Reliable Precursor Research Articles

Earthquake Precursors: The Physics, Identification, and Application

The paper presents the author’s vision of the problem of earthquake hazards from the physical point of view. The first part is concerned with the processes of precursor’s generation. These processes are a part of the complex system of the lithosphere–atmosphere–ionosphere–magnetosphere coupling, which is characteristic of many other natural phenomena, where air ionization, atmospheric thermodynamic instability, and the Global Electric Circuit are involved in the processes of the geosphere’s interaction. The second part of the paper is concentrated on the reliable precursor’s identification. The specific features helping to identify precursors are separated into two groups: the absolute signatures such as the precursor’s locality or equatorial anomaly crests generation in conditions of absence of natural east-directed electric field and the conditional signatures due to the physical uniqueness mechanism of their generation, or necessity of the presence of additional precursors as multiple consequences of air ionization demonstrating the precursor’s synergy. The last part of the paper is devoted to the possible practical applications of the described precursors for purposes of the short-term earthquake forecast. A change in the paradigm of the earthquake forecast is proposed. The problem should be placed into the same category as weather forecasting or space weather forecasting.

Pengesanan Denyutan Pi2 Hampir Masa Nyata Berdasarkan Model Pembelajaran Mesin Terautomatik

The impact of geomagnetic substorms on space weather and various technology on the Earth urges the need to detect the phenomenon. However, the brief period of substorm occurrences makes it more difficult to directly detect them, therefore, their detection by proxy in the form of precursors need to be done. Pi2 pulsations, which is a damped irregular signal in the horizontal component of the geomagnetic field ( as a reliable precursor to substorms. The cessation of Hz), is seen index that previously was the main detection indicator of Pi2 pulsations motivates this study to introduce a new detection method by implementing machine learning. In this study, several features were extracted from geomagnetic field data based on several statistical parameters, impulsive and signal metrics to be used in the development of classification model. The development was performed based on the automated machine learning (AutoML) approach that determines the best algorithm and optimizes the hyperparameters automatically. AutoML tries various algorithms like ensemble, neural network, Naïve Bayes, support vector machine, k-nearest neighbour and binary decision tree that are optimized by Asynchronous Successive Halving Algorithm. An ensemble classification model was determined to be the best performing model with an accuracy of 99.15%. It was then used in the development of near-real tine detection system. The system streams the geomagnetic field data continuously and reports the Pi2 detections on an open cloud repository, The detection system is envisioned to be one of the reference sources to inquire the occurrences of Pi2 pulsations globally.

Multicolor lignin-derived carbon quantum dots: Controllable synthesis and photocatalytic applications

The cost-effective, high-performance fabrication of multicolor carbon quantum dots (CQDs) from biomass is critical to its prospective application. Lignin, with its phenylpropane structural unit and abundant functional groups, is a reliable precursor for the formation of high-quality CQDs. Here, CQDs from renewable lignin were successfully prepared via a two-step method, and controllable preparation of CQDs to emit blue, green, yellow, and red fluorescence was achieved by adjusting the N-containing acid dopant. The investigated fluorescence mechanism revealed that the energy bandgap of the lignin-derived CQDs decreased and the emission wavelength redshifted as the graphitization degree and number of C=O surface groups increased. The light absorption region of the Bi7O9I3 photocatalysts modified with blue CQDs to red CQDs gradually broadened in the redshifted direction. In particular, compared with pure Bi7O9I3 (70.9%), the red CQDs-modified Bi7O9I3 (RCQD/BOI) can remove 94.7% of antibiotics within 60 min of light irradiation. The superior photocatalytic activity of RCQD/BOI is attributed to the established internal electric field that accelerates charge transfer and effectively separates the photogenerated e+-h+ inside Bi7O9I3. Furthermore, through radical capture, electron paramagnetic resonance (EPR) experiments validated the photocatalytic mechanism of RCQD/BOI and revealed that h+, O2− and OH are key reactants in the photocatalytic degradation process. This promising and sustainable approach for the synthesis of multicolor lignin-derived CQDs opens the avenue of high-value utilization of biomass resources, green production of CQDs nanomaterials, and efficient development of CQDs-based photocatalysts for wastewater treatment.

