Geomagnetic variation on decadal time scales: What can we learn from Empirical Mode Decomposition?

Jackson, Luke; Mound, J. E.

doi:10.1029/2010gl043455

Cited by 42 publications

(21 citation statements)

References 22 publications

(32 reference statements)

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“…In this study, we generally call this new and evolving technique "the EEMD method" which includes the original EMD algorithm and the Hilbert-Huang Transform (HHT). The application of this analysis has been widely demonstrated in the recent peer-reviewed literature both in science and engineering communities, and it has been verified very effective in spectrum analysis and noise filtering (Gloerson and Huang, 2003;Flandrin et al, 2004;Peel and McMahon, 2006;Battista et al, 2007;Jeng et al, 2007;Huang and Wu, 2008;Feldman, 2009;Tsolis and Xenos, 2009;Jackson and Mound, 2010;Lee and Ouarda, 2010;Lin and Jeng, 2010). Some contributions of the EMD technique have been made on the seismic data processing; however, due to the high attenuation nature of the reflection data, it still has room for more elaborate studies.…”

Section: Methodsmentioning

confidence: 99%

A nonlinear method of removing harmonic noise in geophysical data

Jeng

Chen

2011

Nonlin. Processes Geophys.

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Abstract.A nonlinear, adaptive method to remove the harmonic noise that commonly resides in geophysical data is proposed in this study. This filtering method is based on the ensemble empirical mode decomposition algorithm in conjunction with the logarithmic transform. We present a synthetic model study to investigate the capability of signal reconstruction from the decomposed data, and compare the results with those derived from other 2-D adaptive filters. Applications to the real seismic data acquired by using an ocean bottom seismograph and to a shot gather of the ground penetrating radar demonstrate the robustness of this method. Our work proposes a concept that instead of Fourier-based approaches, the harmonic noise removal in geophysical data can be achieved effectively by using an alternative nonlinear adaptive data analysis method, which has been applied extensively in other scientific studies.

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Section: Methodsmentioning

confidence: 99%

A nonlinear method of removing harmonic noise in geophysical data

Jeng

Chen

2011

Nonlin. Processes Geophys.

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“…2 in Shen and Ding (2014)), although EMD has demonstrated its applicability in a wide range of geoscience studies over the last 15 years (e.g., Pee and McMahon, 2006;Thomas et al, 2009;Franzke, 2009;Jackson and Mound, 2010;Jeng and Chen, 2011;Lee et al, 2011;Shen and Ding, 2014;Chambers, 2015). The details of EMD and EEMD can be found in many relevant literatures (e.g., Huang et al, 1998;Huang and Wu, 2008;Wu and Huang, 2009;Shen and Ding, 2014).…”

Section: Methodsmentioning

confidence: 99%

Search for the 531-day-period wobble signal in the polar motion based on EEMD

Ding

Shen

2015

Nonlin. Processes Geophys.

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Abstract. In this study, we use a nonlinear and nonstationary time series analysis method, the ensemble empirical mode decomposition method (EEMD), to analyze the polar motion (PM) time series (EOP C04 series from 1962 to 2013) to find a 531-day-period wobble (531 dW) signal. The 531 dW signal has been found in the early PM series (1962)(1963)(1964)(1965)(1966)(1967)(1968)(1969)(1970)(1971)(1972)(1973)(1974)(1975)(1976)(1977), but cannot be found in the recent PM series (1978-2013) using conventional analysis approaches. By virtue of the demodulation feature of EEMD, the 531 dW can be confirmed to be present in PM based on the differences of the amplitudes and phases between different intrinsic mode functions. Results from three sub-series divided from the EOP C04 series show that the period of the 531 dW is subject to variations, in the range of 530.9-524 days, and its amplitude is also time-dependent (about 2-11 mas). Synthetic tests are carried out to explain why the 531 dW can only be observed in recent 30-year PM time series after using EEMD. The 531 dW is also detected in the two longest available superconducting gravimeter (SG) records, which further confirms the presence of the 531 dW. The confirmation of the 531 dW existence could be significant in establishing a more reasonable Earth rotation model and may effectively contribute to the prediction of the PM and its mechanism interpretation.

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“…EMD has been widely used also in geomagnetism, for example to characterize the decadal periodicities of the length of the day and find a relation with torsional oscillations (Roberts et al 2007;Jackson and Mound 2010;De Michelis et al 2013), to study the multi-scale nature of geomagnetic storms (De Michelis et al 2012 and to analyze their impact on electric power systems (Liu et al 2016).…”

Section: Empirical Mode Decomposition Analysis: a Brief Account And Rmentioning

confidence: 99%

Statistical analysis of geomagnetic field intensity differences between ASM and VFM instruments onboard Swarm constellation

Michelis

Tozzi

Consolini

2017

Earth Planets Space

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From the very first measurements made by the magnetometers onboard Swarm satellites launched by European Space Agency (ESA) in late 2013, it emerged a discrepancy between scalar and vector measurements. An accurate analysis of this phenomenon brought to build an empirical model of the disturbance, highly correlated with the Sun incidence angle, and to correct vector data accordingly. The empirical model adopted by ESA results in a significant decrease in the amplitude of the disturbance affecting VFM measurements so greatly improving the vector magnetic data quality. This study is focused on the characterization of the difference between magnetic field intensity measured by the absolute scalar magnetometer (ASM) and that reconstructed using the vector field magnetometer (VFM) installed on Swarm constellation. Applying empirical mode decomposition method, we find the intrinsic mode functions (IMFs) associated with ASM-VFM total intensity differences obtained with data both uncorrected and corrected for the disturbance correlated with the Sun incidence angle. Surprisingly, no differences are found in the nature of the IMFs embedded in the analyzed signals, being these IMFs characterized by the same dominant periodicities before and after correction. The effect of correction manifests in the decrease in the energy associated with some IMFs contributing to corrected data. Some IMFs identified by analyzing the ASM-VFM intensity discrepancy are characterized by the same dominant periodicities of those obtained by analyzing the temperature fluctuations of the VFM electronic unit. Thus, the disturbance correlated with the Sun incidence angle could be still present in the corrected magnetic data. Furthermore, the ASM-VFM total intensity difference and the VFM electronic unit temperature display a maximal shared information with a time delay that depends on local time. Taken together, these findings may help to relate the features of the observed VFM-ASM total intensity difference to the physical characteristics of the real disturbance thus contributing to improve the empirical model proposed for the correction of data.

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Geomagnetic variation on decadal time scales: What can we learn from Empirical Mode Decomposition?

Cited by 42 publications

References 22 publications

A nonlinear method of removing harmonic noise in geophysical data

A nonlinear method of removing harmonic noise in geophysical data

Search for the 531-day-period wobble signal in the polar motion based on EEMD

Statistical analysis of geomagnetic field intensity differences between ASM and VFM instruments onboard Swarm constellation

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