pure and applied geophysics最新文献

{"title":"Research on the Initial Arrival Recognition and Judgment Method of Microseismic Signals Based on PELT","authors":"Xulin Wang, Minghui Lv","doi":"10.1007/s00024-024-03537-6","DOIUrl":"https://doi.org/10.1007/s00024-024-03537-6","url":null,"abstract":"<p>In microseismic monitoring, accurately identifying the arrival time of the P-wave initial arrival is crucial for the precise location and analysis of microseismic sources. However, due to the typically low energy of microseismic signals and poor signal-to-noise ratio (SNR), existing first-arrival picking algorithms struggle with the accuracy of picking results when dealing with microseismic data of low SNR, as they are greatly affected by strong background noise. To address this issue, this study proposes a new initial arrival identification method, which first employs variational mode decomposition (VMD) and the sample entropy method for denoising microseismic data with a low SNR, and then utilizes the pruned exact linear time (PELT) algorithm to determine the time of the microseismic initial arrival. Compared with the traditional short-term average and long-term average ratio (STA/LTA) algorithm and the Akaike information criterion (AIC) method, the method proposed in this paper demonstrates significant advantages in terms of picking precision and noise resistance.</p>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"12 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141721188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Meteorological Sub-Divisional Scale Comparison Between Two Indian Rain Gauge-Based Rainfall Datasets for the Southwest Monsoon Season","authors":"Satya Prakash,&nbsp;D. S. Pai,&nbsp;M. Mohapatra","doi":"10.1007/s00024-024-03540-x","DOIUrl":"10.1007/s00024-024-03540-x","url":null,"abstract":"<div><p>A monthly rainfall dataset for India at country, regional and meteorological sub-divisional scales was developed by the Indian Institute of Tropical Meteorology (IITM) based on a fixed network of 306 rain gauges. This dataset has been constructed when long period data was not available at many locations and there was not much computing power available. This data has been used worldwide for rainfall analysis over India. In this study, this rainfall dataset has been compared with a larger network of rain gauges maintained by the India Meteorological Department (IMD) for the southwest monsoon period of 1901–2010 at meteorological sub-divisional scale. Two different rain gauge networks can give rise to divergent estimates of rainfall, in general from differences in network density or location of individual rain gauges in each network, assuming measurement errors have small effect. Although mean monthly and seasonal monsoon rainfall and their interannual variability in both IITM and IMD datasets are similar, IITM dataset shows larger difference from IMD data for several meteorological sub-divisions. The long-term trends and frequency of occurrence of deficient and excess monsoon rainfall also show considerable differences between these two rainfall datasets. Data from a sparse network is not representative at meteorological sub-divisions associated with rather larger spatial variations in the southwest monsoon rainfall. For instance, IITM dataset has 11 rain gauges compared to 147 IMD rain gauges over a meteorological sub-division—South Interior Karnataka, and mean absolute difference in monthly monsoon rainfall estimates becomes about 25% when compared for rather shorter period using station data. It is also demonstrated that inclusion of additional rain gauges substantially improves the quality of IITM monthly rainfall estimates over this specific meteorological sub-division.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"181 8","pages":"2613 - 2630"},"PeriodicalIF":1.9,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141642765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Link Between Seismic and Atmospheric Parameters Using Spatio Temporal Analysis: Implications for Earthquake Forecasting","authors":"M. Senthil Kumar,&nbsp;N. Venkatanathan","doi":"10.1007/s00024-024-03533-w","DOIUrl":"10.1007/s00024-024-03533-w","url":null,"abstract":"<div><p>Although many earthquake precursors have been proposed to forecast earthquakes, even in this modern era, short-term earthquake forecasting remains challenging due to the heterogeneous nature of the earthquake’s occurrence. This study mainly focused on how the impending earthquake influences pre-earthquake scenarios using minor shocks and further confirmed by atmospheric parameters such as Outgoing Longwave Radiation (OLR). The Himalayan belt is one of the most at-risk areas during a continental-continental collision. The spatiotemporal analysis of the pre-earthquake scenario is carried out to identify the most vulnerable seismic risk zone and to forecast the probable magnitude of the earthquake. From the analysis, it is found that the accumulation of strain energy focussing near the epicenter of the impending earthquake. Furthermore, the study also revealed that abnormal changes in atmospheric parameters observed several days before an earthquake, which could serve as a precursor of seismic activity. On certain days, the anomalous OLR due to the radon gas emanation was observed at the different locations around the epicenter of the impending earthquakes. This phenomenon