可应用于构建面向业务应用的GRAPES全球集合预报系统。   相似文献   
4.
针对相对重力测量数据中存在的重力固体潮信号,本文提出将奇异谱分析方法(Singular Spectrum Analysis,SSA)应用到相对重力测量数据处理中,在不需要测站坐标等先验信息的条件下从相对重力数据中提取重力固体潮,提供了一种获取重力固体潮的新思路.采用模拟的相对重力数据进行实验,利用SSA方法和小波变换方法分别从模拟信号中提取重力固体潮并进行结果对比,SSA获取的重力固体潮与理论值残差RMS为0.3 μGal,小波方法获取的残差RMS为1.6 μGal.利用CG-5相对重力仪实测数据进行实验,提出一种利用SSA外推时间序列来削弱边界效应的新思路,实验结果显示采用这种方法后重力固体潮值与理论值残差序列的RMS和STD均有所减小.通过实验发现削弱边界效应后SSA提取的重力固体潮与采用Tamura潮波表计算的重力固体潮理论值残差RMS值为2.2 μGal.利用SSA提取的零点漂移值与最小二乘拟合得到的结果基本一致,十天内的差值小于0.4 μGal/d.  相似文献   
5.
??RINEX HO???????GPS?????λ?????е???(?????????)????????????????????GPS???????е??????????(ΔIH)p,qi,g??????????(ΔIH)p,qi,g????γ?????????????????????????????????????????????????????£???Bernese 5.0???????????????????????????????δ???и????????????????????л????????????????????????????????ΔbH???????????ΔbH???????С????????????????????Δ??b??H??????????????????????????????????????????ε??С??ΔbH?????????  相似文献   
6.
本文在对地震波场进行模拟时,采用辛差分格式对波动方程进行时间离散,采用奇异核褶积微分算子对波动方程进行空间离散.该方法尽管增加了一些计算量,但提高了计算精度和稳定性;相对于其他非辛算法,它是全局保结构的,并且具有较强的长时间跟踪能力.该方法为解决大尺度、长时程地震波场的高精度模拟问题提供了一种新的、有效的选择.  相似文献   
7.
Based on the NCEP (National Centers for Environmental Prediction) data, the relationship between the Sea Surface Temperature Anomalies (SSTAs) in the North Pacific and the atmospheric circulation anomalies in January 2008 is analyzed in this study. The SSTA mode most correlated with the Geopotential Height anomalies (GHAs) in January 2008 in the North Pacific exhibited a basin-wide horseshoe pattern with a warm center in November 2007. This persistent SSTA pattern would induce positive GHAs in the Aleutian Low area and East Asia and the northward extension of the West Pacific Subtropical High in January 2008 by maximum diabatic heating in the atmosphere over the Kuroshio Oyashio Extension (KOE) area, leading to the occurence of the circumpolar trough-ridge wave train anomaly in January 2008.  相似文献   
8.
对损伤部位向量(DLV)法作了简单介绍,并用该方法对钢框架进行了损伤识别和损伤定位。该方法假定结构损伤前后为线性,对结构损伤前后柔度矩阵差进行奇异值分解,将奇异值为零所对应的向量,作为静荷载施加在无损结构的测点位置,则应力为零的单元为可能损伤的单元。对3种不同工况的钢框架进行了振动模态试验,用前3阶模态参数构造框架的柔度矩阵,按照DLV法对其进行了损伤识别,识别结果与已知损伤情况相一致。从测试自由度不完备、噪声和振型质量归一化系数这3个方面对识别效果进行了分析,结果表明:当损伤使结构动力特性有微小改变时,使用该方法不易定位损伤,应结合局部损伤识别方法进行判定;当损伤使结构动力特性有较大改变时,该方法能有效识别损伤的单元。DLV方法概念简单,理论明确,不受结构类型的限制,不需要结构的数学模型和模型缩聚或扩展技术,只需获得结构损伤前后的前几个低阶模态参数,即可识别结构一处或多处损伤,实际应用时可操作性强。  相似文献   
9.
The extraction of object features from massive unstructured point clouds with different local densities, especially in the presence of random noisy points, is not a trivial task even if that feature is a planar surface. Segmentation is the most important step in the feature extraction process. In practice, most segmentation approaches use geometrical information to segment the 3D point cloud. The features generally include the position of each point (X, Y and Z), locally estimated surface normals and residuals of best fitting surfaces; however, these features could be affected by noisy points and in consequence directly affect the segmentation results. Therefore, massive unstructured and noisy point clouds also lead to bad segmentation (over-segmentation, under-segmentation or no segmentation). While the RANSAC (random sample consensus) algorithm is effective in the presence of noise and outliers, it has two significant disadvantages, namely, its efficiency and the fact that the plane detected by RANSAC may not necessarily belong to the same object surface; that is, spurious surfaces may appear, especially in the case of parallel-gradual planar surfaces such as stairs. The innovative idea proposed in this paper is a modification for the RANSAC algorithm called Seq-NV-RANSAC. This algorithm checks the normal vector (NV) between the existing point clouds and the hypothesised RANSAC plane, which is created by three random points, under an intuitive threshold value. After extracting the first plane, this process is repeated sequentially (Seq) and automatically, until no planar surfaces can be extracted from the remaining points under the existing threshold value. This prevents the extraction of spurious surfaces, brings an improvement in quality to the computed attributes and increases the degree of automation of surface extraction. Thus the best fit is achieved for the real existing surfaces.  相似文献   
10.
A deterministic method for sensitivity analysis is developed and applied to a mathematical model for the simulation of flow in porous media. The method is based on the singular value decomposition (SVD) of the Jacobian matrix of the model. It is a local approach to sensitivity analysis providing a hierarchical classification of the directions in both the input space and of those in the output space reflecting the degree of sensitiveness of the latter to the former. Its low computational cost, in comparison with that of statistical approaches, allows the study of the variability of the results of the sensitivity analysis due to the variations of the input parameters of the model, and thus it can provide a quality criterion for the validity of more classical probabilistic global approaches. For the example treated here, however, this variability is weak, and deterministic and statistical methods yield similar sensitivity results.  相似文献   
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