Journal of Atmospheric and Solar-Terrestrial Physics最新文献

{"title":"Probable signatures of the polarization jet in the plasmasphere","authors":"G.A. Kotova ,&nbsp;V.L. Khalipov ,&nbsp;A.E. Stepanov ,&nbsp;V.V. Bezrukikh","doi":"10.1016/j.jastp.2025.106482","DOIUrl":"10.1016/j.jastp.2025.106482","url":null,"abstract":"<div><div>The measurements of cold plasma on the MAGION 5 spacecraft detected the regions in the plasmasphere or in its boundary layer close to the plasmapause in which proton density is increased by 2 or more times compared to the surrounding areas. As a rule, such structures with increased density are observed after substorm disturbances. Earlier ground-based and satellite measurements evidence that during substorms in the polarization jet band the ascending plasma flows from the ionosphere are formed, the vertical velocity of which reaches 1.0–2.0 km/s at the heights of DMSP satellites (∼850 km). Some examples of case studies are given where registered structures of increased density in the plasmasphere are compared with the observations of rapid plasma flows from the ionosphere during the development of polarization jet taking into account the time of the movement of plasma from the ionosphere to the plasmasphere. These examples suggest the interrelationship of the observed phenomena over long time intervals.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"269 ","pages":"Article 106482"},"PeriodicalIF":1.8,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534844","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":"Cropland classification and water stress vulnerability assessment in arid environment of Churu district, India using machine learning approach","authors":"Zubairul Islam ,&nbsp;Azizur Rahman Siddiqui ,&nbsp;Sudhir Kumar Singh ,&nbsp;Jaspal Singh ,&nbsp;Rajesh Bajpai ,&nbsp;Saroj Ahirwar","doi":"10.1016/j.jastp.2025.106483","DOIUrl":"10.1016/j.jastp.2025.106483","url":null,"abstract":"<div><div>The focus was to map the cropland area and assess the water stress vulnerability within the area. Cropland mapping was performed via a machine learning (ML)-based ensemble classifier (EC). The leveraging of Random Forest, Extreme Gradient Boosting, and Support Vector Machines (RF, XGB, and SVM) models using Landsat 8 data of period 2022–23. The key inputs for the models included the spectral indices such as Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Enhanced Vegetation Index (EVI), Soil Adjusted Vegetation Index (SAVI), Modified Soil Adjusted Vegetation Index (MSAVI), and Land Surface Temperature (LST) in the pre- and post-harvest period of both rabi and kharif crops. Kendall tau-b trend analysis (1991–2023) of the same indices was performed to estimate the long-term changes. The water stress was modeled via the generalized additive model (GAM). The EC identified 11,600.01 km² of cropland and 2254.32 km² of non-cropland, with a more than 90 % F1 score, 92.5% overall accuracy, and a Kappa coefficient (0.84). The trends show significant positive change for NDVI, EVI, and NDWI, while LST increased. The GAM demonstrated a strong fit, with an adjusted coefficient of determination (R²) of 0.89. Model diagnostics show an R² (0.79). The five-fold cross-validation confirmed the model's robustness. Moran's I analysis reveal a significant spatial clustering. The study concludes that water stress is influenced by spatially correlated factors, providing a framework for targeted crop management efforts in the area of Rajasthan, India.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"269 ","pages":"Article 106483"},"PeriodicalIF":1.8,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534909","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":"Analysis of intense geomagnetic storm on 24 April 2023 with interplanetary parameters","authors":"Pawan Kumar ,&nbsp;Mahender Pal ,&nbsp;Sham Singh","doi":"10.1016/j.jastp.2025.106481","DOIUrl":"10.1016/j.jastp.2025.106481","url":null,"abstract":"<div><div>We study plasma parameters with geomagnetic indices for intense geo storms with Dst &lt; −200 nT during the 25 solar cycle. Using planetary index (Kp) 3 h data, symmetric index (SYM/H) minute resolution data, and solar plasma measurements from multiple satellites, examine the connection of significant events of space weather that occurred on 24 April 2023 with past Geostorm occurred on 23 and 24 cycles. The statistical correlation and time series analysis study examined the relationship between plasma parameters and geomagnetic indices during major geomagnetic storms on April 24, 2023. The correlation (Cr) between solar wind (SW) pressure and interplanetary magnetic field (IMF) B and Kp, SW speed, and SYM/H have a strong positive correlation (Cr &gt; 0.70). The findings will provide valuable insights into the relationships between interplanetary conditions and space weather dynamics, contributing to the broader understanding of Space Weather dynamics.