probably due to the transfer of accumulated strain from one side of the fault to other side of the fault through epicenter of the impending earthquake. This gives vital clue in determining the possible epicenter of the earthquake. The statistical analysis of minor shocks associated with significant earthquakes made it possible to determine the magnitude and depth range of minor shocks that may trigger the nucleation process for major earthquakes. The magnitude and depth ranges of microshocks involved in the nucleation process differed among fault types. This research highlights the importance of monitoring seismic and atmospheric activity to improve earthquake forecasting and preparedness. Hence, it is possible to identify the most vulnerable seismic zone, location of the epicenter and probable magnitude spatio-temporal analysis.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"181 8","pages":"2447 - 2474"},"PeriodicalIF":1.9,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141643066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Magnitude Threshold and Missing and Pseudo Links in Markov Chains","authors":"F. A. Nava,&nbsp;Q. J. Gutiérrez","doi":"10.1007/s00024-024-03534-9","DOIUrl":"10.1007/s00024-024-03534-9","url":null,"abstract":"<div><p>A crisp step function is not an adequate threshold for studies of Markovian occurrence of large earthquakes, because it can lead to missing or pseudo links in an observed sequence that should be a Markov chain. A more realistic threshold is a fuzzy one where there is a transition magnitude band, located between those magnitudes that are too small for the earthquakes to be part of a Markovian process and those who are certainly large enough for the earthquakes to be part of it, where earthquakes may or may not be part of the process. This fuzzy threshold is described by a membership function that gives the probability of an earthquake with a given magnitude belonging to the process. We propose a membership function with probabilities in the transition band proportional to the seismic moment. To estimate empirical transition probabilities when considering a fuzzy magnitude threshold, we propose a counting strategy for the observed transitions and justify it through Monte Carlo simulations. The counting strategy is illustrated by application to the model from a previous seismic study of the Japan area by testing, through Monte Carlo simulations, how well the counting strategy results resemble optimum estimations of the transition probabilities. The simulations are also used to study the behavior of three Markovianity measures, and it is found that the peak values of these measures are not useful in identifying the true transition band, but that this band may be better identified by using the whole set of values taken by each measure for different transition band models. As an illustration, the measures were applied to real data from the previous study, a short set corresponding to a single realization, and found that the behavior of the measures does not agree with those expected from a crisp threshold, but agree, within the limitations of the data, with either a fuzzy threshold going from zero probability for magnitudes <span>(Mle 6.9)</span> to probability one for <span>(Mge 7.2)</span> or from zero probability for magnitudes <span>(Mle 7.0)</span> to probability one for <span>(Mge 7.2)</span>.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"181 8","pages":"2495 - 2517"},"PeriodicalIF":1.9,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141610353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Electromagnetic Wave Propagation Through the Ionosphere Over Seismic Active Zones","authors":"Husan Eshkuvatov, Bobomurat Ahmedov, Munawar Shah, Dilfuza Begmatova, Punyawi Jamjareegulgarn, Angela Melgarejo-Morales","doi":"10.1007/s00024-024-03532-x","DOIUrl":"https://doi.org/10.1007/s00024-024-03532-x","url":null,"abstract":"<p>This study presents an analytical solution for the electric current formation in the lower ionosphere as a result of charged aerosols being ejected from the ground before the earthquakes. The impact of ionosphere-related processes on radio wave propagation through the atmosphere is explored by investigating the resulting energy losses of electromagnetic waves traversing this ionospheric layer. Theoretical considerations suggest that these processes may generate detectable electromagnetic signals, offering insights into seismic precursors. The effects of electron density inhomogeneities in the upper ionospheric layers on electromagnetic wave properties such as group delay, Faraday rotation, and Doppler frequency shift are examined. Understanding these effects aims to improve ionospheric monitoring techniques to detect pre-earthquake disturbances. To validate the theoretical findings, a comparison is made with the empirical data from various sources, including VLF transmitters and GPS-TEC measurements. This comparative analysis underscores the potential of electromagnetic phenomena as credible indicators of impending seismic events.