Journal of Atmospheric and Solar-Terrestrial Physics最新文献

{"title":"Study of separation in junction frequency in vertical incidence ionogram traces observed at low-mid latitude Indian station, New Delhi: Ionosonde observations","authors":"Arti Bhardwaj ,&nbsp;Anshul Singh ,&nbsp;Qadeer Ahmed ,&nbsp;Ankit Gupta ,&nbsp;A.K. Upadhayaya","doi":"10.1016/j.jastp.2024.106414","DOIUrl":"10.1016/j.jastp.2024.106414","url":null,"abstract":"<div><div>Ionogram traces split into two modes, ordinary (O) and extraordinary (X), in the F-layer due to magneto-ionic splitting, where a transmitted pulse propagates in two distinct ways under the influence of Earth's magnetic field. The Earth's magnetic field causes ionogram traces to show double hop echoes when an echo is reflected back upward by the ground and then re-reflected by the ionosphere, demonstrating that the ionosphere is a doubly refracting medium. We have investigated the separation in Junction frequencies (JFs) of the O and X modes in vertical incidence ionogram traces observed over a seven-year period (2014–2020) during the declining phase of the solar cycle, from maximum to minimum. This difference in splitting in two modes is expected to be 0.67 MHz at low-mid latitude Indian station, New Delhi (28.6°N, 77.2°E). Anomalous separations of more than 21% in JFs were observed during the analysis. In these cases, we found over 30% anomalous cases of JFs in different seasons, with the highest occurrence in summer, followed by equinox and winter. JFs followed diurnal variation, with heightened variation during the solar cycle maxima and minimal variation during solar cycle minima. Lastly, we observed a concurrency between JFs and ionospheric perturbations caused by phenomena originating in both the lower and upper atmosphere.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"267 ","pages":"Article 106414"},"PeriodicalIF":1.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143137481","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":"A novel hybrid solar radiation forecasting algorithm based on discrete wavelet transform and multivariate machine learning models integrated with clearness index clusters","authors":"Burak Arseven,&nbsp;Said Mahmut Çınar","doi":"10.1016/j.jastp.2025.106417","DOIUrl":"10.1016/j.jastp.2025.106417","url":null,"abstract":"<div><div>This study presents an innovative forecasting algorithm that combines multivariate regression (MR) and discrete wavelet transform (DWT) techniques with clearness index (CI)-based clustering methods to enhance short-term (1 h ahead) solar radiation forecasting. The proposed algorithm consists of two main steps: the first involves forecasting processes using DWT and MR methods, while the second includes clustering processes determined based on CI values. In the forecasting process, the data has been decomposed into sub-signals at different levels using DWT first. Multivariate ridge regression (MRR) and lasso regression (MLR) models for the sub-signals have been determined based on input training data sets created from three different combinations of these sub-signals. Sub-forecast signals have been obtained using models that were determined in different formats. The sub-forecast signals obtained have been recombined using the DWT reconstruction to produce the final forecasts. In the clustering process, clusters have been formed based on CI values using the Kernel k-means algorithm, which has been identified as the most effective among three different algorithms. The effectiveness of forecasts generated using DWT-MRR and DWT-MLR models for all input data set versions has been evaluated within the CI-based clusters.</div><div>The study's key findings have revealed that decomposition at the first level of DWT is sufficient to achieve optimal forecasting performance. Furthermore, the input variables yielding the best results have differed across clusters: radiation and relative humidity for the mostly cloudy cluster, radiation, temperature, and relative humidity for the cloudy cluster, and radiation and temperature for the slightly cloudy cluster. The results have demonstrated that the proposed algorithm achieves a 17% improvement in root mean square error (RMSE) compared to the best-performing model developed without CI clustering. The proposed approach significantly contributes to the literature by optimizing DWT decomposition levels, adapting data modeling to cloudiness conditions, and integrating multiple forecasting techniques to improve performance.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"267 ","pages":"Article 106417"},"PeriodicalIF":1.