Application of singular spectrum analysis and multilayer perceptron in the mid-long-term polar motion prediction

2021 ◽  
Author(s):  
Xin Jin ◽  
Jinyun Guo ◽  
Yi Shen ◽  
Xin Liu ◽  
Chunmei Zhao
Keyword(s):  
Spectrum Analysis ◽  
Multilayer Perceptron ◽  
Polar Motion ◽  
Singular Spectrum Analysis ◽  
Motion Prediction ◽  
Singular Spectrum ◽  
Polar Motion Prediction

Application of singular spectrum analysis in reconstruction of the annual signal from GRACE

2020 ◽  
Vol 14 (3) ◽  
pp. 295-302
Author(s):  
Chuandong Zhu ◽  
Wei Zhan ◽  
Jinzhao Liu ◽  
Ming Chen
Keyword(s):  
Time Series ◽  
Spectrum Analysis ◽  
Singular Spectrum Analysis ◽  
Mixture Effect ◽  
Singular Spectrum ◽  
Grace Data ◽  
Terrestrial Water ◽  
Annual Signal ◽  
Long Term Variations

AbstractThe mixture effect of the long-term variations is a main challenge in single channel singular spectrum analysis (SSA) for the reconstruction of the annual signal from GRACE data. In this paper, a nonlinear long-term variations deduction method is used to improve the accuracy of annual signal reconstructed from GRACE data using SSA. Our method can identify and eliminate the nonlinear long-term variations of the equivalent water height time series recovered from GRACE. Therefore the mixture effect of the long-term variations can be avoided in the annual modes of SSA. For the global terrestrial water recovered from GRACE, the peak to peak value of the annual signal is between 1.4 cm and 126.9 cm, with an average of 11.7 cm. After the long-term and the annual term have been deducted, the standard deviation of residual time series is between 0.9 cm and 9.9 cm, with an average of 2.1 cm. Compared with the traditional least squares fitting method, our method can reflect the dynamic change of the annual signal in global terrestrial water, more accurately with an uncertainty of between 0.3 cm and 2.9 cm.

scholarly journals A high-resolution δ<sup>18</sup>O record and Mediterranean climate variability

2014 ◽  
Vol 10 (5) ◽  
pp. 4057-4084
Author(s):  
C. Taricco ◽  
G. Vivaldo ◽  
S. Alessio ◽  
S. Rubinetti ◽  
S. Mancuso
Keyword(s):  
High Resolution ◽  
Spectrum Analysis ◽  
Singular Spectrum Analysis ◽  
Ionian Sea ◽  
Data Set ◽  
Singular Spectrum ◽  
Proxy Records ◽  
Long Term Trends ◽  
Temperature Proxy

Abstract. A~high-resolution, well-dated foraminiferal δ18O record from a shallow-water core drilled from the Gallipoli Terrace in the Gulf of Taranto (Ionian Sea), previously measured over the last two millennia, has been extended to cover 707 BC–1979 AD. Spectral analysis of this series, performed by Singular Spectrum Analysis (SSA) and other classical and advanced methods, strengthens the results obtained analysing the shorter δ18O profile, detecting the same highly significant oscillations of about 600 yr, 380 yr, 170 yr, 130 yr, and 11 yr, respectively explaining about 12%, 7%, 5%, 2% and 2% of the time series total variance, plus a millennial trend (18% of the variance). The comparison with the results of Multi-channel Singular Spectrum Analysis (MSSA) applied to a data set of 26 Northern Hemisphere (NH) temperature-proxy records shows that NH temperature anomalies share with our local record a long-term trend and a bicentennial cycle. These two variability modes, previously identified as temperature-driven, are the most powerful modes in the NH temperature data set. Both the long-term trends and the bicentennial oscillations, when reconstructed locally and hemispherically, show coherent phases. Also the corresponding local and hemispheric amplitudes are comparable, if changes in the precipitation-evaporation balance of the Ionian sea, presumably associated with temperature changes, are taken into account.

