Modeling and forecast of the polar motion excitation functions for short-term polar motion prediction

Short-term forecast of the polar motion is considered by introducing a prediction model for the excitation function that drives the polar motion dynamics. The excitation function model consists of a slowly varying trend, periodic modes with annual and several sub-annual frequencies (down to the 13.6-day fortnightly tidal period), and a transient decay function with a time constant of 1.5 days. Each periodic mode is stochastically specified using a second-order auto-regression process, allowing its frequency, phase, and amplitude to vary in time within a statistical tolerance. The model is used to time-extrapolate the excitation function series, which is then used to generate a polar motion forecast dynamically. The skills of this forecast method are evaluated by comparison to the C-04 polar motion series. Over the lead-time horizon of four months, the proposed method has performed equally well to some of the state-of-art polar motion prediction methods, none of which specifically features forecasting of the excitation function. The annual mode in the ₂ component is energetically the most dominant periodicity. The modes with longer periods, annual and semi-annual in particular, are found to contribute more significantly to forecast accuracy than those with shorter periods.     

对分量进行联合解算的极移预报方法研究

为了提高极移预报的精度,该文提出结合极移的两个分量进行统一求解的极移联合预报方法:将极移的两个分量组成一个观测方程,并采用LS+AR模型对联合分量的确定项与随机项进行拟合。实验结果表明,文中采用的联合预报方法可以提高极移的预报精度。     

利用SVM与ARIMA组合模型进行大坝变形预测

由于大坝位移时间序列数据受各种复杂因素的影响,具有非平稳和非线性等特征,因此,利用传统、单一的时间序列预测模型较难准确地描述大坝位移变形的复杂规律.综合考虑大坝位移时间序列非线性和线性特征,本文提出了一种SVM和ARIMA相结合的时间序列预测模型.将大坝变形的时间序列分为非线性部分和线性部分.针对非线性部分,利用SVM...     

一种建筑沉降叠加预测方法

针对高层建筑的沉降监测与趋势预报问题,结合时间序列分析方法,该文提出一种基于ARMA的趋势项和随机项叠加预测法,把沉降监测时间序列数据分解为趋势项与随机项,分别建立趋势回归函数模型与随机项ARMA模型,叠加进行沉降量的预报,并通过上海外滩某高层建筑的沉降监测实例,研究并比较了该方法与传统的ARIMA差分预测法对建筑沉降预报精度的影响。实验结果表明:基于ARMA的趋势项和随机项叠加预测法在沉降预报中精度优于基于ARIMA的差分预测法。该方法利用趋势回归函数的保持作用,克服了传统的时间序列ARIMA模型在长期预测中精度不高的问题,并且随着预测步长的增加,优势更加明显。     

利用 ARMA 模型短期预报北极地区电离层 T EC

北极地区电离层结构分布较为特殊,存在梯度变化。利用时间序列分析中的自回归移动平均模型(Autoregressive Moving Average,ARMA)对欧洲定轨中心(CODE)发布的北纬67.5°~87.5°以及利用反距离加权插值法得到的90°的格网数据逐点进行建模,分别利用7d、10d、20d、30d、40d、50d的电离层TEC值为样本数据采用线性最小方差法进行预报分析。结果表明:90%以上的预报绝对误差小于3TECU,预报精度随TEC样本序列长度的增加而提高,但样本序列增加到一定值后,相对精度提高不大;相同样本数据的预报精度随预报时间长度的增加而降低,起初不是很明显,超过20d后精度降低明显且波动幅度较大。尽管北极地区存在梯度变化,ARMA模型在北极地区具有较高的预报精度,是一种比较理想的预报方法。     

Prediction of polar motion

Based on an analysis of polar motion behavior, we found the possibility of predicting polar motion up to one year in advance. Comparing these predicted polar coordinates with the observed ones (smoothed), the rms of the differences is about 0".02. The differences of the relative polar motion are much smaller. For any time interval of 20–30 days throughout the whole year, the rms of the relative polar motion differences is about 0".01. It appears that 80–90% of the polar motion is composed of the stable, predictable Chandler and annual terms.     