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"269 ","pages":"Article 106481"},"PeriodicalIF":1.8,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479356","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":"Nighttime and seasonal variation of lower ionospheric parameters using tweek analysis during minimum solar activity period over low latitude","authors":"Kshama Tiwari,&nbsp;S.B. Singh,&nbsp;A.K. Singh","doi":"10.1016/j.jastp.2025.106476","DOIUrl":"10.1016/j.jastp.2025.106476","url":null,"abstract":"<div><div>VLF signals are continuously recorded, monitored, and observed by an Automatic Whistler Detector (AWD) installed at our low latitude Indian station, Banaras Hindu University, Varanasi (geom. lat. 14° 55^’ N, geom. long. 154° E and geog. lat. 25°15′ 20″ N, long. 82° 59’ 21” E). In the present study, the nighttime and seasonal variation of lower ionospheric parameters mainly D-region during a low solar minimum period from 2018 to 2019 has been analyzed at a low latitude station in Varanasi. Since large numbers of tweeks have been observed at Varanasi, we have randomly chosen three days in a month during the summer (June), winter (November), and equinox (September/October) seasons in the years, 2018 and 2019, where good-quality, continuous nighttime data were available. A total of 35,000 tweeks recorded up to <em><strong>n = 1–10</strong></em> harmonics in different seasons: summer, winter, and equinox showed percentage occurrences of approximately 37%, 32%, and 31% in 2018 and 38%, 31%, and 31% in 2019 respectively during the solar minimum period of solar cycle 24. The analysis of tweeks with harmonics up to tenth modes in different seasons showed higher occurrence in summer, reflecting at less diverse altitudes than winter and equinox seasons, with propagation paths ranging from 500 to 8500 km in 2018 and 800–8000 km in 2019. Nighttime lower ionospheric daily average electron density <strong>(</strong><em><strong>n</strong></em>_{<em><strong>e</strong></em>}<strong>)</strong> values varied from 23 to 26 cm⁻³ at altitudes of 80–94 km during 2018 and 2019. The D-region is less uniform at higher altitudes during summer. The effect of reflection height on frequency, attenuation factor, time delay, and the usefulness of tweek method for estimating electron density in the nighttime D region ionosphere for different harmonics are also discussed in this study. The electron density <strong><em>(n</em></strong>_{<strong><em>e</em></strong>}<strong><em>)</em></strong> values obtained by the tweek method during various seasons are compared to IRI-2016, radar data, and rocket data, all of which fall within a similar range of variations specifically between 80 and 90 km showing a better estimation by the tweek method. Further, we have also evaluated the attenuation coefficient of the nighttime tweek propagation. We have also simulated the frequency-time spectrum of different modes of tweeks at various heights and propagation paths.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"269 ","pages":"Article 106476"},"PeriodicalIF":1.8,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479409","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":"Multifractal and monofractal characteristics of ULF magnetic fields in Kachchh region, Gujarat, India: Prospects for earthquake precursor detection","authors":"Sushanta Kumar Sahoo,&nbsp;Madhusudhanarao Katlamudi,&nbsp;Chandra Sekhar Pedapudi","doi":"10.1016/j.jastp.2025.106478","DOIUrl":"10.1016/j.jastp.2025.106478","url":null,"abstract":"<div><div>Understanding electromagnetic emissions linked to earthquakes is critical for advancing precursor studies, yet research remains limited in seismically active regions like Kachchh, Gujarat, India. This study investigates Ultra-Low Frequency (ULF) magnetic field variations recorded over eight months (January 1–August 13, 2012) at the Multi-parametric Geophysical Observatory (MPGO) in Desalpar (23.742°N, 70.686°E). The analysis focuses on their connection to a magnitude 5.1 earthquake near the observatory on June 20, 2012. Data from a Digital Fluxgate Magnetometer (DFM) were analyzed using Detrended Fluctuation Analysis (DFA) and Multifractal Detrended Fluctuation Analysis (MFDFA) to explore scaling properties in the 0.001–0.1 Hz frequency range. Periodogram analysis identified diurnal and semi-diurnal periodicities, removed using Empirical Mode Decomposition (EMD) to isolate aperiodic signals. DFA results showed non-uniform fluctuation functions with scaling exponent variations prior to the earthquake on June 20, 2012. Notably, the instability index (β) increased in the H-component six days before the event (June 14, 2012), in the D-component on June 17–18, 2012, and in the Z-component one day before (June 19, 2012). MFDFA revealed long-range power-law correlations, with differences in multifractal spectra between observed and shuffled time series, indicating long-range correlations drive multifractality. Surrogate analyses confirmed these correlations while reducing Gaussian characteristics. The multifractal spectrum of H, D, and Z components widened during seismically active phases compared to quiet phases, emphasizing the utility of multifractal analysis in detecting ULF magnetic field instabilities. Abnormal time dynamics in the multifractal characteristics of the H- and Z-components were observed shortly before the earthquake on June 20, 2012. This research highlights the potential of such methods for earthquake monitoring and early-warning systems in active seismic regions.