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One important feature of the Greenland Ice Sheet (GrIS) change is its strong seasonal fluctuation. Taking advantage of deployed seismographic stations in Greenland, we apply cross‐component auto‐correlation of seismic ambient noise to measure in‐situ near surface relative velocity change (dv/v) in different regions of Greenland. Our results demonstrate that dv/v measurements for most stations have less than 3 months lag times in comparison to the surface mass change. These various lag times may provide us constraints for the thickness of the subglacial till layer over different regions in Greenland. Moreover, in southwest Greenland, we observe a change in the long‐term trend of dv/v for three stations, which might be consistent with the mass change rate (dM/dt) due to the “2012–2013 warm‐cold transition.” These observations suggest that seismic noise auto‐correlation technique may be used to monitor both seasonal and long‐term changes of the GrIS. Plain Language Summary The changes of the Greenland Ice Sheet (GrIS) have important implications for both scientific research and human society. Due to its large size, the change of the GrIS varies at different regions. Here, we apply a seismic monitoring technique to study the GrIS mass change by using seismographic stations deployed in Greenland. The advantage of using this technique is that we are able to monitor different locations in a relatively simple, low‐cost and in‐situ way, and obtain indicative information about the ice mass change over time. We specify the seasonal fluctuations of seismic signals and connect them with the subglacial setting at different regions in Greenland, and explore the potential of using these seismic techniques to monitor the long‐term changes of the GrIS. Key Points The seasonal variations of relative velocity change (dv/v) have <3 months lag with respect to the surface Greenland Ice Sheet (GrIS) change Larger lag times of dv/v may provide constrains for thicker subglacial till layers in the central Greenland dv/v may be used for monitoring long‐term GrIS mass change

Broadband seismometers, distinguished by their large dynamic range and wide bandwidth, have seen increasingly widespread application in earthquake early warning systems and seismological research in recent years. A quantitative investigation into the discrepancies in background noise Power Spectral Density (PSD) recorded by co-located broadband seismometers, operating with and without protective enclosures, is of substantial importance for enhancing the data quality and improving the utilization efficiency of these instruments. This paper utilizes co-located observational data from seismographic instruments (equipped with enclosures) and early warning sensors (without enclosures), installed at earthquake early warning reference stations in the Inner Mongolia region, to quantitatively investigate the noise reduction characteristics of seismometer enclosures across various frequency points, under different spatio-temporal conditions, for different components, and in diverse observational settings. The results demonstrate that subsequent to the installation of seismometer enclosures: Within the low-frequency band of 0.02–0.05 Hz, the enclosures effectively mitigate temperature fluctuations and airflow disturbances, thereby suppressing background noise. The efficacy of this suppression exhibits dependencies on both component orientation and frequency; specifically, the suppression of horizontal noise components exceeds that of the vertical component, with this noise-reducing effect becoming increasingly prominent at longer periods. The mean difference for the East-West component is 3.5 dB (median: 1 dB), while the mean difference for the vertical component is 2.2 dB. This characteristic is consistently corroborated by amplitude-squared coherence analyses performed on teleseismic event data (with the difference between the two components being approximately 0.2). Furthermore, surface-based installations benefit more significantly from such noise reduction than those situated in vaults or caves, a difference potentially attributable to the inherently greater thermal stability of subterranean environments. In the primary microseism band (0.05–0.1 Hz), the enclosures provide a discernible noise reduction effect, suggesting that the sources of primary microseisms are not solely oceanic in origin but are also modulated to some extent by the local environment proximal to the seismometer. Conversely, in the secondary microseism band (0.1–0.5 Hz) and the high-frequency band (0.5–40 Hz), the enclosures offer essentially no discernible noise reduction.