</p>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"1 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141610354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In-depth Exploration of Temperature Trends in Morocco: Combining Traditional Methods of Mann Kendall with Innovative ITA and IPTA Approaches","authors":"Zohair Qadem,&nbsp;Gokmen Tayfur","doi":"10.1007/s00024-024-03535-8","DOIUrl":"10.1007/s00024-024-03535-8","url":null,"abstract":"<div><p>This study examines trends in minimum and maximum temperatures at various climate stations located in different regions of Morocco for a period of five decades (1970 to 2019). Mann–Kendall, Sen’s estimator, Innovative Trend Analysis (ITA) and Innovative Polygon Trend Analysis (IPTA) were used in the analysis. The results show significant fluctuations, at different time scales, between minimum and maximum temperatures at all stations. In coastal areas, such as Rabat Sale, minimum temperatures fell during January and February while other months saw increases. Average minimum temperatures in Rabat Sale tend to fall by 0.5 °C. On the other hand, maximum temperatures in Rabat Sale rose by 0.2 °C. A decrease of 0.4 °C for T_min and 1.6 °C for T_max were observed in higher continental regions, such as Meknes. Other stations, such as Fez Sais (0.6 °C T_min and 2.6 °C T_max) and Taza (1.1 °C T_min and 2.6 °C T_max) showed an upward trend. Trends also vary, with notable increases in minimum and maximum temperatures, indicating different climatic dynamics according to altitude and locality. In particular, the ITA highlights a significant increase in annual maximum temperatures, with a P-value &lt; 0.05 and trend slopes ranging from 0.0015 °C per year in Rabat Sale to 0.0076 °C per year in Taza. In addition, the IPTA results confirm diversity of upward and downward trends on monthly and seasonal scales, highlighting impact of geographical factors such as proximity to sea, topography, and continentality that contribute to formation of regional microclimates. The results highlight significant impact of climate change in Morocco.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"181 8","pages":"2717 - 2739"},"PeriodicalIF":1.9,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s00024-024-03535-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141568347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Source Parameters and Seismogenic Fault Model of the 2024 Mw 7.0 Wushi (Xinjiang, China) Earthquake Revealed by InSAR Observations","authors":"Shuyuan Yu, Zhejun Li, Peng Zhao, Jiaji Luo, Yuanyuan Yang","doi":"10.1007/s00024-024-03531-y","DOIUrl":"https://doi.org/10.1007/s00024-024-03531-y","url":null,"abstract":"<p>On January 23, 2024, an <i>M</i>_w 7.0 earthquake struck Wushi County, Xinjiang. This study used Sentinel-1A data to obtain the co-seismic deformation field utilising the InSAR technique in the Wushi area. An earthquake uniform slip model was determined using a Bayesian algorithm. The earthquake fault slip distribution was inverted using the steepest descent method (SDM), and the seismic impact on neighbouring faults was evaluated using the Coulomb instability criteria. The maximum displacement was approximately 76 cm in line of sight (LOS) direction as observed using ascending Interferometric Synthetic Aperture Radar (InSAR) data. The fault is responsible for earthquake trends towards the northwest, with a dip angle of approximately 62.8°, strike of approximately 229°, and slip angle of approximately 49.8°, and it displays a compressive and sinistral strike-slip motion. The fault parameters and spatial position were aligned with the Maidan Fault at the southern margin of the Tianshan Mountains. Coulomb stress analysis revealed that regions such as the Kuokesale Fault Zone, the Dashixia Fault Zone, the Tuoshengan Fault (northwest of the epicentre), the Piqiang North Fault Zone, and the Wensu North Fault Zone situated in the southeast of the epicentre experienced stress accumulation and warranted attention. The co-seismic deformation field of the two strong aftershocks indicates a southeast-trending reverse fault located in the middle of the basin. This fault, influenced by the continuous compressive movement of the Maidan Fault, predominantly exhibited reverse movement during an earthquake. The seismic activity in the Wushi earthquake sequence indicates crustal shortening in the southern Tianshan region facilitated by the absorption of compression from the frontal compressional thrust belt and high-angle reverse faults in the orogenic belt.</p>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"28 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141568510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"b-value as a Seismic Precursor: The 2021 Mizoram Earthquake Mw 6.1 in the Indo-Burma Subduction Zone","authors":"Vickey Sharma,&nbsp;Rajib Biswas","doi":"10.1007/s00024-024-03530-z","DOIUrl":"10.1007/s00024-024-03530-z","url":null,"abstract":"<div><p>This study explores the feasibility of using fluctuations in the recurrence magnitude dispersion factor (b-value) as a seismic precursor for the Mizoram earthquake that occurred on November 26, 2021, in the Indo-Burma region of northeast India. Employing a comprehensive and homogeneous earthquake catalog spanning from 1900 to 2020, the seismic analysis involved delustering and completeness testing. The research implements a sub-sectional b-value calculation method, dividing the study area into uniformly sized grid cells (2° × 2°) and performing temporal b-value mapping for each grid. The epicenter of the Mizoram earthquake was located within a grid cell characterized by an intermediate b-value. Time-series analysis of the b-value indicated a notable decline preceding the main event, suggesting its potential as a seismic precursor. The study also examines depth-dependent variations in the b-value, revealing an inverse relationship between the b-value and crustal stress. To evaluate the significance of b-value anomalies, the Kolmogorov–Smirnov (K-S) statistic was employed instead of visual inspection. Additionally, the research provides probabilistic estimates of seismic hazard parameters, including the most probable maximum yearly earthquake, mean return period, and probabilities of earthquakes of varying magnitudes. These findings contribute to a deeper understanding of the complex seismotectonic framework and high lithospheric variability in the investigated region.