Preliminary geological interpretation of long-wavelength magnetic anomalies over China and surrounding regions

Long-wavelength(>500 km)magnetic anomalies originating in the lithosphere were first found in satellite magnetic surveys.Compared to the striking magnetic anomalies around the world,the long-wavelength magnetic anomalies in China and surrounding regions are relatively weak.Specialized research on each of these anomalies has been quite inadequate;their geological origins remain unclear,in particular their connection to tectonic activity in the Chinese and surrounding regions.We focus on six magnetic high anomalies over the(1)Tarim Basin,(2)Sichuan Basin(3)Great Xing’an Range,(4)Barmer Basin,(5)Central Myanmar Basin,and(6)Sunda and Banda Arcs,and a striking magnetic low anomaly along the southern part of the Himalayan-Tibetan Plateau.We have analyzed their geological origins by reviewing related research and by detailed comparison with geological results.The tectonic backgrounds for these anomalies belong to two cases:either ancient basin basement,or subduction-collision zone.However,the geological origins of large-scale regional magnetic anomalies are always subject to dispute,mainly because of limited surface exposure of sources,later tectonic destruction,and superposition of multi-phase events.

张衡一号感应磁力仪数据闪电哨声波自动识别

张衡一号卫星感应式磁力仪(Search Coil Magnetometer,SCM)探测到了大量的低频电磁波动数据.本文探索从中自动识别闪电哨声波(Lightning Whistler,LW)的算法,相关结果对进一步研究空间天气闪电事件的时空变化规律具有重要研究意义.首先,以20 s的时间窗提取SCM原始波形数据,再对其做短时傅里叶变换(Short-Time Fourier Transform,STFT)得到时频图;接着,以LW在时频图中呈现明显的L形态特征为依据创建LW时频图像数据集,该数据集包括316个LW时频图,8000个非闪电哨声波的时频图;再对时频图像进行灰度化处理和尺度缩放处理以降低计算维度,同时增强闪电哨声波特征;通过设计模糊卷积核,对图像进行卷积计算以滤除大量阶跃边缘信息的影响;基于LW的形态特征设计L形态卷积核,对图像进行卷积处理以进一步增强图像中的L形态特征.最后,将增强后的L特征图输入支持向量机(Support Vector Machines,SVM)进行分类识别.大量数据处理实验结果表明:本文提出的闪电哨声波自动识别方案有效,其识别效果在精度、召回率、F1值(F1 score)和接受者操作特性曲线面积(Area Under Curve,AUC)指标上均达到94%以上.

张衡一号卫星记录的空间电磁波传播特征分析方法及算法实现

本研究主要利用张衡一号电磁卫星(CSES)记录的电磁场波形数据,研发了电磁波波矢量分析工具,该工具包提供电磁波形频谱变换、奇异值分解(SVD)方法以及坡印廷能流计算功能.选取了张衡一号卫星在ULF/ELF/VLF频段观测到的哨声波、准周期辐射、电离层嘶声波等典型波动事件,开展了频谱分析和波矢量分析.通过与DEMETER卫星的对比观测研究,验证了算法的正确性,并且初步探讨了这些波动的传播特征,其结果也验证了张衡一号卫星在电磁场观测方面具有良好的性能.本研究研发的波矢量分析工具包可直接运用到张衡一号卫星的常规数据处理和科学分析应用中.

The Electric Field Detector (EFD) onboard the ZH-1 satellite and firstobservational results