scholarly journals Application of advanced statistical methods for extracting long-term trends in static monitoring data from an arch dam

2011 ◽  
Vol 10 (6) ◽  
pp. 587-601 ◽  
Author(s):  
Chin-Hsiung Loh ◽  
Chia-Hui Chen ◽  
Ting-Yu Hsu
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Spectrum Analysis ◽  
Singular Spectrum Analysis ◽  
Threshold Level ◽  
Arch Dam ◽  
Static Deformation ◽  
Monitoring Data ◽  
Singular Spectrum

The objective of this article is to develop methods for extracting trends from long-term structural health monitoring data and try to set an early warning threshold level based on the results of analyses. The long-term monitoring data in this study is the continuous monitoring of the dam static deformation. Two different approaches were applied to extract features of the long-term structural health monitoring data of the static deformation of the Fei-Tsui Arch Dam (Taiwan). The methods include the singular spectrum analysis with auto regressive model (SSA-AR) and the nonlinear principal component analysis (NPCA) using auto-associative neural network method (AANN). The singular spectrum analysis is a novel nonparametric technique based on principles of multi-variance statistics. An AR model is optimized for each of the principal components obtained from SSA, and the multi step predicted values are recombined to make the time series. Different from SSA method the NPCA-AANN method is also used to extract the underlying features of static deformation of the dam. By using these two different methods, the residual deformation between the estimated and the recorded data was generated, through statistical analysis, the threshold level of the dam static deformation can be determined. Discussion on the two proposed methods to the static deformation monitoring data of Fei-Tsui Arch Dam (Taiwan) is discussed.

scholarly journals Long-term polar motion prediction using normal time–frequency transform

2013 ◽  
Vol 88 (2) ◽  
pp. 145-155 ◽  
Author(s):  
Xiaoqing Su ◽  
Lintao Liu ◽  
Hsu Houtse ◽  
Guocheng Wang
Keyword(s):  
Polar Motion ◽  
Motion Prediction ◽  
Time Frequency ◽  
Polar Motion Prediction

scholarly journals A high-resolution δ<sup>18</sup>O record and Mediterranean climate variability

2015 ◽  
Vol 11 (3) ◽  
pp. 509-522 ◽  
Author(s):  
C. Taricco ◽  
G. Vivaldo ◽  
S. Alessio ◽  
S. Rubinetti ◽  
S. Mancuso
Keyword(s):  
High Resolution ◽  
Spectrum Analysis ◽  
Singular Spectrum Analysis ◽  
Ionian Sea ◽  
Data Set ◽  
Singular Spectrum ◽  
Proxy Records ◽  
Long Term Trends ◽  
Temperature Proxy

Abstract. A high-resolution, well-dated foraminiferal δ18O record from a shallow-water core drilled from the Gallipoli Terrace in the Gulf of Taranto (Ionian Sea), previously measured over the last two millennia, has been extended to cover 707 BC–AD 1979. Spectral analysis of this series, performed using singular-spectrum analysis (SSA) and other classical and advanced methods, strengthens the results obtained analysing the shorter δ18O profile, detecting the same highly significant oscillations of about 600, 380, 170, 130 and 11 years, respectively explaining about 12, 7, 5, 2 and 2% of the time series total variance, plus a millennial trend (18% of the variance). The comparison with the results of multi-channel singular-spectrum analysis (MSSA) applied to a data set of 26 Northern Hemisphere (NH) temperature-proxy records shows that NH temperature anomalies share with our local record a~long-term trend and a bicentennial (170-year period) cycle. These two variability modes, previously identified as temperature-driven, are the most powerful modes in the NH temperature data set. Both the long-term trends and the bicentennial oscillations, when reconstructed locally and hemispherically, show coherent phases. Furthermore, the corresponding local and hemispheric amplitudes are comparable if changes in the precipitation–evaporation balance of the Ionian sea, presumably associated with temperature changes, are taken into account.

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