scholarly journals Possible Correlations between the ULF Geomagnetic Signature and Mw6.4 Coastal Earthquake, Albania, on 26 November 2019

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 233
Author(s):  
Dragoș Armand Stănică ◽  
Dumitru Stănică
Keyword(s):  
Time Series ◽  
Lead Time ◽  
Low Frequency ◽  
Random Variable ◽  
Strain Effect ◽  
Signal Identification ◽  
Variable Equation ◽  
Band Pass ◽  
Time Invariant ◽  
Local Anomalies

An earthquake of Mw6.4 hit the coastal zone of Albania on 26 November 2019, at 02:54:11 UTC. It was intensively felt at about 34 km away, in Tirana City, where damages and lives lost occurred. To emphasize a pre-seismic geomagnetic signature before the onset of this earthquake, the data collected on the interval 15 October–30 November 2019, at the Panagjurishte (PAG)-Bulgaria and Surlari (SUA)-Romania observatories were analyzed. Further on, for geomagnetic signal identification we used the polarization parameter (BPOL) which is time invariant in non-seismic conditions and it becomes unstable due to the strain effect related to the Mw6.4earthquake. Consequently, BPOL time series and its standard deviations are performed for the both sites using ultra low frequency (ULF)-fast Fourier transform (FFT) band-pass filtering. A statistical analysis, based on a standardized random variable equation, was applied to emphasize on the BPOL* (PAG) and ABS BPOL* (PAG) time series the anomalous signal’s singularity and, to differentiate the transient local anomalies due to the Mw6.4 earthquake, from the internal and external parts of the geomagnetic field, taken PAG observatory as reference. Finally, the ABS BPOL* (PAG-SUA) time series were obtained on the interval 1–30 November 2019, where a geomagnetic signature greater than 2.0, was detected on 23 November and the lead time was 3 days before the onset of the Mw6.4earthquake.

Pre-seismic geomagnetic anomalous signature related to the Mw7.0 earthquake generated in the northern coastal zone of Samos island – Greece, on October 30, 2020

2021 ◽  
Author(s):  
Dumitru Stanica ◽  
Dragos Armand Stanica
Keyword(s):  
Time Series ◽  
Coastal Zone ◽  
Geomagnetic Field ◽  
Strong Earthquake ◽  
Random Variable ◽  
Strain Effect ◽  
Signal Identification ◽  
Variable Equation ◽  
Band Pass ◽  
Local Anomalies

<p>A strong earthquake of magnitude Mw7.0 struck the northern coastal zone of Samos Island, Aegean See, Greece, on October 30, 2020, at 11:51 UTC. This earthquake was felt at a wide area including Athens (at 270km) and city of Heraklion, Crete (at 320km), causing over 120 deaths and a lot of damages on houses, buildings and infrastructures mainly in Samos Island and Izmir (Turkey). With the aim to identify an anomalous geomagnetic signature before the onset of this earthquake, we have retrospectively analyzed the data collected, on the interval September 16 - October 31, 2020, at the two geomagnetic observatories, Pedeli (PEG)-Greece and Panagjurishte (PAG)-Bulgaria, by using the polarization parameter (BPOL) and the strain effect–related to geomagnetic signal identification. Thus, for the both observation sites (PEG and PAG), the daily mean distribution of the BPOL and its standard deviation (SD) are carried out using a FFT band-pass filtering in the ULF range (0.001-0.0083Hz). Further on, a statistical analysis based on a standardized random variable equation was applied for the following two particular cases: a) to assess on the both time series BPOL*(PEG) and BPOL*(PAG) the anomalous signature related to Mw7.0 earthquake; b) to differentiate transient local anomalies associated with Mw7.0 earthquake from the internal and external parts of the geomagnetic field, taking the PAG Observatory as reference. Finally, on the BPOL*(PEG-PAG) time series, carried out on the interval 1-31 October, 2020, a very clear anomaly of maximum, greater than 1.2SD, was detected on October 27, with 3days before the onset of Mw7.0 earthquake.</p>

Possible correlation beteen the pre-seismic geomagnetic signal and the M6.4 earthquake generated in the coastal zone of Albania, on November 26, 2019

2020 ◽  
Author(s):  
Dumitru Stanica ◽  
Dragos Armand Stanica
Keyword(s):  
Coastal Zone ◽  
Random Variable ◽  
Tectonic Stress ◽  
Strain Effect ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Anomalous Signal ◽  
Variable Equation ◽  
Band Pass ◽  
Time Invariant