Spring water anomalies before two consecutive earthquakes (Mw 7.7 and Mw 7.6) in Kahramanmaraş (Türkiye) on 6 February 2023

Abstract. Understanding earthquake phenomena is always challenging. The search for reliable precursors of earthquakes is important but requires systematic and long-time monitoring employing multi-disciplinary techniques. In search of possible precursors, we obtained commercially bottled spring waters dated before and after the earthquakes of 6 February 2023. Hydrogeochemical precursors have been detected in commercially bottled natural spring waters (Ayran Spring and Bahçepınar Spring), which are at a distance of about 100 and 175 km from the epicenters of the Mw 7.7 and Mw 7.6 Kahramanmaraş (Türkiye) earthquakes of 6 February 2023, respectively. The available water samples cover the period from March 2022 to March 2023. The pre-earthquake anomaly is characterized by an increase in electrical conductivity and major ions (Ca2+, Mg2+, K+, Na+, Cl−, and SO42-) compared to the background for Ayran Spring water samples. The pre-earthquake anomaly lasted for at least 6 months. The anomaly in major ions sharply declined and the ion content approached the background values about 2 weeks after the earthquakes. Although only 6.5 km away from the Ayran Spring, the bottled water samples of the Bahçepınar Spring did not show any anomalies in electrical conductivity; therefore, the samples were not analyzed for ion content. Bahçepınar water is collected from shallow boreholes dug into alluvial deposits, which we believe are decoupled from the basement rocks, and this may be the reason for the lack of abnormal water chemistry prior to the earthquakes. This attests to the fact that sampling locations are very important in the detection of possible earthquake precursors. Results of the Ayran spring water samples indicate that spring water chemical anomalies of discrete samples may provide valuable information on pre-earthquake crustal deformation. Monitoring of spring waters, along with other monitoring techniques in a multidisciplinary network, and for a sufficiently long time, could potentially enable obtaining reliable proxy indicators of pre-earthquake crustal deformation.

Investigating ultra-low frequency emissions and total electron content anomalies as earthquake precursors in Sumatra (2019–2020)

Ultra-low frequency (ULF) emissions and total electron content (TEC) anomalies are potential earthquake precursors for short-term earthquake prediction. This study comprehensively examines ULF emissions and TEC anomalies associated with the Sumatra earthquakes spanning 2019–2020. Precursor ULF emissions are identified through the polarization power ratio calculations involving Z-component and H-component geomagnetic data, meticulously recorded by the Magnetik Acquisition Data System (MAGDAS). Employing the Single Station Function Transfer technique, ULF anomalies directed toward the epicenter of earthquakes are recognized as reliable precursors. Among the 29 earthquakes scrutinized, 25 were heralded by ULF emissions acting as precursors. Among these, 15 instances solely exhibited ULF emissions, unaccompanied by TEC anomalies, while the remaining ten were linked to TEC anomalies. The investigation of TEC anomalies employs advanced autocorrelation techniques rooted in the analysis of correlation coefficient deviations. TEC anomalies are meticulously acquired from the observations of the Sumatran GPS Array (SuGAr) stations. Furthermore, this study illuminates a positive correlation (R = 0.65) between the lead time of ULF emissions and TEC anomalies. Moreover, the frequency of ULF emissions and TEC anomalies also showcases a direct relationship with earthquake magnitude. Heightened frequencies of ULF emissions and TEC anomalies as earthquake precursors correspond to more significant magnitudes in ensuing earthquakes. The outcomes of this research significantly augment the understanding of employing ULF emissions and TEC anomalies as effective earthquake precursors in the context of Sumatra.

Are eruptions reliable precursors to marine volcano collapses?

Volcanoes are sources of numerous threats including lava flows, pyroclastic flows, ash dispersal and landslides or sector collapses. In addition to these commonly known volcanic hazards, volcano-induced tsunamis can occur in the marine environment, introducing a major hazard that can affect populations located far away from the volcanoes. Existing tsunami warning systems generally do not account for volcano-generated tsunamis, due to the multiple source mechanisms that can cause such tsunamis, a limited understanding of precursory signals for these events, and the need for local detection rather than remote sensing. Among these source mechanisms of volcanic tsunamis, sector and lateral collapses are at the high risk-low frequency extreme of risk matrices. Marine volcanoes grow in specific environments, with factors like marine clays, constant full saturation, sediment transport and remobilization, interaction with ocean dynamics, and sea level changes that may impact edifice stability in distinct ways. The majority of historically documented marine volcano collapses occurred at erupting volcanoes, suggesting that eruptions could serve as a remotely detectable warning signal for collapses. However, careful examination of temporal sequences of these examples reveals that collapses do not always follow eruptions. Consequently, there is a need for identifying other, more robust precursors to volcano collapse, in particular in the marine environment, where the consequences of collapses may be widespread.