Previous studies have reported that, before or after occurrences of strong earthquakes, some low earth orbit satellites recorded ionospheric disturbances, including electromagnetic emissions and plasma fluctuations over the epicenter region or its conjugate point.Theoretically speaking, due to some electromagnetic coupling effect, electromagnetic emissions from the earthquake preparation zone could propagate from the lithosphere to the atmosphere, and could reach the ionosphere, even up to the inner magnetosphere. This paper introduces the electric field detector(EFD) onboard the ZhangHeng-1 satellite(ZH-1). The EFD is designed to measure electric field fluctuations within the broad frequency range of DC to 3.5 MHz, divided into 4 channels: ULF(DC–16 Hz), ELF(6 Hz–2.2 kHz), VLF(1.8 kHz–20 kHz) and HF(18 kHz–3.5 MHz). The sampling rates of the channels are 125 Hz, 5 kHz, 50 kHz and 10 MHz, respectively. The EFD includes4 spherical probes mounted on a over 4.5 m boom and an electronic box inside the satellite module. The resolution of the EFD is 1μV·m-1·Hz-1/2 at frequencies from DC to 16 Hz, and the sensitivity is 0.1 μV·m-1·Hz-1/2 at frequencies from 6 Hz to 2.2 kHz, 0.05 μV·m-1·Hz-1/2 in the band 1.8 kHz to 20 kHz, and 0.1μV·m-1·Hz-1/2 from 20 kHz to 3.5 MHz. The dynamic range from DC to 20 kHz is over 120 dB, and over96 dB from 20 kHz to 3.5 MHz. The EFD has two observation modes: survey mode and burst mode. The survey mode concentrates primarily on electric field power density values; the burst mode provides high sampling rate waveform data. The detailed configuration of the EFD onboard the ZH-1 is also introduced in this paper. During the six months' orbit test phase, the EFD recorded a number of natural electromagnetic emissions. Preliminary analysis of these data suggests that the EFD performs well onboard the ZH-1 and is meeting the requirements of the scientific objectives of ZH-1.

Ionospheric TEC and plasma anomalies possibly associated with the 14 July 2019 M_(w) 7.2 Indonesia Laiwui earthquake,from analysis of GPS and CSES data

This study presents signatures of seismo-ionospheric perturbations possibly related to the 14 July 2019 M_(w)7.2 Laiwui earthquake,detected by a cross-validation analysis of total electron content(TEC)data of the global ionospheric map(GIM)from GPS and plasma parameter data recorded by the China Seismo-Electromagnetic Satellite(CSES).After separating pre-seismic ionospheric phenomena from the ionospheric disturbances due to the magnetospheric and solar activities,we have identified three positive temporal anomalies,around the epicenter,at 1 day,3 days and 8 days before the earthquake(14 July 2019),along with a negative anomaly 6 days after the earthquake.These results agree well with the TEC spatial variations in latitude-longitude-time(LLT)maps.To confirm these anomalies further,we employed the moving mean method(MMM)to analyze ionospheric plasma parameters(electron,O^(+) and He^(+) densities)recorded by the Langmuir probe(LAP)and Plasma Analyzer Package(PAP)onboard the CSES.The analysis detected on,on Day Two,Day Four,and Day Seven before the earthquake,remarkable enhancements along the orbits around when in proximity to the epicenter.To make the investigations still more convincing,we compared the orbits on which anomalous readings were recorded to their corresponding four nearest revisiting orbits;the comparison did indeed indicate the existence of plasma parameter anomalies that appear to be associated with the Laiwui earthquake.All these results ilustrate that the unusual ionospheric perturbations detected through GPS and CSES data are possibly associated with the M_(w)7.2 Laiwui earthquake,which suggests that at least some earthquakes may be predicted by alertness to pre-seismic ionospheric anomalies over regions known to be at seismic risk.This case study also contributes additional information of value to our understanding of lithosphere-atmosphere-ionosphere coupling.

Disturbance identification of electric field data observed by the CSES-01 satellite before earthquakes

