scholarly journals Tectonic process monitoring by variations of the geomagnetic field absolute intensity

1997 ◽  
Vol 40 (2) ◽  
Author(s):  
D. B. Avdeev ◽  
A. V. Kuvshinov ◽  
O. V. Pankratov
Keyword(s):  
Time Series ◽  
Process Monitoring ◽  
Geomagnetic Field ◽  
Reference Site ◽  
Transfer Functions ◽  
Absolute Intensity ◽  
Novel Technique ◽  
Tectonic Process ◽  
Tectonic Processes ◽  
Measured Time

We propose a novel technique for tectonic process monitoring. The technique includes: measurements of absolute intensity variations, at network sites, synchronously with measurements of horizontal geomagnetic field variations at a reference site; spectral analysis of measured time series and construction non-conventional transfer functions and interpretation of the transfer functions constructed in order to detect or/and to forecast the tectonic processes. Using numerical modelling we show the sensitivity of transfer functions obtained with respect to the temporal changes in the Earth's resistivity associated with tectonic processes. We also demonstrate that the components of the geomagnetic field are reconstructed in terms of spatial distribution of absolute intensity variations.

scholarly journals Geomagnetic Virtual Observatories: monitoring geomagnetic secular variation with the Swarm satellites

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Magnus D. Hammer ◽  
Grace A. Cox ◽  
William J. Brown ◽  
Ciarán D. Beggan ◽  
Christopher C. Finlay
Keyword(s):  
Time Series ◽  
Secular Variation ◽  
Geomagnetic Field ◽  
Time Windows ◽  
Low Earth Orbit ◽  
Data Selection ◽  
Spherical Harmonic Analysis ◽  
Core Field ◽  
The Core ◽  
Swarm Satellites

AbstractWe present geomagnetic main field and secular variation time series, at 300 equal-area distributed locations and at 490 km altitude, derived from magnetic field measurements collected by the three Swarm satellites. These Geomagnetic Virtual Observatory (GVO) series provide a convenient means to globally monitor and analyze long-term variations of the geomagnetic field from low-Earth orbit. The series are obtained by robust fits of local Cartesian potential field models to along-track and East–West sums and differences of Swarm satellite data collected within a radius of 700 km of the GVO locations during either 1-monthly or 4-monthly time windows. We describe two GVO data products: (1) ‘Observed Field’ GVO time series, where all observed sources contribute to the estimated values, without any data selection or correction, and (2) ‘Core Field’ GVO time series, where additional data selection is carried out, then de-noising schemes and epoch-by-epoch spherical harmonic analysis are applied to reduce contamination by magnetospheric and ionospheric signals. Secular variation series are provided as annual differences of the Core Field GVOs. We present examples of the resulting Swarm GVO series, assessing their quality through comparisons with ground observatories and geomagnetic field models. In benchmark comparisons with six high-quality mid-to-low latitude ground observatories we find the secular variation of the Core Field GVO field intensities, calculated using annual differences, agrees to an rms of 1.8 nT/yr and 1.2 nT/yr for the 1-monthly and 4-monthly versions, respectively. Regular sampling in space and time, and the availability of data error estimates, makes the GVO series well suited for users wishing to perform data assimilation studies of core dynamics, or to study long-period magnetospheric and ionospheric signals and their induced counterparts. The Swarm GVO time series will be regularly updated, approximately every four months, allowing ready access to the latest secular variation data from the Swarm satellites.

scholarly journals Multiscale Sample Entropy of Two-Dimensional Decaying Turbulence

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 245
Author(s):  
Ildoo Kim
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Soap Film ◽  
Sample Entropy ◽  
Series Data ◽  
Entropy Analysis ◽  
Measured Time ◽  
Energetic Analysis ◽  
Turbulence Data ◽  
Decaying Turbulence