Terrestrial Snowmelt as a Precursor to Landfast Sea Ice Break-up in Hudson Bay and James Bay

Numerous studies have been conducted to enhance our understanding of how climate change impacts landfast ice and its break-up in spring or summer. Yet, predictions of break-up timing have proven elusive illusive, and dependent on multiple environmental drivers. In this study, we investigate whether/to what extent snow melt on land adjacent to the coast can serve as a precursor to landfast ice break-up. For the study, we used MODIS snowmelt timing products to explore the pattern of snowmelt across the study area. This was compared against landfast ice break-up dates generated mainly from CIS ice-chart, across the Hudson Bay and James Bay coast. Snowmelt timings recorded across the study area followed the same latitudinal gradient as the landfast ice break-up dates, with almost a 50-day difference between the south and the north snowmelt and ice break-up timings. The data shows that the timing of landfast ice break-up across the Hudson Bay and James Bay region showed significantly stronger correlations with the timing of terrestrial snowmelt, as compared to air temperature thresholds, with an average 17-day gap observed between snowmelt to landfast ice break-up. Based on the observations, we believe snowmelt can be a reliable precursor to landfast ice break-up.

Infrared radiation response mechanism of sandstone during loading and fracture process

Rock damage and fracture are the fundamental causes of coal mine dynamic disasters such as coal and gas outbursts, rock bursts, and mine water inrush. It is also one of the basic and common scientific problems in the field of rock engineering. Therefore, the reliable precursor information of rock damage and fracture process can be determined for the effective monitoring of the early warning of coal mine dynamic disaster, and early warning of surrounding rock fracture and seepage (water inrush) in mines. In this regard, the researcher failed to describe the mechanism of infrared radiation characteristics for the determination of rock failure precursors quantitatively. Further, the qualitative analysis of the infrared radiation mechanism restricts the use of infrared radiation to characterize the internal damage evolution and permeability characteristics of rocks. Therefore, in this paper, the equivalent plastic strain difference of sandstone is defined based on the plastic strain energy and deformation work conversion equation. The frictional heat effect of loaded sandstone is clarified. According to the Euclidean distance between the plastic zone location and the crack tip, the temperature source density function of the crack plastic zone is characterized. Based on the Fourier law of heat conduction, the thermal effect of crack propagation is deduced and analyzed, and the mathematical model of the infrared radiation response mechanism in the process of sandstone loading and fracture is established. Based on this model, the heat conduction range of sandstone fracture under biaxial loading is determined through the secondary development of finite element software, and the average infrared radiation temperature in the local high-temperature region of loaded sandstone is predicted. The findings of this research can provide a theoretical and experimental foundation for detecting rock failure for the safe and efficient execution of underground engineering projects e.g. mines, tunnels, etc.

Infrared Precursor Experiment to Predict Water Inrushes in Underground Spaces Using a Multiparameter Normalization

Rock failure is the root cause of geological disasters such as slope failure, civil tunnel collapse, and water inrush in roadways and mines. Accurate and effective monitoring of the loaded rock failure process can provide reliable precursor information for water inrushes in underground engineering structures such as in mines, civil tunnels, and subways. The water inrush may affect the safe and efficient execution of these engineering structures. Therefore, it is essential to predict the water inrush effectively. In this paper, the water inrush process of the roadway was simulated by laboratory experiments. The multiparameters such as strain energy field and infrared radiation temperature field were normalized based on the normalization algorithm of linear function transformation. On the basis of analyzing the variation characteristics of the original parameters, the evolution characteristics after the parameters normalization algorithm were studied, and the precursor of roadway water inrush was predicted comprehensively. The results show that the dissipation energy ratio, the infrared radiation variation coefficient (IRVC), the average infrared radiation temperature (AIRT), and the variance of successful minor infrared image temperature (VSMIT) are all suitable for the prediction of roadway water inrushes in the developing face of an excavation. The intermediate mutation of the IRVC can be used as an early precursor of roadway water inrush in the face of an excavation that is being developed. The inflection of the dissipation energy ratio from a declining amount to a level value and the mutation of VSMIT during rock failure can be used as the middle precursor of roadway water inrush. The mutation of AIRT and VSMIT after rock failure can be used as the precursor of roadway imminent water inrush. Combining with the early precursor and middle precursor of roadway water inrush, the graded warning of “early precursor–middle precursor–final precursor” of roadway water inrush can be obtained. The research results provide a theoretical basis for water inrush monitoring and early warning in the sustainable development of mine, tunnel, shaft, and foundation pit excavations.

