Earthquake Early Warning(EEW)is the rapid acquisition of earthquake epicenter, magnitude, and occurrence time after a destructive earthquake has started to issue alerts to the public before the arrival of transverse waves and long-period surface waves. Magnitude estimation plays a significant role in EEW algorithm research, serving as a fundamental component for early warning, post-earthquake disaster assessment, and emergency response. Seismic monitoring methods primarily focus on technologies like High-rate Global Navigation Satellite System (HR-GNSS) and strong-motion instruments. HR-GNSS is capable of capturing high-precision ground deformation signals and offers the advantages of a non-saturation recording range, making it crucial for rapid estimation of earthquake magnitudes during major seismic events. However, due to the low GNSS sampling rate and high instrument noise, observational noise often overshadows the deformation signals obtained during low-magnitude earthquakes. Additionally, the sparse distribution of GNSS stations currently impacts the accuracy and timeliness of magnitude estimation. Strong-motion observation methods, characterized by high sampling rates, low noise, and dense station distribution, are widely applied in magnitude estimation. Prevalent methods for strong-motion magnitude estimation often rely on P-wave arrival time information for timely determination of magnitude, commonly used in earthquake early warning systems. Yet, these methods are susceptible to saturation effects, leading to underestimation of magnitudes for large earthquakes. Moment magnitude estimation methods are closely associated with rupture characteristics of the seismic source and hold clear physical significance. However, determining this magnitude necessitates knowledge of the rupture extent and slip distribution along the fault plane, which are challenging to precisely obtain at the moment of earthquake occurrence. Hence, such methods are generally employed for post-event magnitude calculations.

Addressing these challenges, this paper proposes a novel method for rapidly estimating earthquake magnitudes using Peak Ground Velocity(PGV)derived from strong motion. First, a comprehensive dataset of strong-motion acceleration records is compiled, covering nearly 20 years and including 5 596 records from 23 global seismic events with magnitudes ranging from 6.0 to 9.0. These records encompass epicentral distances from 1km to 1 000km, with source depths within 60km. A uniform processing approach is applied to standardize the records in terms of time domain orientation, measurement units(converted to cm/s²), and file formats. Data from each station is categorized into three directions: East-West(EW), North-South(NS), and Vertical(UD). Subsequently, the data is converted into the Seismic Analysis Code(SAC)file format, which is specialized for digital seismic waveform data exchange. Ensuring accurate PGV measurements from strong-motion data involves meticulous data preprocessing. This includes removing the mean acceleration from the first 5 seconds before the seismic event for simple bias correction, followed by baseline correction using a high-pass filter with a cutoff frequency of 0.02Hz. The preprocessed strong-motion acceleration records are then integrated to obtain velocity, enabling the measurement of PGV. A robust PGV-based magnitude estimation model, suitable for rapid earthquake magnitude estimation, is constructed using the least-squares regression method.

Furthermore, the constructed PGV-based magnitude estimation model undergoes comprehensive experimental analysis. Initially, the residuals between observed PGV values from 5596 strong-motion records and PGV values predicted by the regression model are computed to evaluate the precision of the constructed PGV-based magnitude estimation model. The model is validated using four earthquake events not included in its construction: the 2021 Damasi M_W6.3 earthquake, the 2012 Nicoya M_W7.6 earthquake, the 2008 Wenchuan M_W7.9 earthquake, and the 2014 Iquique M_W8.2 earthquake. This validation process assesses the reliability of the constructed magnitude estimation model. Finally, the paper conducts a study on rapid magnitude estimation to evaluate the timeliness and accuracy of the PGV-based magnitude estimation model within this context.

The experimental results indicate that the predicted values of strong-motion PGV are largely consistent with the observed values for 23 seismic events, with a root mean square error of residuals measuring 0.296. For the four seismic events that were not included in the modeling process, the estimated magnitudes based on strong-motion PGV correspond closely to the moment magnitudes reported by the United States Geological Survey(USGS). The absolute deviations for these events are 0.15, 0.14, 0.05, and 0.13 magnitude units, with an average absolute deviation of 0.12 magnitude units. In the investigation of rapid magnitude estimation, the following outcomes were observed: For the Damasi M_W6.3 earthquake, an initial magnitude of 5.03 was calculated at 13 seconds, approaching the theoretical magnitude at 63 seconds, and reaching a convergent magnitude of 6.09 at 76 seconds. Regarding the Nicoya M_W7.6 earthquake, a preliminary magnitude of 4.57 was computed within 6 seconds, approximating the theoretical magnitude at 30 seconds, and converging to 7.46 at 50 seconds. In the case of the Wenchuan M_W7.9 earthquake, a preliminary magnitude of 4.06 was determined within 19 seconds. At 50 seconds, the calculated magnitude approached the theoretical value, and it converged to 7.81 at 84 seconds. For the Iquique M_W8.2 earthquake, an initial magnitude of 6.45 was estimated within 2 seconds, nearing the theoretical magnitude at 55 seconds, and achieving a convergent magnitude of 8.04 at 70 seconds. The convergence time for rapid magnitude estimation for all four events was consistently under 90 seconds.