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"181 8","pages":"2475 - 2493"},"PeriodicalIF":1.9,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141568346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Historical Land Cover Changes on Land Surface Characteristics over the Indian Region Using Land Information System","authors":"Vibin Jose,&nbsp;Anantharaman Chandrasekar,&nbsp;Suraj Reddy Rodda","doi":"10.1007/s00024-024-03523-y","DOIUrl":"10.1007/s00024-024-03523-y","url":null,"abstract":"<div><p>The present study has employed a regional Land Surface Model (LSM) to investigate the impact of historical land cover changes on land surface characteristics over the Indian subcontinent for the period of 1930–2013. Four simulations that include a control run and three experiment runs are performed with the Noah 3.6 LSM within the Land Information System (LIS). In the present study, the Noah LSM is driven by meteorological forcings, with radiation data obtained from the Global Data Assimilation System (GDAS) and the rainfall data obtained from IMD gridded rainfall data. The control run is performed with a MODIS-IGBP land cover map, while the three experimental runs are performed with three different potential land cover maps for the years 1930, 1975, and 2013. The potential land cover maps for the above three simulations are developed by blending the MODIS-IGBP data set with the fractional forest cover data set; the latter data is available for the years 1930, 1975, and 2013. Results indicate that the historical land cover change (1930 to 2013) has reduced the annual mean of latent heat flux and net surface heat flux over the Indian domain by <span>(-)</span>24.74 <span>(W/m^2)</span> and <span>(-)</span>14.18 <span>(W/m^2)</span> respectively, while the sensible heat flux and the soil temperature has increased by 4.97 <span>(W/m^2)</span> and 2.78 K. The annual mean change in latent heat flux, sensible heat flux, and soil temperature demonstrate that the largest changes occur when the land cover changes from forest to urban land as compared to forest to cropland, forest to grassland and forest to open shrubland. The annual mean change in latent heat flux is moderately large for the land cover change from forest to open shrubland when compared to forest to grassland and forest to cropland. The above is attributed to the effects of evapotranspiration, which has high values for the cropland followed by grassland and open shrubland. Furthermore, the triple collocation method is employed to assess the impact of historical land cover change on soil moisture. Results indicate that the triple collocation method effectively demonstrates the impact of land cover change on soil moisture.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"181 8","pages":"2561 - 2588"},"PeriodicalIF":1.9,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141568511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid Particle Swarm Optimized Models for Rainfall Prediction: A Case Study in India","authors":"Chawngthu Zoremsanga,&nbsp;Jamal Hussain","doi":"10.1007/s00024-024-03528-7","DOIUrl":"10.1007/s00024-024-03528-7","url":null,"abstract":"<div><p>Predicting rainfall is crucial across multiple sectors and activities, impacting agriculture, water management and disaster preparedness. In this study, the Particle Swarm Optimization (PSO) algorithm is used to optimize the hyperparameters of hybrid deep learning and machine learning models such as Bidirectional Long Short-Term Memory (BiLSTM), Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), Artificial Neural Network (ANN) and Support Vector Regression (SVR). The performances of the PSO-optimized models are compared using the monthly rainfall dataset of Aizawl Weather Station and the all-India monthly average rainfall dataset. For the all-India rainfall datasets, the results of the PSO models are also compared with models from previous studies. The results show that, for the all-India rainfall dataset, the hybrid model PSO-BiLSTM IV achieved an RMSE of 225.12 and outperformed an existing RNN model by 14% and an existing single-cell LSTM, Vanilla LSTM and stacked LSTM by 11%, 10% and 8% respectively. In the Aizawl Weather Station dataset, the hybrid model PSO-BiLSTM II achieved the best result with an RMSE of 76.6, a benchmark result for this dataset. Overall, the hybrid PSO-BiLSTM models have the lowest RMSE score and the SVR models achieve the lowest performance for both datasets.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"181 7","pages":"2343 - 2357"},"PeriodicalIF":1.9,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141511635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}