<p>A catastrophic earthquake of magnitude Mw6.4 generated at 10km depth hit coastal zone of Albania on November 26-th 2019, at 2h54min UTC. The earthquake was intensively felt at about 34km far, in Tirana City, where a lot of damages have occurred. Consequently, in order to identify the anomalous geomagnetic signature before the onset of this earthquake, we retrospectively analyzed the data collected on the interval October 15–November 30, 2019 at the two geomagnetic observatories: Panagjurishte (PAG)-Bulgaria and Surlari (SUA)-Romania, the last one taken as reference. The pre-seismic geomagnetic anomalous signal is postulated to be due to the electrical conductivity changes, most probably associated with the earthquake-induced tectonic stress, followed by rupture and electrochemical processes deployed along the Adria plate subduction zone. To identify a pre-seismic geomagnetic signal related to this earthquake we used: (i) polarization parameter BPOL which should be time invariant in non-seismic condition and it becomes unstable before the onset a seismic event; (ii) Strain effect-related to the anomalous geomagnetic signals identification. Thus, the daily mean distributions of the BPOL and its standard deviations (SD) are performed for the both observation site (PAG and SUA) by using the FFT band-pass filter analysis in the ULF range (0.001Hz - 0.0083Hz). Further on, a statistical analysis based on a standardized random variable equation was applied for the two particular cases: a) the assessment of the singularity for anomalous signal, related to the Mw6.4earthquake, observed on the daily mean distributions of the BPOL*(PAG) and BPOL*(SUA); b) the differentiation of the transient local anomalies associated with Mw6.4earthquake from the internal and external parts of the geomagnetic field, taking Geomagnetic Observatory (SUA) as reference, and the result is presented as daily mean distribution of the BPOL*(PAG-SUA). Finally, on the BPOL*(PAG-SUA) time series, carried out on the interval 1-30 November 2019, a very clear anomaly of maximum greater than 2.5 SD was detected on November 22, what means a lead time of 4 days before the onset of Mw6.4earthquake. In consequence, all mentioned results could offer opportunities to develop new tools for early detection of geomagnetic anomalies related to major seismic events. </p>

scholarly journals Electromagnetic contribution to the resilience improvement against the Vrancea intermediate depth earthquakes, Romania

2020 ◽  
Vol 63 (5) ◽  
Author(s):  
Dragoș Armand Stănică ◽  
Dumitru Stănică ◽  
Monica Valeca ◽  
Ștefan Iordache
Keyword(s):  
Real Time ◽  
Lead Time ◽  
Warning System ◽  
Random Variable ◽  
Anomalous Behavior ◽  
Time Intervals ◽  
Intermediate Depth ◽  
Daily Data ◽  
Variable Equation ◽  
Band Pass

In this paper we used the geomagnetic data, collected in real time on the intervals August- September and November-December, 2016, to emphasize possible relationships between the anomalous behavior of the normalized function Bzn and the both M5.7 and M5.6 earthquakes, generated at 72 km and, respectively 71 km depth, in the seismic active Vrancea zone on September 24 and December 28, 2016. Daily mean distributions of the Bzn and its standard deviation (SD) are obtained for the both time-intervals, in the ULF frequency range 0.001Hz - 0.0083Hz, by using the FFT band-pass filtering. We investigate the singularities of the pre-seismic anomalous signals related to the M5.7 and M5.6 earthquakes applying a statistical analysis based on a standardized random variable equation, and the results are presented as Bz* time series performed on the new time intervals 1-30 September and 1-31 December, 2016. Finally, two pre-seismic anomalous signals are observed: first one on September 21, with values greater than 5 SD, what means a lead time of 3 days before the onset of M5.7 earthquake; the second one, with values larger than 4 SD, which was identified on December 21 with 7 days prior to M5.6earhquake. In conclusion, as the work-station has specific programs for data processing, analyses and real time (daily) data display on the institute website, it may be used as an early warning system able to provide useful information for resilience improvement against the Vrancea intermediate depth seismicity.

scholarly journals ULF Pre-Seismic Geomagnetic Anomalous Signal Related to Mw8.1 Offshore Chiapas Earthquake, Mexico on 8 September 2017

Entropy ◽  
2019 ◽  
Vol 21 (1) ◽  
pp. 29 ◽  
Author(s):  
Dragoș Armand Stănică ◽  
Dumitru Stănică
Keyword(s):  
Low Frequency ◽  
Random Variable ◽  
Seismic Signal ◽  
Polarization Parameter ◽  
Earthquake Nucleation ◽  
Anomalous Signal ◽  
Variable Equation ◽  
Band Pass ◽  
Geomagnetic Observations ◽  
The Relationship