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143137168","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":"Interpretable artificial intelligence models for predicting lightning prone to inducing forest fires","authors":"Sida Song ,&nbsp;Xiao Zhou ,&nbsp;Shangbo Yuan ,&nbsp;Pengle Cheng ,&nbsp;Xiaodong Liu","doi":"10.1016/j.jastp.2024.106408","DOIUrl":"10.1016/j.jastp.2024.106408","url":null,"abstract":"<div><div>Specific types and intensities of lightning are significant causes of forest lightning fires. Analyzing the relationship between these lightning events and the climatic conditions that favor their occurrence is crucial for predicting and preventing forest lightning fires. However, there is a lack of research in this area for the Greater Khingan Range in Northeast China. This study utilized data from three lightning location networks and the ERA5 meteorological dataset to analyze the historical climate and lightning data in the Greater Khingan Mountains region of China from 2021 to 2023, focusing on the impact of various climatic factors on the density of target lightning—lightning that is prone to cause forest lightning fires. Four machine learning models—SVM, RF, XGBoost, and LightGBM—were evaluated, with RF demonstrating the best predictive performance, achieving R² of 0.83, MAE of 1.91, and MSE of 14.90. Additionally, the prediction results of the RF model were evaluated using the Kruskal-Wallis test to determine if the results are statistically significant. Using SHAP values to interpret the model, it was found that the K-index (kx) and Convective Available Potential Energy (CAPE) are the most significant predictors of target lightning density, followed by the leaf area index for high vegetation (lai_kv), surface pressure (sp), cloud base height (cbh), temperature at 2 m (t2m), and coverage of high vegetation (cvh). Approximately 70% of the total average absolute SHAP values are attributed to kx and CAPE, highlighting their crucial role in the prediction process. This study provides insights into the environmental factors influencing lightning frequency and emphasizes the importance of interpretable machine learning models in predicting future lightning occurrences and forest lightning fires. Visualization tools, including SHAP summary plots and force plots, were used to provide a detailed illustration of each feature's contribution to the model predictions.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"267 ","pages":"Article 106408"},"PeriodicalIF":1.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143137179","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":"Analytical model for the transit time of an interplanetary magnetic cloud","authors":"E. Romashets ,&nbsp;M. Vandas ,&nbsp;T. Weaver ,&nbsp;C. Bahrim","doi":"10.1016/j.jastp.2024.106416","DOIUrl":"10.1016/j.jastp.2024.106416","url":null,"abstract":"<div><div>This paper presents an analytical model for the propagation of a toroidal interplanetary magnetic cloud from the vicinity of the Sun to Earth’s orbit. This model is applied to the May 12–15, 1997 event for calculations of cloud’s acceleration and velocity using a three forces approximation in driving the magnetic cloud’s dynamics: the diamagnetic push away from the stronger magnetic field region near the Sun, a drag force due to the ambient solar wind, and the Sun’s gravity pull. From the minimization of the difference between the calculated versus observed transit time of the magnetic cloud, we determine free parameters of our model and identify the solar source on May 12 at 5:03 UT. In situ measurements near Earth’s orbit done before May 12 set the values of the ambient interplanetary magnetic field, as well as of the ambient solar wind through which the magnetic cloud traveled. The observed temperature and density inside the magnetic cloud at Earth’s orbit determine the corresponding inner values during the magnetic cloud’s propagation. The coefficient of the drag force is one of free parameters in the model.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"267 ","pages":"Article 106416"},"PeriodicalIF":1.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143137479","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":"Climatology and circulation classification of Saharan dust over Bulgaria","authors":"Ralena Ilieva ,&nbsp;Krasimir Stoev ,&nbsp;Guergana Guerova","doi":"10.1016/j.jastp.2024.106403","DOIUrl":"10.1016/j.jastp.2024.106403","url":null,"abstract":"<div><div>The Sahara is the largest hot desert in the world and produces more aeolian soil dust than any other desert. Saharan dust significantly impacts climate, biogeochemical, and hydrological processes. Additionally, Saharan dust strongly affects air quality and human health. As a result, it is important to monitor the frequency and the transport patterns of dust outbreaks. In this work, it is found that for the 10 years (2011–2020), there are a total of 365 days with Saharan dust transport over Bulgaria, with the number of days per year being between 16 and 53. The monthly climatology shows that the month with the largest number of days is March. The rarest transport of Saharan dust over Bulgaria is observed during the summer months. An objective classification of the atmospheric circulation on days with Saharan dust transport to Bulgaria is made for the period 2011–2019. Two objective circulation classifications — GrossWetter Types and Jenkinson–Collison Type with 26 types were used. The main circulation types with the transport of Saharan dust are associated with the development of Mediterranean cyclones and the transport of air masses from the south-southwest. A case study of Saharan dust intrusion into Bulgaria was made for the period from 25 to 27 March 2020. The specific synoptic conditions that lead to the transport of Saharan dust are discussed.