The Ross Ice Shelf (RIS) is host to a broadband, multimode seismic wavefield that is excited in response to atmospheric, oceanic and solid Earth source processes. A 34-station broadband seismographic network installed on the RIS from late 2014 through early 2017 produced continuous vibrational observations of Earth's largest ice shelf at both floating and grounded locations. We characterize temporal and spatial variations in broadband ambient wavefield power, with a focus on period bands associated with primary (10–20 s) and secondary (5–10 s) microseism signals, and an oceanic source process near the ice front (0.4–4.0 s). Horizontal component signals on floating stations overwhelmingly reflect oceanic excitations year-round due to near-complete isolation from solid Earth shear waves. The spectrum at all periods is shown to be strongly modulated by the concentration of sea ice near the ice shelf front. Contiguous and extensive sea ice damps ocean wave coupling sufficiently so that wintertime background levels can approach or surpass those of land-sited stations in Antarctica.

The availability of GPS (Global Positioning System) provides an alternative technology to seismography to detect earthquakes and detect their epicenters. However, the limited sampling rate and processing errors could potentially reduce the accuracy for estimating the required signal parameters. This paper evaluates the methods for analysing GPS derived seismic signals from the 2004 Sumatra Andaman Earthquake based on their timerepresentation, power spectrum and time-frequency representation. Between the three representations, the parameters of the earthquake signals such as P-wave and S-wave are clearly represented on the time-frequency representation.

As seismologists continue to place more stringent demands on data quality, accurately described metadata are becoming increasingly important. In order to better constrain the orientation and sensitivities of seismometers deployed in U.S. Geological Survey networks, the Albuquerque Seismological Laboratory (ASL) has recently begun identifying true north with a fiber optic gyroscope (FOG) and has developed methodologies to constrain mid-band, vertical component sensitivity levels to less than 1% in a controlled environment. However, questions remain regarding the accuracy of this new alignment technique as well as if instrument sensitivities and background noise levels are stable when the seismometers are installed in different environmental settings. In this study, we examine the stability and repeatability of these parameters by reinstalling two high-quality broadband seismometers (Streckeisen STS-2.5 and Nanometrics T-360 Global Seismographic Network (GSN) version) at different locations around the ASL and comparing them to each other and a reference STS-6 seismometer that stayed stationary for the duration of the experiment. We find that even in different environmental conditions, the sensitivities of the two broadband seismometers stayed stable to within 0.1% and that orientations attained using the FOG are generally accurate to within a degree. However, one install was off by 5° due to a mistake made by the installation team. These results indicate that while technology and methodologies are now in place to calibrate and orient a seismometer to within 1°, human error both during the installation and while producing the metadata is often a limiting factor. Finally, we find that background noise levels at short periods (0.1–1 s) become noisier when the sensors are emplaced in unconsolidated materials, whereas the noise levels at long periods (30–100 s) are not sensitive to local geological structure on the vertical components.

The average relationship is established between the basic magnitude for the Kamchatka regional catalog, ML, and modern moment magnitude Mw. The latter is firmly tied to the value of the source seismic moment M0 which has a direct physical meaning. ML magnitude is not self-reliant but is obtained through the conversion of the traditional Fedotov’s S-wave energy class, KS1,2F68. Installation of the digital seismographic network in Kamchatka in 2006–2010 permitted mass estimates of M0 and Mw to be obtained from the regional data. In this paper we outline a number of techniques to estimate M0 for the Kamchatka earthquakes using the waveforms of regional stations, and then compare the obtained Mw estimates with each other and with ML, based on several hundred earthquakes that took place in 2010–2014. On the average, for Mw = 3.0–6.0, Mw = ML–0.40; this relationship allows obtaining Mw estimates (proxy-Mw) for a large part of the regional earthquake catalog with ML = 3.4–6.4 (Mw = 3.0–6.0).