Progressive Failure Characteristics and Failure Symptoms of Straight-Walled Arched Sandstone Tunnels

In order to investigate the development process of crack formation in shallow-buried sandstone tunnel, biaxial compression tests were conducted on a similar model of the real straight-walled arched sandstone tunnel. The results indicate that the initial crack appeared at the arch line on both sides of the tunnel and propagated downwards, eventually leading to spalling of the rock mass on the surface of the tunnel, forming a V-shaped groove. Additionally, slab cracks were observed in the straight wall on the right side of the tunnel, which were approximately parallel to the vertical load. The failure characteristics of the tunnel were closely related to the fractal dimension of the crack geometry distribution. During the tunnel compaction and elastic deformation stage, the fractal dimension of the cracks in the tunnel surface increased linearly, while during the crack propagation stage, the fractal dimension increased gradually, with a sudden increase occurring just before the rock mass reached its peak load. The acoustic emission results revealed that AE ringing counts and amplitude were inactive during the first 4239 seconds of the test. And they only increased during the crack propagation stage. The continuous decrease of the b-value and the sudden increase of the fractal dimension of cracks can serve as a reliable precursor of tunnel failure.

Opera 2015 Project: Accurate Measurement Equipment for Earthquake Electromagnetic Emissions and Radio Seismic Indicator.

Electromagnetic emissions from earthquakes are known as precursors and are of considerable importance for the purpose of early alarms. The propagation of low-frequency waves is favored, and the range between tens of mHz to tens of Hz has been heavily investigated in the last thirty years. This work describes the self-financed Opera 2015 project that initially consisted of six monitoring stations over Italy, equipped with electric and magnetic field sensors, among others. Insight of the designed antennas and low-noise electronic amplifiers provides both characterization of performance (similar to the best commercial products) and the elements to replicate the design for our own independent studies. Measured signals through data acquisition systems were then processed for spectral analysis and are available on the Opera 2015 website. Data provided by other world-known research institutes have also been considered for comparison. The work provides examples of processing methods and results representation, identifying many exogenous noise contributions of natural or human-made origin. The study of the results occurred for some years and led us to think that reliable precursors are confined to a short area around the earthquake due to the significant attenuation and the effect of overlapping noise sources. To this aim, a magnitude-distance indicator was developed to classify the detectability of the EQ events observed during 2015 and compared this with some other known earthquake events documented in the scientific literature.

Valorization of waste biaxially‐oriented polypropylene plastic films by its co‐carbonization with almond leaves

AbstractThis study utilized the top‐lit updraft technology for the co‐carbonization of waste biaxially‐oriented polypropylene (BOPP) and almond leaves (Terminalia catappa) for the production of hybrid biochar, which was then further characterized. Biochar was also synthesized and characterized using the almond leaves alone, as it served as control for the study. The carbonization process, which ran for 100 min, gave a yield of 39.4% and 33.9% for biochar and hybrid biochar, respectively. FTIR spectra showed the presence of functional groups such as amine and carbonyl groups in the hybrid biochar. EDX results showed that the hybrid biochar contained about 57.3% carbon, in combination with other elements. SEM micrographs confirmed the presence of the plastic in the hybrid biochar. In addition, the hybrid biochar had a BET surface area of 366.8 m2/g and a pore diameter of 2.093 nm. DTA/TGA analysis showed that the presence of the plastics decreased the thermal stability of the hybrid biochar. This study supports the use of Terminalia catappa leaves as a reliable precursor for the synthesis of biochar and hybrid biochar.