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"269 ","pages":"Article 106478"},"PeriodicalIF":1.8,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465136","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":"Spatio-temporal variation of particulate matter (PM10) concerning the COVID-19 pandemic in the major cities of Uttarakhand, India","authors":"Amar Deep ,&nbsp;Tushar Kandari ,&nbsp;Hemwati Nandan ,&nbsp;Mahima","doi":"10.1016/j.jastp.2025.106464","DOIUrl":"10.1016/j.jastp.2025.106464","url":null,"abstract":"<div><div>The present investigation focuses on one of the principal air quality parameters, Particulate Matter (PM₁₀), in some of the major cities of Uttarakhand, viz. Haridwar, Dehradun, Rishikesh, Kashipur, Rudrapur, and Haldwani during 2011–2020. In the year 2020 (from 22nd March to September), the lockdown was implemented worldwide due to the COVID-19 pandemic, which resulted in a considerable decrease in air pollutants globally and nationally. Understanding the ambient air quality of Uttarakhand requires analyzing PM₁₀ variability in these cities, which are among the most populated and industrialized in the state. Hence, a decadal study explains the change in air quality with every changing year. The observed PM₁₀ concentration was 2–3 times higher than the prescribed limits (60 μgm⁻³) fixed by the Central Pollution Control Board (CPCB) in New Delhi, India. The highest (251.8 μgm⁻³) PM₁₀ concentration was observed in the winter season (2011) as compared to other seasons in Dehradun city. The PM₁₀ concentration was observed to be high during this decadal period except in 2020 due to the COVID-19 lockdown. A negative correlation coefficient was observed when correlated with rainfall and humidity, while a positive correlation was observed when correlated with temperature for all the sampling sites. The calculated p-values for PM10 and meteorological parameters for Haridwar, Dehradun, Rishikesh, Kashipur, and Rudrapur are 0.01, 0.05, 0.01, 0.05, 0.01, and 0.01, respectively.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"269 ","pages":"Article 106464"},"PeriodicalIF":1.8,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562531","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":"Statistical study of low-latitude E-region irregularity occurrence rate based on Qujing VHF radar observations","authors":"Yunzhou Zhu ,&nbsp;Qiong Tang ,&nbsp;Zhongxin Deng ,&nbsp;Chen Zhou ,&nbsp;Tong Xu ,&nbsp;Yi Liu ,&nbsp;Zhengyu Zhao ,&nbsp;Fengsi Wei","doi":"10.1016/j.jastp.2025.106479","DOIUrl":"10.1016/j.jastp.2025.106479","url":null,"abstract":"<div><div>Based on the Quing VHF radar (25.6°N, 103.7°E, magnetic latitude 16.1°N, magnetic longitude 177.0°E) measurements from 2016 to 2020, the morphological characteristic of low-latitude E-region field-aligned irregularities (FAIs) was reported in this work. Statistical results show that the occurrence of Qujing E-region irregularities highly depends on both season and local time. The occurrence rate of E-region FAIs peaks in the summer, with the lowest occurrence rates in autumn and winter, and primarily occurs at night. The Doppler spectrum suggests that the Qujing E-region FAI echoes are mainly characterized by type II echoes. Quantitative analysis of both the activity of the Es layer and E-region FAI structures was also conducted. It is found that the occurrence of low-latitude E-region FAIs is closely correlated with the enhanced electron density structures inherent in the local Es layers. Given the weak electric field at low and mid-latitudes, neutral winds controlling ion drift likely trigger gradient drift instability above the Es layer, leading to small-scale irregularities in Qujing. Further investigation is required to understand the influence of the medium-scale traveling ionospheric disturbance on the occurrence rate of ionosphere E-region FAIs in low latitudes.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"269 ","pages":"Article 106479"},"PeriodicalIF":1.8,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465205","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":"Long-term drought characterization: A spatiotemporal analysis in Rayalaseema, southern peninsular India","authors":"Kandula Bharghavi ,&nbsp;Hemalatha Kapa ,&nbsp;Thotli Lokeswara Reddy ,&nbsp;Penti Rajesh ,&nbsp;Krishnareddigari Krishna Reddy","doi":"10.1016/j.jastp.2025.106467","DOIUrl":"10.1016/j.jastp.2025.106467","url":null,"abstract":"<div><div>The unique combination of features in Andhra Pradesh's Rayalaseema region makes it an ideal location for drought studies. These features include hilly terrain, a semi-arid climate with the lowest rainfall in India, and the influence of both the Southwest and Northeast monsoons. Rainfall is a fundamental metric for water availability, while temperature plays a pivotal role in regulating evapotranspiration rates. Understanding their trends is crucial since both factors are integral in delineating drought conditions. This study delves into the drought dynamics of the Rayalaseema region from 1961 to 2021, employing meteorological drought indices: the standardized precipitation evapotranspiration index (SPEI) and the standardized precipitation index (SPI). In order to achieve this, rainfall data was retrieved from the archives of the India Meteorological Department (IMD), while temperature data was sourced from ERA-5 (the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis). In order to assess the significance of drought characteristic trends across various