Multiscale sample entropy analysis has been developed to quantify the complexity and the predictability of a time series, originally developed for physiological time series. In this study, the analysis was applied to the turbulence data. We measured time series data for the velocity fluctuation, in either the longitudinal or transverse direction, of turbulent soap film flows at various locations. The research was to assess the feasibility of using the entropy analysis to qualitatively characterize turbulence, without using any conventional energetic analysis of turbulence. The study showed that the application of the entropy analysis to the turbulence data is promising. From the analysis, we successfully captured two important features of the turbulent soap films. It is indicated that the turbulence is anisotropic from the directional disparity. In addition, we observed that the most unpredictable time scale increases with the downstream distance, which is an indication of the decaying turbulence.

scholarly journals Development and application of problem-oriented digital twins for magnetic observatories and variation stations

2021 ◽  
pp. 60-71
Author(s):  
Andrei Vorobev ◽  
Vyacheslav Pilipenko ◽  
Gulnara Vorobeva ◽  
Olga Khristodulo
Keyword(s):  
Time Series ◽  
Geomagnetic Field ◽  
Missing Values ◽  
Information Environment ◽  
Small Scale ◽  
Geomagnetic Variation ◽  
Digital Twin ◽  
Digital Twins ◽  
Geomagnetic Data ◽  
Magnetic Station

Introduction: Magnetic stations are one of the main tools for observing the geomagnetic field. However, gaps and anomalies in time series of geomagnetic data, which often exceed 30% of the number of recorded values, negatively affect the effectiveness of the implemented approach and complicate the application of mathematical tools which require that the information signal is continuous. Besides, the missing values ​​add extra uncertainty in computer simulation of dynamic spatial distribution of geomagnetic variations and related parameters. Purpose: To develop a methodology for improving the efficiency of technical means for observing the geomagnetic field. Method: Creation of problem-oriented digital twins of magnetic stations, and their integration into the collection and preprocessing of geomagnetic data, in order to simulate the functioning of their physical prototypes with a certain accuracy. Results: Using Kilpisjärvi magnetic station (Finland) as an example, it is shown that the use of digital twins, whose information environment is made up of geomagnetic data from adjacent stations, can provide the opportunity for reconstruction (retrospective forecast) of geomagnetic variation parameters with a mean square error in the auroral zone of up to 11.5 nT. The integration of problem-oriented digital twins of magnetic stations into the processes of collecting and registering geomagnetic data can provide automatic identification and replacement of missing and abnormal values, increasing, due to the redundancy effect, the fault tolerance of the magnetic station as a data source object. For example, the digital twin of Kilpisjärvi station recovers 99.55% of annual information, and 86.73% of it has an error not exceeding 12 nT. Discussion: Due to the spatial anisotropy of geomagnetic field parameters, the error at the digital twin output will be different in each specific case, depending on the geographic location of the magnetic station, as well as on the number of the surrounding magnetic stations and the distance to them. However, this problem can be minimized by integrating geomagnetic data from satellites into the information environment of the digital twin. Practical relevance: The proposed methodology provides the opportunity for automated diagnostics of time series of geomagnetic data for outliers and anomalies, as well as restoration of missing values and identification of small-scale disturbances.

scholarly journals Analysis of the time series of waste water quality at the inflow of the wastewater treatment plant and transfer functions

2014 ◽  
Vol 62 (1) ◽  
pp. 55-59 ◽  
Author(s):  
Ivan Nesmerak ◽  
Sarka D. Blazkova
Keyword(s):  
Time Series ◽  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Transfer Functions ◽  
Treatment Plant ◽  
Total Precipitation ◽  
Periodic Components ◽  
The Relationship ◽  
Pollution Loads ◽  
Daily Total