一种组合模型在卫星钟差长期预报中的应用研究

近年来,卫星钟差长期预报普遍采用灰色模型,该模型的预报精度虽较传统的二次多项式模型有所提高,但仍不理想。本文在其基础上提出了一种新的组合模型:首先利用灰色模型估计的残差建立二次多项式模型,预报以后历元的残差,然后和灰色模型的预报结果相加;并分析了利用不同历元个数的残差建模所得组合模型的精度,将组合模型与灰色模型、二次多项式模型的预报精度进行了比较。结果表明:组合模型相对于灰色模型的预报精度能提高一个数量级左右,验证了本文提出的组合模型的可行性和有效性。     

Atmospheric excitation of polar motion

The polar motion excited by the fluctuation of global atmospheric angular momentum (AAM) is investigated. Based on the global AAM data, numerical results demonstrate that the fluctuation of AAM can excite the seasonal wobbles (e.g., the 18-month wobble) and the Chandler wobble, which agree well with previous studies. In addition, by filtering the dominant low frequency components, some distinct polar wobbles corresponding to some great diurnal and semi-diurnal atmospheric tides are found.     

Atmospheric excitation of polar motion

The polar motion excited by the fluctuation of global atmospheric angular momentum (AAM) is investigated. Based on the global AAM data, numerical results demonstrate that the fluctuation of AAM can excite the seasonal wobbles (e.g., the 18-month wobble) and the Chandler wobble, which agree well with previous studies. In addition, by filtering the dominant low frequency components, some distinct polar wobbles corresponding to some great diurnal and semi-diurnal atmospheric tides are found.     

Doppler satellite observations of polar motion

Observations on Navy navigation satellites made by thirteen Doppler receiving stations have been used to determine the position of the earth's pole daily for a six month period of time. A precision of one meter has been obtained on the basis of forty-eight hours of observations on one satellite. No bias is apparant between computations based on different satellites, but differences of about a meter exist with respect to values published by the Bureau International de l'Heure on the basis of astronomical observations.     

Analysis of secular polar motion and continental drift

The secular latitude variations of the five ILS stations of Mizusawa, Kitab, Carloforte, Gaithersburg and Ukiah were analyzed taking into account the recent continental drift theory. Using Le Pichon's 1968 reconstruction, the rate of rotation was computed from the astronomical data, fixing the pole of rotation by Le Pichon's determination. The most reasonable solution was obtained considering Mizusawa, Kitab and Carloforte lying on the Eurasia plate, the two American stations as one on the American plate (Gaithersburg) and the other on the North—East Pacific plate (Ukiah). The resulting relative rate between the Euro-American plates is found to be 0".0028/year and between the American—Pacific plates 0".0032/ years, or about 1°,3/10⁶ years and in excellent agreement with the plate tectonic theory. Luxembourg Meeting of the “Journées Luxembourgeoises de Géodynamique”, 1972.     

An improved empirical model for the effect of long-period ocean tides on polar motion

Because the tide-raising potential is symmetric about the Earth’s polar axis it can excite polar motion only by acting upon non-axisymmetric features of the Earth like the oceans. In fact, after removing atmospheric and non-tidal oceanic effects, polar motion excitation observations show a strong fortnightly tidal signal that is not completely explained by existing dynamical and empirical ocean tide models. So a new empirical model for the effect of the termensual (Mtm and mtm), fortnightly (Mf and mf), and monthly (Mm) tides on polar motion is derived here by fitting periodic terms at these tidal frequencies to polar motion excitation observations that span 2 January 1980 to 8 September 2006 and from which atmospheric and non-tidal oceanic effects have been removed. While this new empirical tide model can fully explain the observed fortnightly polar motion excitation signal during this time interval it would still be desirable to have a model for the effect of long-period ocean tides on polar motion that is determined from a dynamical ocean tide model and that is therefore independent of polar motion observations.     

Polar motion for an elastic earth model using a canonical theory

The purpose of this paper is to develop a canonical formulation of the rotational motion for an elastic Earth model. We have obtained the canonical equations for the precession and nutation motion in an inertial frame, and from this we have deduced the equations in an Earth-fixed frame. The linearized equations deduced for polar motion are equivalent to those obtained using Liouville's equations.     