This experimental findings underscore the applicability of the constructed PGV-based magnitude estimation model for rapid earthquake magnitude estimation. The model's ability to counter saturation effects and prevent magnitude underestimation reinforces its robustness and offers substantial technical support for earthquake early warning systems and post-earthquake emergency response strategies.

According to the Unified Earthquake Catalogue of China Earthquake Networks, using the seismic phase data compiled by the Seismic Data Center, the observations of 101 fixed and mobile seismic stations in the Yunnan region and its surrounding seismic network from May 18 to 28, 2021, we conducted precise positioning research on the foreshock-mainshock-aftershock sequence of the Yangbi earthquake using the double-difference positioning method, and obtained the precise locations of 2 144 earthquakes. It is found that the distribution of the main aftershocks and the long axis orientation of the intensity isoseismal are not consistent with the image position of the Weixi-Qiaohou Fault, and the strike intersects with a small angle. The seismogenic fault of this earthquake may be a secondary fault of the Weixi-Qiaohou Fault. On the basis of the precision positioning results, the Bayesian Bootstrap Optimization(BABO)algorithm is used to perform a moment tensor inversion on the M6.4 earthquake and the M3.6 and above earthquake sequences in Yangbi, Yunnan from May 18 to 28, 2021. The results show that the sequence of Yangbi earthquake in Yunnan has obvious segmentation. The M6.4 Yangbi main shock is of right-handed strike-slip type with a small amount of normal dip-slip component, and the centroid depth is 5.9km. Most aftershocks have the same focal mechanism as the main shock, mainly right-handed strike-slip, except for the earthquakes in the west branch of the southeast section of the aftershock area, where the source property is obviously different, showing a normal strike-slip motion. The centroid depth of the entire earthquake sequence is 3.5~8.2km. The inversion results show that the principal compressive stress field of the earthquake area is in the near NS direction and the strike-slip dislocation is associated with a slight normal dip-slip component.

The spatial distribution of earthquakes shows that this earthquake sequence gradually developed from NW to SE, and the seismic density gradually dispersed from NW to SE. Therefore, it can be considered that the stress was mainly concentrated in the NW direction before the earthquake, and then gradually spread to the SE. Therefore, the main power source of this earthquake may be the southeastward extrusion of the Sichuan-Yunnan block. The rupture process and rupture pattern of this earthquake represents the “relaxation” process of the Sichuan-Yunnan rhombic block after being extruded.

The southern part of the Sichuan-Yunnan block is the material diffusion zone resulting from the eastward extrusion of Qinghai-Tibet Plateau. In this area, the subduction and westward retreat of the Indian plate led to the absence of lateral restraint on the Sichuan-Yunnan block, which may be the main reason causing the earthquake sequences in this area changing from convergence to dispersion, from strike-slip to normal fault type.

The Sichuan-Yunnan block is one of the most insensive areas where the Qinghai-Tibet Plateau squeezes out and escapes southeastward. Regarding the regional dynamic mode, we believe that under the background of continuous eastward extrusion of the material in the eastern part of the Qinghai-Tibet Plateau, and due to the lack of rigid blocks in the horizontal direction, it is more prone to velocity migration in the horizontal direction when the Sichuan-Yunnan block extrudes in the direction of SE and crosses the eastern structural junction and Longmen Mountains. The velocity migration in the study area may be caused by plate subduction or mantle underplating. The study of the lithospheric structure in the Sichuan-Yunnan area found that the crustal thickness of the sub-blocks in central Yunnan gradually thinned from north to south, and the lithospheric thickness in the area west of the Honghe fault zone shows a gradual thinning trend from east to west. It may be related to the intrusion of hot mantle material caused by the subduction and westward retreat of the Indian plate. Tomography results show that in the Ailaoshan-Honghe fault zone, the Yangtze block subducted downwards accompanied by mantle disturbance and asthenosphere upwelling, which led to magmatic activity and intrusion in the Cenozoic. Both of the above two effects can make the western boundary of the Sichuan-Yunnan block have a tensile stress background, and make the focal mechanism of major earthquakes on the nearby tectonic belt possible to appear normal. In summary, the dynamic source of earthquakes in the study area mainly comes from the escape of the Sichuan-Yunnan block to the southeast, and plate subduction or mantle underplating is possibly the deep-seated dynamic background for the lateral velocity migration of the study area.

InSAR coseismic deformation fields caused by the Maduo M_W7.3 earthquake occurring on May 22, 2021 were generated using the C-band Sentinel-1A/B SAR images with D-InSAR technology. The spatial characteristics, magnitude of coseismic deformation and segmentation of the seismogenic fault were analyzed. The surface rupture trace was depicted clearly by InSAR observations. In addition, the coseismic slip distribution inversion was carried out constrained by both ascending and descending InSAR deformation fields and relocated aftershocks to understand the characteristics of deep fault slip and geometry of the seismogenic fault. The regional stress disturbance was analyzed based on coseismic Coulomb stress change. The results show that the Maduo M_W7.3 earthquake occurred on a secondary fault within the Bayan Har block which is almost parallel to the main fault trace of the Kunlun Fault. According to field investigation, geological data and InSAR surface rupture traces, the seismogenic fault is confirmed to be the Kunlunshankou-Jiangcuo Fault. The rupture length of seismogenic fault is estimated to be~210km. The NWW direction is followed by the overall displacement field, which indicates a left-lateral strike-slip movement of seismogenic fault. The maximum displacement is about 0.9m in LOS direction observed by both ascending and descending InSAR data. The inversion result denotes that the strike of the seismogenic fault is 276°and the dip angle is 80°. The maximum slip is about 6m and the average rake is 4°. The predicted moment magnitude is M_W7.45, which is overall consistent with the result of GCMT. An obvious slip-concentrated area is located at the depth of 0~10km. The coseismic Coulomb stress change with the East Kunlun Fault as the receiver fault shows that the Maduo earthquake produced obvious stress increase near the eastern segment of the East Kunlun Fault. Thus the seismic risk increases based on the high interseismic strain rate along this segment, which should receive more attention. In addition, the coseismic Coulomb stress change with the Maduo-Gande Fault as the receiving fault indicates that the Maduo earthquake produced an obvious stress drop near the western part of the Maduo-Gande Fault, which indicates that the Maduo earthquake released the Coulomb stress of the Maduo-Gande Fault, and its seismic risk may be greatly reduced. However, there is a stress loading effect in the intersection area of the Maduo-Gande Fault and the Kunlunshankou-Jiangcuo Fault. Considering that aftershocks of Maduo earthquake will release excess energy, the greater earthquake risk may be reduced.

Using data of Crustal Movement Observation Network of China(CMONC)we analyzed variations of total electron content(TEC)over southwest China during a period of low solar and geomagnetic activity in April-October 2008. During that time, six large earthquakes with magnitude M≥6.0 occurred around the southwest region of China. To determine the abnormal TEC signals, a quartile-based process is performed. At each time point we calculated the median M using the TEC values at the same local time for the preceding 15 days. In addition, we calculated the maps of differential TEC from global ionosphere maps(GIM)in the above period. Known that the decisive role in the ionosphere state is performed by space weather effects, we compared the TEC variations with time series of EUV solar radiation, Bz component of the interplanetary magnetic field (IMF), index of geomagnetic activity D_st and planetary index K_p, respectively. It is found that the observed anomalies in the regional TEC are in good correlation with the variations of above solar and geomagnetic activities. We have not detected obvious TEC disturbance before five earthquakes expect for Wenchuan earthquake. In order to additionally check the spatial occurrence of the observed anomalies, we chose a "check-region" with the same geomagnetic latitudes as the epicentral area of the six considered earthquakes, and analyzed the TEC changes. The result shows that the time series of anomalous TEC in "check-region" is similar to the epicentral area, which is dominated by space weather. Therefore, it indicates the difficulties in identifying earthquake precursors in the ionosphere TEC. The seismo-ionospheric coupling process is complex, and it is necessary to strengthen the observation of multi-parameters on the ground, in the atmosphere and ionosphere synchronously.