In the last decade, the real time ground–based geomagnetic observations realized in correlation with the Vrancea seismicity in Romania, together with supplementary studies related to some earthquakes (Mw9.0 Tohoku, Japan on 11 March 2011 and Mw8.3 Coquimbo, Chile on 16 September 2015), enlarged our knowledge about the relationship between the pre-seismic anomalous phenomena and the final stage of the earthquake nucleation. To identify possible ultra-low-frequency (ULF) geomagnetic signals prior to the onset of an Mw8.1 earthquake, we retroactively analyzed the data collected on the interval 1 August–16 September 2017 at the Geomagnetic Observatories in Teoloyucan (TEO), Mexico and Tucson (TUC) USA, with the last taken as a reference. Daily mean distributions of the polarization parameter BPOL (geomagnetic polarization parameter) and standard deviation are obtained for both observatories using a fast Fourier transform (FFT) band-pass filtering in the ULF range (0.001–0.083 Hz). Further on, we investigated the singularity of the pre-seismic signal associated with an Mw8.1 earthquake and applied a statistical analysis based on a standardized random variable equation; results are presented as BPOL* time series on the interval 1–26 September. Finally, the hourly mean distribution, obtained as difference BPOL (TUC-TEO) on the interval 7–9 September emphasizes an anomalous signal with five hours before the onset of the Mw8.1 earthquake.

scholarly journals Shift Detection in Hydrological Regimes and Pluriannual Low-Frequency Streamflow Forecasting Using the Hidden Markov Model

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 2058 ◽  
Author(s):  
Larissa Rolim ◽  
Francisco de Souza Filho
Keyword(s):  
Time Series ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Extreme Events ◽  
Hidden Markov ◽  
Low Frequency ◽  
Streamflow Forecasting ◽  
Hydrologic Time Series ◽  
Low Frequency Variability ◽  
The Impact

Improved water resource management relies on accurate analyses of the past dynamics of hydrological variables. The presence of low-frequency structures in hydrologic time series is an important feature. It can modify the probability of extreme events occurring in different time scales, which makes the risk associated with extreme events dynamic, changing from one decade to another. This article proposes a methodology capable of dynamically detecting and predicting low-frequency streamflow (16–32 years), which presented significance in the wavelet power spectrum. The Standardized Runoff Index (SRI), the Pruned Exact Linear Time (PELT) algorithm, the breaks for additive seasonal and trend (BFAST) method, and the hidden Markov model (HMM) were used to identify the shifts in low frequency. The HMM was also used to forecast the low frequency. As part of the results, the regime shifts detected by the BFAST approach are not entirely consistent with results from the other methods. A common shift occurs in the mid-1980s and can be attributed to the construction of the reservoir. Climate variability modulates the streamflow low-frequency variability, and anthropogenic activities and climate change can modify this modulation. The identification of shifts reveals the impact of low frequency in the streamflow time series, showing that the low-frequency variability conditions the flows of a given year.

scholarly journals Locally and Remotely Forced Subtropical AMOC Variability: A Matter of Time Scales

2020 ◽  
Vol 33 (12) ◽  
pp. 5155-5172
Author(s):  
Quentin Jamet ◽  
William K. Dewar ◽  
Nicolas Wienders ◽  
Bruno Deremble ◽  
Sally Close ◽  
...  
Keyword(s):  
Time Series ◽  
Time Scales ◽  
North Atlantic ◽  
Time Scale ◽  
Low Frequency ◽  
Meridional Overturning Circulation ◽  
Open Boundary ◽  
Overturning Circulation ◽  
Decadal Scale ◽  
Meridional Overturning