Prognostic factors and a customized approach to anti-VEGF therapy for exudative age-related macular degeneration. Analysis of the risk of macular atrophy development

Age-related macular degeneration (AMD) is a chronic progressive multifactorial disease characterized by a degenerative process in the retinal pigment epithelium (RPE), Bruch's membrane and choriocapillaris of the fovea with secondary neuroepithelial (NE) damage. Intravitreal administration of drugs that inhibit VEGF is recognized as the only treatment for exudative form of AMD. Literature data is limited, and do not allow drawing conclusions about the influence of various factors (identified using OCT in the EDI mode) on the development of various subtypes of atrophy and their progression, so we decided to conduct our own study and research the possible timing and risks of developing various subtypes of macular atrophy in patients with exudative AMD receiving anti-VEGF therapy. As a result of the study, it was revealed that general macular atrophy (p=0.005) has a predominant effect on BCVA in the first year of the follow-up, while subtypes of atrophy anatomically less pronounced at one year of the follow-up manifest themselves only in the second year of the follow-up (p<0.05). Although color photography and autofluorescence are currently the only approved methods for assessing the degree of atrophy, the use of OCT may reveal reliable precursor endpoints that will facilitate and allow earlier and more accurate assessment of neurosensory tissue loss resulting from the atrophy. Thus, the development of macular atrophy is influenced by such parameters of disease activity as intraretinal fluid (p=0.006952), RPE detachment (p=0.001530) and the type of neovascularization (p=0.028860), as well as neurodenegerative changes in the form of drusen (p=0.011259) and cysts (p=0.042023). The new classification of atrophy according to the degree and localization of the lesion allows more differentiated conclusions about the effect of anti-VEGF drugs on the development of certain types of atrophy, which can be a decisive factor in determining the treatment tactics.

Sleep to Reduce Incident Depression Effectively (STRIDE): study protocol for a randomized controlled trial comparing stepped-care cognitive-behavioral therapy for insomnia versus sleep education control to prevent major depression

BackgroundPrevention of major depressive disorder (MDD) is a public health priority. Strategies targeting individuals at elevated risk for MDD may guide effective preventive care. Insomnia is a reliable precursor to depression, preceding half of all incident and relapse cases. Thus, insomnia may serve as a useful entry point for preventing MDD. Cognitive-behavioral therapy for insomnia (CBT-I) is recommended as the first-line treatment for insomnia, but widespread implementation is limited by a shortage of trained specialists. Innovative stepped-care approaches rooted in primary care can increase access to CBT-I and reduce rates of MDD.Methods/designWe propose a large-scale stepped-care clinical trial in the primary care setting that utilizes a sequential, multiple assignment, randomized trial (SMART) design to determine the effectiveness of dCBT-I alone and in combination with clinician-led CBT-I for insomnia and the prevention of MDD incidence and relapse. Specifically, our care model uses digital CBT-I (dCBT-I) as a first-line intervention to increase care access and reduce the need for specialist resources. Our proposal also adds clinician-led CBT-I for patients who do not remit with first-line intervention and need a more personalized approach from specialty care. We will evaluate negative repetitive thinking as a potential treatment mechanism by which dCBT-I and CBT-I benefit insomnia and depression outcomes.DiscussionThis project will test a highly scalable model of sleep care in a large primary care system to determine the potential for wide dissemination and implementation to address the high volume of population need for safe and effective insomnia treatment and associated prevention of depression.Trial registrationClinicalTrials.gov NCT03322774. Registered on October 26, 2017

Evaluating the prevalence of spurious correlations in pulsar timing array data sets

ABSTRACT Pulsar timing array collaborations have recently reported evidence for a noise process with a common spectrum among the millisecond pulsars in the arrays. The spectral properties of this common-noise process are consistent with expectations for an isotropic gravitational-wave background (GWB) from inspiralling supermassive black hole binaries. However, recent simulation analyses based on Parkes Pulsar Timing Array data indicate that such a detection may arise spuriously. In this paper, we use simulated pulsar timing array data sets to further test the robustness of the inference methods for spectral and spatial correlations from a GWB. Expanding on our previous results, we find strong support (Bayes factors exceeding 105) for the presence of a common-spectrum noise process in data sets where no common process is present, under a wide range of timing noise prescriptions per pulsar. We show that these results are highly sensitive to the choice of Bayesian priors on timing noise parameters, with priors that more closely match the injected distributions of timing noise parameters resulting in diminished support for a common-spectrum noise process. These results emphasize shortcomings in current methods for inferring the presence of a common-spectrum process, and imply that the detection of a common process is not a reliable precursor to detection of the GWB. Future searches for the nanohertz GWB should remain focused on detecting spatial correlations, and make use of more tailored specifications for a common-spectrum noise process.

