ترغب بنشر مسار تعليمي؟ اضغط هنا

Cultural noise and the night-day asymmetry of the seismic activity recorded at the Bunker-East (BKE) Vesuvian Station

248   0   0.0 ( 0 )
 نشر من قبل Nicola Scafetta
 تاريخ النشر 2018
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

Mazzarella and Scafetta (2016) showed that the seismic activity recorded at the Bunker-East (BKE) Vesuvian station from 1999 to 2014 suggests a higher nocturnal seismic activity. However, this station is located at about 50 m from the main road to the volcanos crater and since 2009 its seismograms also record a significant diurnal cultural noise due mostly to tourist tours to Mt. Vesuvius. Herein, we investigate whether the different seismic frequency between day and night times could be an artifact of the peculiar cultural noise that affects this station mostly from 9:00 am to 5:00 pm from spring to fall. This time-distributed cultural noise should evidently reduce the possibility to detect low magnitude earthquakes during those hours but not high magnitude events. Using hourly distributions referring to different magnitude thresholds from M = 0.2 to M = 2.0, the Gutenberg-Richter magnitude-frequency diagram applied to the day and night-time sub-catalogs and Montecarlo statistical modeling, we demonstrate that the day-night asymmetry persists despite an evident disruption induced by cultural noise during day-hours. In particular, for the period 1999-2017, and for earthquakes with M > 2 we found a Gutenberg-Richter exponent b = 1.66 +/- 0.07 for the night-time events and b = 2.06 +/- 0.07 for day-time events. Moreover, we repeat the analysis also for an older BKE catalog covering the period from 1992 to 2000 when cultural noise was not present. The analysis confirms a higher seismic nocturnal activity that is also characterized by a smaller Gutenberg-Richter exponent b for M > 2 earthquakes relative to the day-time activity. Thus, the found night-day seismic asymmetric behavior is likely due to a real physical feature affecting Mt. Vesuvius.



قيم البحث

اقرأ أيضاً

A qualitative understanding of the day-night asymmetry for solar neutrinos is provided. The greater night flux in nu_e is seen to be a consequence of the fact that the matter effect in the sun and that in the earth have the same sign. It is shown in the adiabatic approximation for the sun that for all values of the mixing angle theta_V between 0 and pi/2, the night flux of neutrinos is greater than the day flux. Only for small values of theta_V where the adiabatic approximation badly fails does the sign of the day-night asymmetry reverse.
268 - A. D. Supanitsky , 2007
We present a new treatment of the Earth matter effects on the neutrino oscillations that is valid for an arbitrary density profile. When applied to the the study of the day-night effect on the solar neutrino flux it renders us a simple analytical exp ression, which is more accurate than those derived by using the perturbation theory and can be extended to higher energies.
We analyze hourly seismic data measured at the Osservatorio Vesuviano Ovest (OVO, 1972-2014) and at the Bunker Est (BKE, 1999-2014) stations on the Mt. Vesuvius. The OVO record is complete for seismic events with magnitude M > 1.9. We demonstrate tha t before 1996 this record presents a daily oscillation that nearly vanishes afterwards. To determine whether a daily oscillation exists in the seismic activity of the Mt. Vesuvius, we use the higher quality BKE record that is complete for seismic events with magnitude M > 0.2. We demonstrate that BKE confirms that the seismic activity at the Mt. Vesuvius is higher during nighttime than during day-time. The amplitude of the daily oscillation is enhanced during summer and damped during winter. We speculate possible links with the cooling/warming diurnal cycle of the volcanic edifice, with external geomagnetic field and with magnetostriction that should also stress the rocks. We find that the amplitude of the seismic daily cycle changes in time and has been increasing since 2008. Finally, we propose a seismic activity index to monitor the 24-hour oscillation that could be used to complement other methodologies currently adopted to determine the seismic status of the volcano and to prevent the relative hazard.
148 - Louis De Barros 2010
129 Long Period (LP) events, divided into two families of similar events, were recorded by the 50 stations deployed on Mount Etna in the second half of June 2008. During this period lava was flowing from a lateral fracture after a summit strombolian eruption. In order to understand the mechanisms of these events, we perform moment tensor
Noise suppression is an essential step in any seismic processing workflow. A portion of this noise, particularly in land datasets, presents itself as random noise. In recent years, neural networks have been successfully used to denoise seismic data i n a supervised fashion. However, supervised learning always comes with the often unachievable requirement of having noisy-clean data pairs for training. Using blind-spot networks, we redefine the denoising task as a self-supervised procedure where the network uses the surrounding noisy samples to estimate the noise-free value of a central sample. Based on the assumption that noise is statistically independent between samples, the network struggles to predict the noise component of the sample due to its randomnicity, whilst the signal component is accurately predicted due to its spatio-temporal coherency. Illustrated on synthetic examples, the blind-spot network is shown to be an efficient denoiser of seismic data contaminated by random noise with minimal damage to the signal; therefore, providing improvements in both the image domain and down-the-line tasks, such as inversion. To conclude the study, the suggested approach is applied to field data and the results are compared with two commonly used random denoising techniques: FX-deconvolution and Curvelet transform. By demonstrating that blind-spot networks are an efficient suppressor of random noise, we believe this is just the beginning of utilising self-supervised learning in seismic applications.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا