Rapid Earthquake Source Description Using Variometric-Derived GPS Displacements toward Application to the 2019 Mw 7.1 Ridgecrest Earthquake

2021 ◽  
Author(s):  
Jianfei Zang ◽  
Caijun Xu ◽  
Yangmao Wen ◽  
Xiaohang Wang ◽  
Kefeng He
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Moment Tensor ◽  
Continuous Phase ◽  
Earthquake Source ◽  
High Rate ◽  
Convergence Time ◽  
Centroid Moment Tensor ◽  
Origin Time ◽  
Broadcast Ephemeris

Abstract Using near-field high-rate Global Positioning System (GPS) displacements to invert for earthquake fault slips in real time has the potential to improve the accuracy of earthquake early warning or tsunami early warning. For such applications, real-time retrieval of high-accuracy GPS displacements is essential. Here, we report on rapid modeling of the 2019 Mw 7.1 Ridgecrest earthquake with real-time GPS displacements derived from a variometric approach with readily available broadcast ephemeris. This method calculates station variations in real time by differencing continuous phase observations and does not rely on precise orbit and clock information. The phase ambiguity is also removed, and thus the method does not suffer from a relatively long convergence time. To improve the accuracy of variometric displacements, we use a local spatial filter to decrease the influence of residual errors that cannot be removed completely by the time difference. We invert for the centroid moment tensor, static fault slips, and fault rupture process from the derived displacements. Our results show that all inverted models are available within about 65 s after the origin time of the earthquake and are comparable with models inverted by real-time precise point positioning displacements. This study highlights the great value of variometric displacements for the rapid earthquake source description with only broadcast ephemeris.

Comparison of local kinematic rupture joint inversion approaches for tsunami early warning: Examples of the 2017-2020 Mw > 6.3 East Aegean earthquakes

2021 ◽  
Author(s):  
Malte Metz ◽  
Marius Isken ◽  
Rongjiang Wang ◽  
Torsten Dahm ◽  
Haluk Özener ◽  
...  
Keyword(s):  
Early Warning ◽  
Joint Inversion ◽  
Moment Tensor ◽  
Strong Motion ◽  
Aegean Sea ◽  
High Rate ◽  
Source Inversion ◽  
Dynamic Rupture ◽  
Centroid Moment Tensor ◽  
Tsunami Early Warning

<p>The fast inversion of reliable centroid moment tensor and kinematic rupture parameters of earthquakes occurring near coastal margins is a key for the assessment of the tsunamigenic potential and early tsunami warning (TEW). In recent years, more and more multi-channel seismic and geodetic online station networks have been built-up to improve the TEW, for instance the GNSS and strong motion networks in Italy, Greece, and Turkey, additionally to the broadband seismological monitoring. Inclusion of such data for the fast kinematic source inversion can improve the resolution and robustness of its’ solutions. However, methods have to be further developed and tested to fully exploit the potential of such rich joint dataset.</p><p>In this frame, we compare and test two in-house developed, kinematic / dynamic rupture inversion methods which are based on completely different approaches. The IDS (Iterative Deconvolution and Stacking, Zhang et al., 2014) combines an iterative seismic network inversion with back projection techniques to retrieve subfault source time functions. The pseudo dynamic rupture model (Dahm et al., in review) links the rupture front propagation estimate based on the Eikonal equation with the dislocation derived from a boundary element method to model dislocation snapshots. We used the latter in both a fast rupture estimate and a fully probabilistic source inversion.</p><p>We use some Mw > 6.3 earthquakes that occurred in the coastal range of the Aegean Sea as an example for comparison: the Mw 6.3 Lesbos earthquake (12 June 2017), the Mw 6.6 Bodrum earthquake (20 July 2017), and the recent Mw 7.0 earthquake which occurred at Samos on 30 October 2020. The latter earthquake and the resulting tsunami caused fatalities and severe damage at the shorelines of Samos and around the city of Izmir, Turkey.<br>The fast estimates are based on only little data and/or prior information obtained from the regional seismicity catalogue and available active fault information. The large number of seismic (broadband, strong motion) and geodetic (high-rate GNSS) stations in local and regional distance from the earthquake with good azimuthal coverage jointly inverted with InSAR data allows for robust inversion results. These, and other solutions, are used as a reference for the comparison of our fast source estimates.<br>Preliminary results of the slip distribution and the source time function are in good agreement with modelling results from other authors.</p><p>We present our insights into the kinematics of the chosen earthquakes investigated by means of joint inversions. Finally, the accuracy of our first fast source estimates, which could be of potential use in tsunami early warning, will be discussed.</p>

Application of high-rate GPS for earthquake rapid response and modelling: a case in the 2019 Mw 7.1 Ridgecrest earthquake

2020 ◽  
Vol 222 (3) ◽  
pp. 1923-1935
Author(s):  
Jin Fang ◽  
Caijun Xu ◽  
Jianfei Zang ◽  
Yangmao Wen ◽  
Chuang Song ◽  
...  
Keyword(s):  
Real Time ◽  
Moment Tensor ◽  
Propagation Speed ◽  
Source Model ◽  
High Rate ◽  
Centroid Moment Tensor ◽  
Magnitude Scaling ◽  
Global Positioning ◽  
Slip Event ◽  
Kaikoura Earthquake

SUMMARY The 2019 Mw 7.1 Ridgecrest earthquake opens an opportunity to investigate how soon we can produce a reliable fault geometry and subsequently a robust source model based on high-rate Global Positioning System (GPS) data. In this study, we conduct peak ground displacement (PGD) magnitude scaling, real-time centroid moment tensor (CMT) calculation and rapid kinematic slip inversion. We conclude that a four-station PGD warning with a magnitude of Mw 7.03 can be issued at 24 s after initiation of the rupture. Fast CMT inversion can initially recover the correct nodal planes at 30 s. The kinematic slip model reveals that the Mw 7.1 earthquake is a predominant dextral strike-slip event with both normal and thrust components resolved. The earthquake shows a bilateral rupture with a low propagation speed of ∼2.1 km s−1 and a slip maxima of ∼4 m. The total moment is 5.18 × 1019 N m (Mw 7.11). We further suggest that a reasonable source model will be available in a simulated real-time mode within 30 s after the earthquake occurring, without using full high-rate GPS waveforms. This research highlights the significance of high-rate GPS for rapid earthquake response and modelling of kinematic rupture, which is also generalized by the hypothetical real-time GPS analysis for the 2016 Mw 7.8 Kaikoura earthquake and the 2010 Mw 7.2 El Mayor-Cucapah earthquake.

GNSS for Quasi-Real-Time Earthquake Source Determination in Eastern Tibet: A Prototype System toward Early Warning Applications

2021 ◽  
Author(s):  
Xinjian Shan ◽  
Yanchuan Li ◽  
Zhenjie Wang ◽  
Hao Yin ◽  
Xiaodong Liu ◽  
...  
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Crustal Deformation ◽  
Processing System ◽  
Earthquake Source ◽  
High Rate ◽  
Prototype System ◽  
The Tibetan Plateau ◽  
Source Determination ◽  
Eastern Tibet

Abstract Active crustal deformation of the Tibetan plateau results in destructive continental earthquakes and is therefore the focus of intense research interest. Increases in the numbers of Global Navigation Satellite System (GNSS) networks and stations deployed in Tibet are allowing for the characterization of crustal deformation during different phases of the earthquake cycle. Here, we present the status of a “seismic + high-rate GNSS” network deployed in eastern Tibet, including its data streams and data processing system, with the goal of supporting quasi-real-time earthquake source determination. Furthermore, we use this network to test a prototype earthquake early warning (EEW) system using data from the 2008 Mw 7.9 Wenchuan earthquake, the 2011 Mw 9.0 Tohoku earthquake, and 2200 synthetic earthquakes with moment magnitudes ranging from 6.5 to 7.5 on the southern Longmen Shan fault and Anninghe fault. The results show that our current methodology could respond to moderate-to-large earthquakes (magnitude 7+) within tens of seconds after the origin time, with implications for EEW applications in China.

scholarly journals Complementing regional moment magnitudes to GCMT: a perspective from the rebuilt International Seismological Centre Bulletin

2021 ◽  
Vol 13 (5) ◽  
pp. 1957-1985
Author(s):  
Domenico Di Giacomo ◽  
James Harris ◽  
Dmitry A. Storchak
Keyword(s):  
Body Wave ◽  
Moment Tensor ◽  
Specific Area ◽  
Centroid Moment Tensor ◽  
Earthquake Catalogues ◽  
Origin Time ◽  
Earthquake Parameters ◽  
Short Period ◽  
The Moment ◽  
International Seismological Centre

Abstract. Seismologists and geoscientists often need earthquake catalogues for various types of research. This input usually contains basic earthquake parameters such as location (longitude, latitude, depth, and origin time), as well as magnitude information. For the latter, the moment magnitude Mw has become the most sought after magnitude scale in the seismological community to characterize the size of an earthquake. In this contribution we provide an informative account of the Mw content for the newly rebuilt Bulletin of the International Seismological Centre (ISC, http://www.isc.ac.uk, last access: May 2021), which is regarded as the most comprehensive record of the Earth's seismicity. From this data, we extracted a list of hypocentres with Mw from a multitude of agencies reporting data to the ISC. We first summarize the main temporal and spatial features of the Mw provided by global (i.e. providing results for moderate to great earthquakes worldwide) and regional agencies (i.e. also providing results for small earthquakes in a specific area). Following this, we discuss their comparisons, by considering not only Mw but also the surface wave magnitude MS and short-period body wave magnitude mb. By using the Global Centroid Moment Tensor solutions as an authoritative global agency, we identify regional agencies that best complement it and show examples of frequency–magnitude distributions in different areas obtained both from the Global Centroid Moment Tensor alone and complemented by Mw from regional agencies. The work done by the regional agencies in terms of Mw is fundamental to improve our understanding of the seismicity of an area, and we call for the implementation of procedures to compute Mw in a systematic way in areas currently not well covered in this respect, such as vast parts of continental Asia and Africa. In addition, more studies are needed to clarify the causes of the apparent overestimation of global Mw estimations compared to regional Mw. Such difference is also observed in the comparisons of Mw with MS and mb. The results presented here are obtained from the dataset (Di Giacomo and Harris, 2020, https://doi.org/10.31905/J2W2M64S) stored at the ISC Dataset Repository (http://www.isc.ac.uk/dataset_repository/, last access: May 2021).

scholarly journals NEAR REAL-TIME DETERMINATION OF EARTHQUAKE SOURCE PARAMETERS FOR TSUNAMI EARLY WARNING FROM GEODETIC OBSERVATIONS

2016 ◽  
Vol XLI-B8 ◽  
pp. 117-120
Author(s):  
Sunanda Manneela ◽  
T. Srinivasa Kumar ◽  
Shailesh R. Nayak
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Rapid Determination ◽  
Moment Tensor ◽  
Source Parameters ◽  
Critical Role ◽  
Tsunami Source ◽  
Tsunami Early Warning ◽  
Earthquake Source Parameters

Exemplifying the tsunami source immediately after an earthquake is the most critical component of tsunami early warning, as not every earthquake generates a tsunami. After a major under sea earthquake, it is very important to determine whether or not it has actually triggered the deadly wave. The near real-time observations from near field networks such as strong motion and Global Positioning System (GPS) allows rapid determination of fault geometry. Here we present a complete processing chain of Indian Tsunami Early Warning System (ITEWS), starting from acquisition of geodetic raw data, processing, inversion and simulating the situation as it would be at warning center during any major earthquake. We determine the earthquake moment magnitude and generate the centroid moment tensor solution using a novel approach which are the key elements for tsunami early warning. Though the well established seismic monitoring network, numerical modeling and dissemination system are currently capable to provide tsunami warnings to most of the countries in and around the Indian Ocean, the study highlights the critical role of geodetic observations in determination of tsunami source for high-quality forecasting.

scholarly journals Predicting approximate seismic responses in multistory buildings from real-time earthquake source information, for earthquake early warning applications

2021 ◽  
Author(s):  
Gemma Cremen ◽  
Omar Velazquez ◽  
Benazir Orihuela ◽  
Carmine Galasso
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Source Parameters ◽  
Earthquake Source ◽  
Earthquake Early Warning ◽  
Multistory Buildings ◽  
Building Model ◽  
Beam Combination ◽  
Earthquake Source Parameters ◽  
Wide Range

AbstractRegional earthquake early warning (EEW) alerts and related risk-mitigation actions are often triggered when the expected value of a ground-motion intensity measure (IM), computed from real-time magnitude and source location estimates, exceeds a predefined critical IM threshold. However, the shaking experienced in mid- to high-rise buildings may be significantly different from that on the ground, which could lead to sub-optimal decision-making (i.e., increased occurrences of false and missed EEW alarms) with the aforementioned strategy. This study facilitates an important advancement in EEW decision-support, by developing empirical models that directly relate earthquake source parameters to resulting approximate responses in multistory buildings. The proposed models can leverage real-time earthquake information provided by a regional EEW system, to provide rapid predictions of structure-specific engineering demand parameters that can be used to more accurately determine whether or not an alert is triggered. We use a simplified continuum building model consisting of a flexural/shear beam combination and vary its parameters to capture a wide range of deformation modes in different building types. We analyse the approximate responses for the building model variations, using Italian accelerometric data and corresponding source parameter information from 54 earthquakes. The resulting empirical prediction equations are incorporated in a real-time Bayesian framework that can be used for building-specific EEW applications, such as (1) early warning of floor-shaking sensed by occupants; and (2) elevator control. Finally, we demonstrate the improvement in EEW alert accuracy that can be achieved using the proposed models.

scholarly journals Resolving dynamic ground motions with high-rate GNSS and implications for data fusion in broadband seismology and Earthquake Early Warning

2020 ◽  
Author(s):  
Roland Hohensinn ◽  
Nikolaj Dahmen ◽  
John Clinton ◽  
Alain Geiger ◽  
Markus Rothacher
Keyword(s):  
Data Fusion ◽  
Real Time ◽  
Early Warning ◽  
Ground Motions ◽  
Real Data ◽  
Satellite System ◽  
Earthquake Early Warning ◽  
High Rate ◽  
Velocity Waveform ◽  
Global Navigation Satellite

<p>In this paper we highlight the potential of geodetic high-precision and high-rate GNSS <em>(Global Navigation Satellite System)</em> sampling (1 to 100 Hz) for resolving seismic ground motions, of both the near and the far field of an earthquake. The analysis of the budget and characteristics of the error of high-rate GNSS displacement time series yields results, discussion, and conclusions on the sensitivity and waveform resolvability as well as on the derivation of a minimum detectable displacement (in the statistical sense).</p><p>Based on these analyses, we show how GNSS can contribute to optimal broadband displacement and velocity waveform products by means of data fusion by combining measurements taken from co-located sensors – e.g. accelerometers or gyroscopes – in real-time, near real-time and postprocessing mode. Concerning the inclusion of GNSS for such an analysis, we also briefly explore the ability of GNSS to record signals from different earthquake magnitudes and epicentral distances. We show that high-rate GNSS is sensitive to displacements down to the level of a few millimeters, and even below – an example also comes from the detection of very small vibrations from 100 Hz GNSS data.</p><p>We analyze measurements of synthetized signals obtained from experiments with a shake table, as well as from real data from strong earthquakes, namely the 6.5 M<sub>w</sub> event of 2016 near the city of Norcia (Italy) and the 7.0 M<sub>w</sub> Kumamoto earthquake of 2016 (Japan). Based on these data and our main findings, we finally discuss the role of GNSS in Earthquake Early Warning in terms of a fast hypocenter localization and reliable magnitude estimation.</p>

scholarly journals Vital Signs Prediction and Early Warning Score Calculation Based on Continuous Monitoring of Hospitalised Patients Using Wearable Technology

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6593
Author(s):  
Ahmed Youssef Ali Amer ◽  
Femke Wouters ◽  
Julie Vranken ◽  
Dianne de Korte-de Boer ◽  
Valérie Smit-Fun ◽  
...  
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Real Time ◽  
Early Warning ◽  
Continuous Monitoring ◽  
Time Series Prediction ◽  
Vital Signs ◽  
Wearable Technology ◽  
High Rate ◽  
Hospitalised Patients

In this prospective, interventional, international study, we investigate continuous monitoring of hospitalised patients’ vital signs using wearable technology as a basis for real-time early warning scores (EWS) estimation and vital signs time-series prediction. The collected continuous monitored vital signs are heart rate, blood pressure, respiration rate, and oxygen saturation of a heterogeneous patient population hospitalised in cardiology, postsurgical, and dialysis wards. Two aspects are elaborated in this study. The first is the high-rate (every minute) estimation of the statistical values (e.g., minimum and mean) of the vital signs components of the EWS for one-minute segments in contrast with the conventional routine of 2 to 3 times per day. The second aspect explores the use of a hybrid machine learning algorithm of kNN-LS-SVM for predicting future values of monitored vital signs. It is demonstrated that a real-time implementation of EWS in clinical practice is possible. Furthermore, we showed a promising prediction performance of vital signs compared to the most recent state of the art of a boosted approach of LSTM. The reported mean absolute percentage errors of predicting one-hour averaged heart rate are 4.1, 4.5, and 5% for the upcoming one, two, and three hours respectively for cardiology patients. The obtained results in this study show the potential of using wearable technology to continuously monitor the vital signs of hospitalised patients as the real-time estimation of EWS in addition to a reliable prediction of the future values of these vital signs is presented. Ultimately, both approaches of high-rate EWS computation and vital signs time-series prediction is promising to provide efficient cost-utility, ease of mobility and portability, streaming analytics, and early warning for vital signs deterioration.

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