AbstractMechanisms driving the North Atlantic meridional overturning circulation (AMOC) variability at low frequency are of central interest for accurate climate predictions. Although the subpolar gyre region has been identified as a preferred place for generating climate time-scale signals, their southward propagation remains under consideration, complicating the interpretation of the observed time series provided by the Rapid Climate Change–Meridional Overturning Circulation and Heatflux Array–Western Boundary Time Series (RAPID–MOCHA–WBTS) program. In this study, we aim at disentangling the respective contribution of the local atmospheric forcing from signals of remote origin for the subtropical low-frequency AMOC variability. We analyze for this a set of four ensembles of a regional (20°S–55°N), eddy-resolving (1/12°) North Atlantic oceanic configuration, where surface forcing and open boundary conditions are alternatively permuted from fully varying (realistic) to yearly repeating signals. Their analysis reveals the predominance of local, atmospherically forced signal at interannual time scales (2–10 years), whereas signals imposed by the boundaries are responsible for the decadal (10–30 years) part of the spectrum. Due to this marked time-scale separation, we show that, although the intergyre region exhibits peculiarities, most of the subtropical AMOC variability can be understood as a linear superposition of these two signals. Finally, we find that the decadal-scale, boundary-forced AMOC variability has both northern and southern origins, although the former dominates over the latter, including at the site of the RAPID array (26.5°N).

Prediction of Surge Motion Response of Floating Structure Using Kalman Smoother Adaptive Filters Based Time-Domain Volterra Model

2014 ◽  
Vol 660 ◽  
pp. 799-803
Author(s):  
Edwar Yazid ◽  
M.S. Liew ◽  
Setyamartana Parman ◽  
V.J. Kurian ◽  
C.Y. Ng
Keyword(s):  
Time Series ◽  
Transfer Function ◽  
Time Domain ◽  
Adaptive Filters ◽  
Low Frequency ◽  
Volterra Model ◽  
Floating Structure ◽  
Frequency Responses ◽  
Kalman Smoother ◽  
System Output

This work presents an approachto predict the low frequency and wave frequency responses (LFR and WFR) of afloating structure using Kalman smoother adaptive filters based time domain Volterramodel. This method utilized time series of a measured wave height as systeminput and surge motion as system output and used to generate the linear andnonlinear transfer function (TFs). Based on those TFs, predictions of surgemotion in terms of LFR and WFR were carried out in certain frequency ranges ofwave heights. The applicability of the proposed method is then applied in ascaled 1:100 model of a semisubmersible prototype.

Effects of interaural time delays of noise stimuli on low-frequency cells in the cat's inferior colliculus. II. Responses to band-pass filtered noises

1987 ◽  
Vol 58 (3) ◽  
pp. 543-561 ◽  
Author(s):  
J. C. Chan ◽  
T. C. Yin ◽  
A. D. Musicant
Keyword(s):  
Inferior Colliculus ◽  
Time Delays ◽  
Discharge Rate ◽  
Low Frequency ◽  
Central Peak ◽  
Broadband Noise ◽  
Central Nucleus ◽  
Rate Curve ◽  
Median Frequency ◽  
Band Pass

1. We studied cells in the central nucleus of the inferior colliculus of the cat that were sensitive to interaural time delays (ITDs) in order to evaluate the influence of the stimulus spectrum of noise signals. Stimuli were sharply filtered low-, high-, and band-pass noise signals whose cutoff frequencies and bandwidths were systematically varied. The responses to ITDs of these noise signals were compared with responses obtained to ITDs of broadband noise and pure tones. 2. The discharge rate in response to band-pass noise as a function of ITD was usually a cyclic function with decreasing peak amplitudes at longer ITDs. The reciprocal of the mean interval between adjacent peaks indicated how rapidly the response rate varied with ITD and was termed the response frequency (RF). This RF was approximately equal to the median frequency of the stimulus spectrum filtered by the cell's sync-rate curve, which was the product of the synchronization to interaural phase and the discharge rate plotted against frequency. This suggests that the RF was determined by all the spectral components in the stimulus that fell within the frequency range in which the cell's response was synchronized. The contribution of each component was proportional to the sync-rate for that frequency. 3. The central peak of the ITD function usually fell within the physiological range of ITDs (+/- 400 microseconds). The location of this peak did not vary significantly with changes in stimulus spectrum by comparison with responses to tones of different frequency. Its shape also remained constant, except for a decrease in width when high-frequency components within the range of the sync-rate curve were added to the stimulus. A few cells responded with a minimal discharge instead of a maximal near-zero ITD, and this central minimum had similar properties as the central peak. The amplitude of the secondary peaks of the ITD function decreased as the stimulus bandwidth that overlapped the sync-rate curve broadened. 4. The sum of the ITD functions to two band-pass signals was similar to that of a broadband signal whose spectrum was composed of the sum of the band-pass spectra. 5. From these binaural responses we could make inferences about the response characteristics of the monaural inputs to binaural neurons. We then verified these predictions by studying responses of low-frequency trapezoid body fibers to band-pass noises.

Sign in / Sign up

Export Citation Format

Share Document