Atmospheric and oceanic forcing of the rapid polar motion

The rapid polar motion for periods below 20 days is revisited in light of the most recent and accurate geodetic and geophysical data. Although its amplitude is smaller than 2 mas, it is excited mostly by powerful atmospheric processes, as large as the seasonal ones. The residual amplitude, representing about 20% of the total excitation, stems from the oceans. Rapid polar motion has an irregular nature that is well explained by the combined influence of the atmosphere and the oceans. An overall spectrum reveals cycles principally at 20, 13.6 (fortnightly tidal period) and 10 days (corresponding to the normal atmospheric mode Y₃¹{\Psi_3^1}), but this is only an averaged feature hiding its strong variability over seasonal time scales. This explains why it is so delicate to determine an empirical model of the tidal effect on polar motion. The variability in both amplitude and phase of the 13.6-day term is probably caused by a lunar barometric effect, modulated by some sub-seasonal thermal processes. The irregularities of the prominent cycles of the short-term polar motion are well explained by the atmospheric and oceanic excitations. The oceanic variability reinforces the atmospheric one, as they were triggered by the same agent, maybe seasonal and inter-annual thermal variations.     

Evidence and cause of climate cycles in polar motion

 The long-term variation of polar motion contains a number of periods similar to climate cycles. Two possible causes for these long-term variations are mass redistributions produced by variations of atmospheric and oceanic circulation, and mass exchanges between the cryosphere and hydrosphere. Inner-core wobble, which can be inferred from the observed motion of the geomagnetic pole, is another phenomenon with periods similar to climate cycles. Only observations relating to mass redistributions caused by atmosphere dynamics and inner-core wobble are available for sufficiently long periods of time to investigate their influence on climate cycles in polar motion. Both processes contribute to climate cycles in polar motion, but they cannot completely explain these cycles. Possible sources of climate cycles are discussed. Received: 20 December 1999 / Accepted: 28 August 2000     

Influence of subdaily polar motion model on nutation offsets estimated by very long baseline interferometry

This paper studies the connection between the subdaily model for polar motion used in the processing of very long baseline interferometry (VLBI) observations and the estimated nutation offsets. By convention accepted by the International Earth Rotation Service, the subdaily model for polar motion recommended for routine processing of geodetic observations does not contain any daily retrograde terms due to their one-to-one correlation with the nutation. Nevertheless, for a 24-h VLBI solution a part of the signal contained in the polar motion given by the used subdaily model is numerically mistaken for a retrograde daily sidereal signal. This fictitious retrograde daily signal contributes to the estimated nutation, leading to systematic differences between the nutation offsets from VLBI solutions computed with different subdaily polar motion models. We demonstrate this effect using solutions for all suitable 24-h VLBI sessions over a time span of 11 years (2000–2011). By changing the amplitudes of one tidal term in the underlying subdaily model for polar motion and comparing the estimated parameters to the solutions computed with the unchanged subdaily model, the paper shows and explains theoretically the effects produced by the individual subdaily terms on the VLBI nutation estimates.     

CPSO-BP组合优化模型的滑坡位移预测

针对粒子群优化BP神经网络模型存在的不足,该文在粒子群算法中引入混沌理论,建立混沌粒子群算法优化BP神经网络的组合优化模型。以四川省凉山彝族自治州某滑坡的位移监测数据为例,将混沌粒子群算法优化BP神经网络模型与其他优化粒子群算法与BP神经网络组合模型的预测结果进行对比分析。实验结果表明,基于混沌粒子群算法优化BP神经网络的预测模型,滑坡水平位移与垂直位移的预测值与相应的实测值相对误差的平均值分别为1.05%和0.78%,平均绝对误差分别为0.825 0和0.460 1mm,均方根误差分别为1.000 5和0.527 5mm,实验结果验证了该文预测模型结果能更好地反映滑坡位移趋势,具有较好的实用性。     

灰时序GM-AR模型在建筑物沉降变形预测中的应用

本文以现代高层建筑沉降变形预测为主要研究目的,讨论了灰色GM(1,1)模型和时序AR模型的特点和适用范围,从预测的角度对灰色和时序模型进行了比较和分析;提出了基于优化灰参数α、u的GM(1,1)模型和AR组合模型预测高层建筑物沉降变形的新方法;将变形量分解成具有确定性的趋势项和具有不确定性的随机项,建立GM-AR模型分别对趋势项和随机项进行预测,应用结果表明,该方法使预测结果更为可靠、准确。     

EARTH ROTATION EQUATIONS CONTAINING BOTH NUTATION AND POLAR MOTION

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