Maximal growth rate of the ascending phase of a sunspot cycle for predicting its amplitude

Context. Forecasting the solar cycle amplitude is important for a better understanding of the solar dynamo as well as for many space weather applications. Different empirical relations of solar cycle parameters with the peak amplitude of the upcoming solar cycle have been established and used for solar cycle forecasts, as, for instance, the Waldmeier rule relating the cycle rise time with its amplitude, the polar fields at previous minimum, and so on. Recently, a separate consideration of the evolution of the two hemispheres revealed even tighter relations. Aims. We aim to introduce the maximal growth rate of sunspot activity in the ascending phase of a cycle as a new and reliable precursor of a subsequent solar cycle amplitude. We also intend to investigate whether the suggested precursor provides benefits for the prediction of the solar cycle amplitude when using the sunspot indices (sunspot numbers, sunspot areas) derived separately for the two hemispheres compared to the total sunspot indices describing the entire solar disc. Methods. We investigated the relationship between the maximal growth rate of sunspot activity in the ascending phase of a cycle and the subsequent cycle amplitude on the basis of four data sets of solar activity indices: total sunspot numbers, hemispheric sunspot numbers from the new catalogue from 1874 onwards, total sunspot areas, and hemispheric sunspot areas. Results. For all the data sets, a linear regression based on the maximal growth rate precursor shows a significant correlation. Validation of predictions for cycles 1–24 shows high correlations between the true and predicted cycle amplitudes reaching r = 0.93 for the total sunspot numbers. The lead time of the predictions varies from 2 to 49 months, with a mean value of 21 months. Furthermore, we demonstrated that the sum of maximal growth rate indicators determined separately for the north and the south hemispheric sunspot numbers provides more accurate predictions than that using total sunspot numbers. The advantages reach 27% and 11% on average in terms of rms and correlation coefficient, respectively. The superior performance is also confirmed with hemispheric sunspot areas with respect to total sunspot areas. Conclusions. The maximal growth rate of sunspot activity in the ascending phase of a solar cycle serves as a reliable precursor of the subsequent cycle amplitude. Furthermore, our findings provide a strong foundation for supporting regular monitoring, recording, and predictions of solar activity with hemispheric sunspot data, which capture the asymmetric behaviour of the solar activity and solar magnetic field and enhance solar cycle prediction methods.

Atmospheric circulation anomaly over mid- and high-latitudes and its association with severe persistent haze events in Beijing

In recent years, under strict air pollution control measures, the PM2.5 emission has been significantly reduced across China. However, the capital city of Beijing still experiences severe persistent haze events (SPHEs). This study investigated the dominant characteristics of SPHEs and their associations with synoptic atmospheric circulation anomalies in the winters of 2009–2020. The results reveal that 72.0% of winter SPHEs in Beijing occurred under an atmospheric dipole pattern involving positive geopotential height anomalies over northeastern China and negative height anomalies over West Siberia. This dipole pattern exhibited a barotropic structure, providing favorable conditions for pollutant accumulation in Beijing. Over the key region encompassing mid- to high-latitudes areas of Eurasia (50°–80°N, 30°–90°E), persistent negative height anomalies could be regarded as precursor anomalous events (PAEs) for haze occurrence in Beijing. Upon PAE initiation, a dipole pattern was formed downstream through atmospheric energy propagation, and the above positive height anomalies migrated southeastward into northeastern China, leading to an increase in PM2.5 in Beijing. After PAE onset, the PM2.5 concentration and haze frequency in Beijing increased to high levels lagging 5–8 days behind. Six days after PAE onset, the haze (severe haze) frequency reached a maximum value of 85.8% (53.6%), more than twice the winter average. Thus, PAE occurrence is a reliable precursor signal for severe haze in Beijing leading by 5–8 days, representing the crucial impact of circulation anomalies over mid- and high-latitudes. This precursor signal is also applicable to wide-range haze pollution in the whole region of North China.