Abstract Time series of the daily total precipitation, daily wastewater discharges and daily concentrations and pollution loads of BOD5, COD, SS, N-NH4, Ntot and Ptot were analyzed at the inflow to the wastewater treatment plant (WWTP) for a larger city in 2004-2009 (WWTP is loaded by pollution from 435,000 equivalent inhabitants). The time series of the outflow from a WWTP was also available for 2007. The time series of daily total precipitation, daily wastewater discharges, concentrations and pollution loads at the inflow and outflow from the WWTP were standardized year by year to exclude a long-term trend, and periodic components with a period of 7 days and 365 days (and potentially also 186.5 days) were excluded from the standardized series. However, these two operations eliminated only a small part of the variance; there was a substantial reduction in the variance only for ammonium nitrogen and total nitrogen at the inflow and outflow from a WWTP. The relationship between the inflow into a WWTP and the outflow from a WWTP for the concentrations and pollution loads was described by simple transfer functions (SISO models) and more complicated transfer functions (MISO models). A simple transfer function (SISO model) was employed to describe the relationship between the daily total precipitation and the wastewater discharge.

scholarly journals Significance and Causality in Continuous Wavelet and Wavelet Coherence Spectra Applied to Hydrological Time Series

Hydrology ◽  
2020 ◽  
Vol 7 (4) ◽  
pp. 82
Author(s):  
Juan Carlos Rodríguez-Murillo ◽  
Montserrat Filella
Keyword(s):  
Time Series ◽  
Multiple Testing ◽  
Power Spectra ◽  
Wavelet Coherence ◽  
Data Series ◽  
Arma Process ◽  
Significance Level ◽  
Common Effect ◽  
Measured Time ◽  
Wavelet Spectra

Wavelet transform, wavelet spectra, and coherence are popular tools for studying fluctuations in time series in the form of a bidimensional time and scale representation. We discuss two aspects of wavelet analysis—namely the significance and stochastic/deterministic character of the wavelet spectra. Real-time series of discharge, sodium, and sulfate concentrations in the alpine Rhône River, Switzerland, are used to illustrate these issues. First, the consequences of using an arbitrary stochastic process (usually, AR (1)) instead of the best-fitted general ARMA process in the evaluation of the significance of wavelet spectra are analyzed. Using a general ARMA instead of AR (1) decreases the significance level of the differences in wavelet power spectra (WPS) of ARMA and AR (1) compared to the WPS of the time series in all cases studied and points to a possible systematic overestimation of significance in many published studies. Besides, the significance of particular patches in the spectra is affected by multiple testing. A (conservative) way to circumvent this problem, using global wavelet spectra and global coherence spectra, is evaluated. Finally, we discuss the issue of causality and investigated it in the three measured time series mentioned above. Even if the use of the best fitted ARMA pointed to no deterministic features being present in the corrected series studied (i.e., stochastic processes are dominant in the three data series), coherence spectra between variables allowed to reveal cause-effect relationships between two “coherent” variables and/or the existence of a common effect on both variables. Therefore, such type of analysis provides a useful tool to better understand data causal relationships.

Dynamical modelling of measured time series from a Q-switched CO2 laser

2003 ◽  
Vol 17 (2-3) ◽  
pp. 397-404 ◽  
Author(s):  
W Horbelt ◽  
J Timmer ◽  
M.J Bünner ◽  
R Meucci ◽  
M Ciofini
Keyword(s):  
Time Series ◽  
Co2 Laser ◽  
Measured Time ◽  
Dynamical Modelling

scholarly journals Observation of Intermittency-Induced Critical Dynamics in Geomagnetic Field Time Series Prior to the Intense Magnetic Storms of March, June, and December 2015

2018 ◽  
Vol 123 (6) ◽  
pp. 4594-4613 ◽  
Author(s):  
Georgios Balasis ◽  
Ioannis A. Daglis ◽  
Yiannis Contoyiannis ◽  
Stelios M. Potirakis ◽  
Constantinos Papadimitriou ◽  
...  
Keyword(s):  
Time Series ◽  
Geomagnetic Field ◽  
Magnetic Storms ◽  
Critical Dynamics
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