Numerous studies have confirmed that electromagnetic disturbances before earthquakes can be observed by satellites.In this study,we use the C-value method that includes the acoustic whistle signature;pre-seismic ionospheric electromagnetic disturbance signals were acquired based on the CSES-01 satellite electric field data,and the maximum value of C in the earthquake preparation zones increased continuously from 2.0 three days before the earthquake and reached a maximum weight of 3.0 on the day of the earthquake,after the earthquake,it gradually decreased and recovered to about 2.0;its the C values fluctuated between-2 and 3,it is different from the C values range-2–12 of the previous seismic case study using the DEMETER satellite,which may be related to the orbital altitude and revisit period of the satellite.Then,the C values were normalized,and the time series analysis of the obtained θ values were done,and the results showed that:In the pregnant zone,the background variation of the disturbance amplitude θ is within 2σ,and the maximum disturbance amplitude of θ starts to increase gradually from the seventh period(one period of 5 days,i.e.,35–39 days before the earthquake),it reached 2σ by the fourth preseismic cycle(20–24 days before the earthquake),and then dropped sharply to about 1.5σ in the third pre-seismic cycle(15–19days before the earthquake),after two cycles of increase,the θ over the epicenter reached a maximum of 2.1σ at the time of the earthquake(combining the time of the earthquake and the satellite flight characteristics,the epicenter period is defined as January25-January 29,2020,and this defines the study time period line),and the θ decreases to within 2 times the standard range after the earthquake;The negative value of the disturbance amplitude θ in the central region of the pregnant seismic zone during the earthquake shows the transient energy release process.Through comparison,the θ values obtained by normalization based on the C-value method takes into account the variation of the background field,and the result can better reflect the energy change of the ionospheric field before the earthquakes.

Cross-calibration on the electromagnetic field detection payloads of the China Seismo-Electromagnetic Satellite

The China Seismo-Electromagnetic Satellite(CSES)deploys three payloads to detect the electromagnetic environment in the ionosphere.The tri-axial fluxgate magnetometers(FGM),as part of the high precision magnetometer(HPM),measures the Earth magnetic vector field in a frequency range from direct current(DC)to 15 Hz.The tri-axial search coil magnetometer(SCM)detects the alternating current(AC)related magnetic field in a frequency range from several Hz to 20 k Hz,and the electric field detector(EFD)measures the spatial electric field in a broad frequency band from DC to 3.5 MHz.This work mainly crosscalibrates the consistency of these three payloads in their overlapped detection frequency range and firstly evaluates CSES’s timing system and the sampling time differences between EFD and SCM.A sampling time synchronization method for EFD and SCM waveform data is put forward.The consistency between FGM and SCM in the ultra-low-frequency(ULF)range is validated by using the magnetic torque(MT)signal as a reference.A natural quasiperiodic electromagnetic wave event verifies SCM and EFD’s consistency in extremely low-frequency and very low-frequency(ELF/VLF)bands.This cross-calibration work is helpful to upgrade the data quality of CSES and brings valuable insights to similar electromagnetic detection solutions by low earth orbit satellites.

Stability validation on the VLF waveform data of the China-Seismo-Electromagnetic Satellite

The China-Seismo-Electromagnetic Satellite(CSES),which was launched in February 2018,carries the search coil magnetometer(SCM)and the electric field detector(EFD)to realize the high-resolution electromagnetic field and wave detection in the upper ionosphere.Due to the complexity and variability of the ionospheric environment,the stability of such a high sampling rate and high-precision electromagnetic field detection systems is always an essential link in data processing and the scientific application of CSES.This work evaluates the stability of the very-low-frequency(VLF)band detection by validating the systemic sampling-time differences between SCM and EFD in the VLF burst-mode observations.The optimal waveform data preprocessing method is put forward according to the noise levels of the VLF burst-mode observation and the inherent design characteristics of EFD.The VLF waveform data of EFD is rebuilt by filling the data gaps among the sampling sub-periods,making it with a similar sample length to SCM.Then by precisely intercepting the maximum and minimum values of the burst-mode waveforms,the variation of the sampling-time difference between EFD and SCM is statistically evaluated.Results show that during the three years'operation,the sampling-time difference between EFD and SCM predominately keeps below 0.5 s,indicating good stability of EFD and SCM on orbit.Then we developed an automatic synchronization tool based on the similarity function and STA/LTA(short time average over long time average)characteristic function.This tool can effectively realize the precise synchronization between SCM and EFD in the VLF burst-mode observation.This work is helpful to upgrade the data quality of CSES and provides technical support for electromagnetic wave propagation studies.