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1.
Practical implementation of Hilbert-Huang Transform algorithm 总被引：12，自引：0，他引：12
Hilbert-Huang Transform (HHT) is a newly developed powerful method for nonlinear and non-stationary time series analysis. The empirical mode decomposition is the key part of HHT, while its algorithm was protected by NASA as a US patent, which limits the wide application among the scientific community. Two approaches, mirror periodic and extrema extending methods, have been developed for handling the end effects of empirical mode decomposition. The implementation of the HHT is realized in detail to widen the application. The detailed comparison of the results from two methods with that from Huang et al. (1998, 1999), and the comparison between two methods are presented. Generally, both methods reproduce faithful results as those of Huang et al. For mirror periodic method (MPM), the data are extended once forever. Ideally, it is a way for handling the end effects of the HHT, especially for the signal that has symmetric waveform. The extrema extending method (EEM) behaves as good as MPM, and it is better t 相似文献
2.
In order to clarify the formation and circulation of the Japan/East Sea Intermediate Water (JESIW) and the Upper portion of
the Japan Sea Proper Water (UJSPW), numerical experiments have been carried out using a 3-D ocean circulation model. The UJSPW
is formed in the region southeast off Vladivostok between 41°N and 42°N west of 136°E. Taking the coastal orography near Vladivostok
into account, the formation of the UJSPW results from the deep water convection in winter which is generated by the orchestration
of fresh water supplied from the Amur River and saline water from the Tsushima Warm Current under very cold conditions. The
UJSPW formed is advected by the current at depth near the bottom of the convection and penetrates into the layer below the
JESIW. The origin of the JESIW is the low salinity coastal water along the Russian coast originated by the fresh water from
the Amur River. The coastal low salinity water is advected by the current system in the northwestern Japan Sea and penetrates
into the subsurface below the Tsushima Warm Current region forming a subsurface salinity minimum layer.
This revised version was published online in August 2006 with corrections to the Cover Date. 相似文献
3.
给出了提取潮汐调和常数的一种新方法--正交方法,并应用1992～1997年的TOPEX/POSEIDON卫星高度计遥感资料,提取中国海M2分潮调和常数.同时,利用最小二乘法来提取中国海M2分潮调和常数,两种方法结果比较渤海、黄海、东海海域M2分潮振幅、迟角的均方差分别是3.3 cm,3.6°;南中国海海域M2分潮振幅、迟角均方差分别是1.1 cm,1.7°,结果表明正交方法是一种可信的具有实用性的方法. 相似文献
4.
近45 a东北地区春季降水异常的气候特征 总被引：8，自引：0，他引：8
利用1959-2003年我国东北地区93站春季降水资料，将降水场分成5个区域，并在此基础之上分析了春季降水的时空变化特征，发现：降水量年际变化及长期趋势有明显的区域差异，呈东多西少的分布特征；西部是旱涝易发生区，近45a来降水量略有增多；降水量的周期振荡存在明显的区域差异。 相似文献
5.
6.
Nils-Otto Kitterrød Lars Gottschalk 《Stochastic Environmental Research and Risk Assessment (SERRA)》1997,11(6):459-482
Simulation of multigaussian stochastic fields can be made after a Karhunen-Loéve expansion of a given covariance function.
This method is also called simulation by Empirical Orthogonal Functions. The simulations are made by drawing stochastic coefficients
from a random generator. These numbers are multiplied with eigenfunctions and eigenvalues derived from the predefined covariance
model. The number of eigenfunctions necessary to reproduce the stochastic process within a predefined variance error, turns
out to be a cardinal question. Some ordinary analytical covariance functions are used to evaluate how quickly the series of
eigenfunctions can be truncated. This analysis demonstrates extremely quick convergence to 99.5% of total variance for the
2nd order exponential (‘gaussian’) covariance function, while the opposite is true for the 1st order exponential covariance
function. Due to these convergence characteristics, the Karhunen-Loéve method is most suitable for simulating smooth fields
with ‘gaussian’ shaped covariance functions. Practical applications of Karhunen-Loéve simulations can be improved by spatial
interpolation of the eigenfunctions. In this paper, we suggest interpolation by kriging and limits for reproduction of the
predefined covariance functions are evaluated. 相似文献
7.
Simulation of multigaussian stochastic fields can be made after a Karhunen-Loéve expansion of a given covariance function.
This method is also called simulation by Empirical Orthogonal Functions. The simulations are made by drawing stochastic coefficients
from a random generator. These numbers are multiplied with eigenfunctions and eigenvalues derived from the predefined covariance
model. The number of eigenfunctions necessary to reproduce the stochastic process within a predefined variance error, turns
out to be a cardinal question. Some ordinary analytical covariance functions are used to evaluate how quickly the series of
eigenfunctions can be truncated. This analysis demonstrates extremely quick convergence to 99.5% of total variance for the
2nd order exponential (‘gaussian’) covariance function, while the opposite is true for the 1st order exponential covariance
function. Due to these convergence characteristics, the Karhunen-Loéve method is most suitable for simulating smooth fields
with ‘gaussian’ shaped covariance functions. Practical applications of Karhunen-Loéve simulations can be improved by spatial
interpolation of the eigenfunctions. In this paper, we suggest interpolation by kriging and limits for reproduction of the
predefined covariance functions are evaluated. 相似文献
8.
1. IntroductionPacific Decadal Oscillation (PDO) is a long-termENSO-like variability of the North Pacific. It can becharacterized by the first principal component of EOFof the North Pacific SST (Zhu and Yang, 2003; Tren-berth, 1990; Yang and Zhang, 2003). ENSO is thestrongest signal of annular change of global climatesystem (Trenberth, 1997). The spatial pattern of PDOis a wedge similar to El Nino. In the cool (warm)phases of PDO, the central and northwest Pacific is ofwarm (co… 相似文献
9.
10.