temporal and spatial scales, the Mann-Kendall trend test and Sen's slope estimator techniques were applied. Rainfall patterns varied significantly, with Kurnool receiving the highest and Anantapur the lowest, while temperatures steadily increased, peaking in the sixth decade, especially in Kadapa, Kurnool, and Chittoor, with June being the warmest month. Rainfall trends shifted from negative to positive, with Kurnool and Chittoor experiencing significant increases, while Kadapa and Anantapur continued to face negative trends. Drought conditions, as measured by SPI and SPEI, were frequent, particularly in the first three decades, with a shift towards wetter conditions in later decades. The SPEI trends revealed rising drought severity, exacerbated by increasing temperatures, particularly in Kurnool and Kadapa. Nonetheless, both indices effectively capture significant drought events, with SPEI detecting more severe drought occurrences than SPI.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"269 ","pages":"Article 106467"},"PeriodicalIF":1.8,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465206","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":"Short-time forecast of ionospheric irregularities using long short-term memory networks over equatorial and low-latitudes regions","authors":"Olakunle L. Ojo ,&nbsp;Oladipo Emmanuel Abe ,&nbsp;Olaide Sakiru Hammed ,&nbsp;Olugbenga Olumodimu","doi":"10.1016/j.jastp.2025.106466","DOIUrl":"10.1016/j.jastp.2025.106466","url":null,"abstract":"<div><div>Predicting ionospheric conditions is becoming increasingly important towards the operational efficiency of both ground-based and space-borne radio communication systems with a view to compensate for the effects of space weather. This study focuses on predicting ionospheric irregularities in the complex and variable equatorial ionosphere which is deemed critical for optimal space-based application. We utilized the Long-Short-Term-Memory (LSTM) deep learning algorithm to develop a predictive model for forecasting disturbances in the equatorial ionization anomaly (EIA) region using Global Navigation Satellite Systems (GNSS) data. We utilized fifteen-year worth of data (2005–2020) to train, validate and test the performance of the model and assessed the results against a baseline model relying on daily and hourly Rate of Change of TEC Index (ROTI) values and utilized evaluation metrics such as correlation (R), determination coefficient (<span><math><mrow><msup><mi>R</mi><mn>2</mn></msup></mrow></math></span>), and mean squared error (MSE). Remarkably, the LSTM Predictive Model consistently outperformed the Baseline Model across various stations, demonstrating higher R and R² values and significantly lower MSE. These results indicate the LSTM model's superior accuracy in forecasting ionospheric disturbances, essential for space-based applications. The distribution analysis of residual errors highlighted the LSTM model's ability to better capture underlying patterns and variability in the target variable. This study contributes to enhancing ionospheric forecasting models for space applications, ensuring the dependability of space-based systems.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"269 ","pages":"Article 106466"},"PeriodicalIF":1.8,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512306","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":"Sudden pollution incidents around Beijing on a crisp October day: Insights from capturing pollution conveyor belts","authors":"Deying Wang ,&nbsp;Jizhi Wang ,&nbsp;Yuanqin Yang ,&nbsp;Wenxing Jia ,&nbsp;Junting Zhong ,&nbsp;Xiaofei Jiang ,&nbsp;Liangke Liu ,&nbsp;Yaqiang Wang ,&nbsp;Xiaoye Zhang","doi":"10.1016/j.jastp.2025.106461","DOIUrl":"10.1016/j.jastp.2025.106461","url":null,"abstract":"<div><div>North China Plain, an area is usually sunny and cloudless in autumn, rare heavy pollution suddenly occurred around Beijing. This is a new focus of public attention and research. Since late October 2023, it has caused sudden haze pollution. This study focuses on capturing the mechanisms behind sudden pollution in clear skies, tracking the establishment and transmission of adverse weather conditions, focusing on targeted key stations affected by adverse weather. Revealing the correlation between implicit multiple types of precursor meteorological signals: atmospheric boundary layer, condensation rate threshold, in the atmosphere. Obtain the coupling point of the interaction and matching between micro-scale disturbances and weather-scale fluctuations, and reveal its driving mechanism behind sudden pollution in clear skies. The novelty of this study lies in targeting regions that have achieved certain success in emission reduction. Provide insights into the \"feedback\" effects that adverse weather conditions can cause. It particularly provides a further understanding of the interactions between clouds, aerosols in the “pollution conveyor belt” and provides quantitative indicators for early warning. Provide quantitative technical support for developing accurate response measures in air quality research.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"269 ","pages":"Article 106461"},"PeriodicalIF":1.8,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454341","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}