The electromagnetic anomalies recorded by CSES during Yangbi and Madoi earthquakes occurred in late May 2021 in west China

This work analyzed the electromagnetic field (EM) anomalies recorded by the electric field detector (EFD) and the search coil magnetometer (SCM) onboard the China Seismo-Electromagnetic Satellite (CSES) during the two earthquakes (EQ), which are the Yangbi Ms6.4 EQ on May 21 (China Standard Time, CST) and the Madoi Ms7.4 EQ on May 22 (CST), 2021. These two EQs successively occurred in West China. The prevailing frequency band excluding the interferences from the satellite platform was chosen to extract convincible seismic-related EM disturbances. Two criteria were put forward to obtain reliable precursors using the Kp and Dst index and the variation rate of Dst per hour to eliminate the tinier spatial perturbations. We found that the seismic-related EM disturbances mainly appeared 1–10 days before the two earthquakes within the spatial extension of 1000 ​km above the epicenters.

Flare-forecasting Algorithms Based on High-gradient Polarity Inversion Lines in Active Regions

Abstract Solar flares emanate from solar active regions hosting complex and strong bipolar magnetic fluxes. Estimating the probability of an active region to flare and defining reliable precursors of intense flares are extremely challenging tasks in the space weather field. In this work, we focus on two metrics as flare precursors, the unsigned flux R, tested on Michelson Doppler Imager/Solar and Heliospheric Observatory data, one of the most used parameters for flare-forecasting applications, and a novel topological parameter D, representing the complexity of a solar active region. In greater detail, we propose an algorithm for the computation of the R value, which exploits the higher spatial resolution of Helioseismic Magnetic Imager maps. This algorithm leads to a differently computed R value, whose functionality is tested on a set of solar cycle 24 flares. Furthermore, we introduce a topological parameter based on the automatic recognition of magnetic polarity inversion lines in identified active regions and are able to evaluate its magnetic topological complexity. We use both a heuristic approach and a supervised machine-learning method to validate the effectiveness of these two descriptors to predict the occurrence of X- or M-class flares in a given solar active region during the following 24 hr period. Our feature ranking analysis shows that both parameters play a significant role in prediction performances. Moreover, the analysis demonstrates that the new topological parameter D is the only one, among 173 overall predictors, that is always present for all test subsets and is systematically ranked within the top 10 positions in all tests concerning the computation of the weights with which each predictor impacts the flare forecasting.

Algebraic quantification of an active region contribution to the solar cycle

Context. The solar dipole moment at cycle minimum is considered to be the most reliable precursor with which to determine the amplitude of the subsequent cycle. Numerical simulations of the surface flux transport (SFT) model are widely used to effectively predict the dipole moment at cycle minimum. An algebraic method was recently proposed to quickly predict the contribution of an active region (AR) to the axial dipole moment at cycle minimum instead of SFT simulations. The method assumes a bipolar magnetic region (BMR) configuration of ARs, however most ARs are asymmetric in configuration of opposite polarities, or have more complex configurations. Such ARs evolve significantly differently from those of BMR approximations. Aims. We propose a generalized algebraic method to describe the axial dipole contribution of an AR with an arbitrary configuration, and evaluate its effectiveness compared to the BMR-based method. Methods. We employ mathematical deductions to obtain the generalized method. We compare the results of the generalized method with SFT simulations of observed ARs, artificially created BMRs, and ARs with more complex configurations. We also compare the results with those from the BMR-based method. Results. The generalized method is equivalent to the SFT model, and precisely predicts the contributions of ARs to the dipole moment, but has a much higher computational efficiency. Although the BMR-based method has similar computational efficiency to the generalized method, it is only accurate for symmetric bipolar ARs. The BMR-based method systematically overestimates the dipole contributions of asymmetric bipolar ARs, and randomly miscalculates the contributions of more complex ARs. Conclusions. The generalized method provides a quick and precise quantification of the contribution of an AR to solar cycle evolution, which paves the way for application in physics-based solar cycle predictions.