The South China Sea Tsunami Advisory Center (SCSTAC) established by China, under the aegis of UNESCO's Intergovernmental Oceanographic Commission (UNESCO/IOC), had inaugurated commencing its full operation on November 5, 2019. This center is operating 24 × 7 h and round-the-clock shift to monitor tsunami hazard that pose a serious threat to countries which bordering the South China Sea (SCS) region. Prior to the official operation, SCSTAC had taken action for the last 10 years in upgrading their technology capability which are real-time earthquake monitoring and the processing system that is crucial to be able providing the international standard of tsunami warning services in the SCS and its adjacent areas. This paper briefly reviewed on the initiation steps and its developments of the South China Sea region Tsunami Warning and Mitigation Systems, tectonic setting as well as the characteristics of historical earthquakes and tsunamis in the region. In addition, we highlighted the structure and basic functions of the earthquake monitoring and processing system, earthquake location, source mechanism solution and finite fault model inversion using the real-time seismic waveform data from regional and global seismographic networks that will result in the rapid source parameters estimation for a larger earthquake in tsunami warning. Numerous simulations and hands-on events have shown that the preliminary earthquake parameters could be determined less than 8 min after earthquake. The W phase method is used and be able to produce rapid and reliable estimation of the moment magnitude and source mechanism for larger events within 10–15 min from earthquake origin time. A finite fault model can be acquired just after the earthquake event via computing teleseismic body-wave inversion program. The earthquake monitoring and processing system provide accurate and reliable information in contributing to tsunami warning services, thus promoting the development of tsunami warning technologies, which enhancing the tsunami warning capability and tsunami emergency responses. These high-end technology can be used in facilitating others such as marine disaster prevention, mitigation and its risk reduction.

Despite significant advances in the understanding of earthquake generation processes and derivation of underlying physical laws, controversy remains regarding the constitutive law for earthquake ruptures and how it should be formulated. Laboratory experiments are necessary to obtain high-resolution measurements that allow the physical nature of shear rupture processes to be deduced, and to resolve the controversy. This important book provides a deeper understanding of earthquake processes from nucleation to their dynamic propagation. Its key focus is a deductive approach based on laboratory-derived physical laws and formulae, such as a unifying constitutive law, a constitutive scaling law, and a physical model of shear rupture nucleation. Topics covered include: the fundamentals of rock failure physics, earthquake generation processes, physical scale dependence, and large-earthquake generation cycles. Designed for researchers and professionals in earthquake seismology, rock failure physics, geology and earthquake engineering, it is also a valuable reference for graduate students.

Nonclinical measurements of a seismocardiogram (SCG) can diagnose cardiovascular disease (CVD) at an early stage, when a critical condition has not been reached, and prevents unplanned hospitalization. However, researchers are restricted when it comes to investigating the benefits of SCG signals for moving patients, because the public database does not contain such SCG signals. The analysis of a mathematical model of the seismocardiogram allows the simulation of the heart with cardiovascular disease. Additionally, the developed mathematical model of SCG does not totally replace the real cardio mechanical vibration of the heart. As a result, a seismocardiogram signal of 60 beats per min (bpm) was generated based on the main values of the main artefacts, their duration and acceleration. The resulting signal was processed by finite impulse response (FIR), infinitive impulse response (IRR), and four adaptive filters to obtain optimal signal processing settings. Meanwhile, the optimal filter settings were used to manage the real SCG signals of slowly moving or resting. Therefore, it is possible to validate measured SCG signals and perform advanced scientific research of seismocardiogram. Furthermore, the proposed mathematical model could enable electronic systems to measure the seismocardiogram with more accurate and reliable signal processing, allowing the extraction of more useful artefacts from the SCG signal during any activity.

In technical systems, static pressure and pressure changes are usually measured with piezoelectric materials or solid membranes. In this paper, we suggest a new biomimetic principle based on thin air layers that can be used to measure underwater pressure changes. Submerged backswimmers ( Notonecta sp. ) are well known for their ability to retain air layers on the surface of their forewings (hemelytra). While analyzing the hemelytra of Notonecta , we found that the air layer on the hemelytra, in combination with various types of mechanosensitive hairs (clubs and pins), most likely serve a sensory function. We suggest that this predatory aquatic insect can detect pressure changes and water movements by sensing volume changes of the air layer under water. In the present study, we used a variety of microscopy techniques to investigate the fine structure of the hemelytra. Furthermore, we provide a biomimetic proof of principle to validate our hypothesis. The suggested sensory principle has never been documented before and is not only of interest for sensory biologists but can also be used for the development of highly sensitive underwater acoustic or seismographic sensory systems.