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"267 ","pages":"Article 106403"},"PeriodicalIF":1.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143137178","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":"Performance analysis of IRI-2016 and IRI-2020 models, and GPS and GLONASS-TEC variations, and their predictions using Artificial Neural Networks (ANNs) at low latitude station Agra, India","authors":"Swati ,&nbsp;Priya Gupta ,&nbsp;Nitin Dubey ,&nbsp;Sparsh Agarwal ,&nbsp;Dhananjali Singh ,&nbsp;Devbrat Pundhir","doi":"10.1016/j.jastp.2024.106412","DOIUrl":"10.1016/j.jastp.2024.106412","url":null,"abstract":"<div><div>The total electron content (TEC) data was collected using the newly installed receiver namely GPStation6 at the Agra, India station in 2016. The TEC data for Global Positioning System (GPS) and GLONASS navigation systems and the IRI-2020 and IRI-2016 models were statistically processed diurnally, monthly, seasonally, and yearly during the descending phase of solar activity in 2018. The entropy of the TEC variations was calculated to assess the chaotic behaviour of the data. Subsequently, the observed results were predicted using artificial neural networks (ANNs). The highest TEC values for GPS, GLONASS, and both IRI models were recorded in April (≈50 TECU and 35 TECU), whereas the lowest values were recorded in November and December (≈20–25 and 15–20 TECU). In terms of seasonal values, GPS and GLONASS-TEC were underestimated by the IRI models. The maximum seasonal TEC values (≈45 TECU) were recorded for GLONASS in the equinox, ≈35 TECU for GPS in the summer, and ≈30 TECU for both IRI models in the equinox, while the minimum TEC values were recorded in winter for GPS (≈30 TECU), GLONASS (≈35 TECU), and IRI models (≈25 TECU). A strong correlation was observed between TEC variations and IRI models. A weaker and negative correlation between magnetic storm activity (∑Kp) and observed TEC variations was observed, whereas a weaker and positive correlation was found between TEC and solar activity (F10.7). The entropy values were higher for GPS-TEC than for GLONASS-TEC. These variations were interpreted based on literature published by previous researchers.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"267 ","pages":"Article 106412"},"PeriodicalIF":1.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143137480","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":"Separation frequency of large-scale anisotropic eddies and small-scale isotropic eddies in the near-neutral and unstable atmospheric surface layer","authors":"Guowen Han,&nbsp;Bowen Zhang,&nbsp;Lixia Wang,&nbsp;Hongshuo Yan,&nbsp;Guowei Xin,&nbsp;Xiaobin Zhang","doi":"10.1016/j.jastp.2025.106429","DOIUrl":"10.1016/j.jastp.2025.106429","url":null,"abstract":"<div><div>High-frequency fluctuations of streamwise, spanwise, and vertical velocity components were measured in the logarithmic region of the atmospheric surface layer (ASL) to analyze the separation frequency of large-scale anisotropic eddies and small-scale isotropic eddies in high Reynolds number wall turbulence. The experimental results indicate that the separation frequency decreases exponentially with height and increases linearly with friction velocity in the near-neutral ASL. Furthermore, our study investigated the impact of atmospheric thermal stability on the separation frequency and revealed a decrease in the separation frequency with increasing thermal buoyancy in the ASL. By analyzing the mean wind shear in the near-neutral and unstable ASL at different heights, our study suggested that mean wind shear destroys large-scale turbulent eddies, transforming them into small-scale turbulent eddies. This phenomenon may lead to variations in the separation frequency with height, friction velocity, and atmospheric thermal stability. Our findings may shed new light on the understanding of atmospheric turbulence dynamics and its implications for the local-isotropy hypothesis in the ASL.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"267 ","pages":"Article 106429"},"PeriodicalIF":1.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143137484","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":"Soil moisture downscaling in the state of Oklahoma: Employing advanced machine learning","authors":"Sahar Rezaei Koujani,&nbsp;Seyed Abbas Hosseini,&nbsp;Ahmad Sharafati","doi":"10.1016/j.jastp.2025.106454","DOIUrl":"10.1016/j.jastp.2025.106454","url":null,"abstract":"<div><div>This investigation employs a machine learning downscaling framework, explicitly utilizing the Random Forest (RF) algorithm, to enhance the spatial resolution of soil moisture data obtained from the Global Land Data Assimilation System (GLDAS) model, thereby transitioning from a resolution of 27 km–1 km, which significantly increases its utility for agricultural applications. By incorporating high-resolution predictors sourced from Moderate Resolution Imaging Spectroradiometer (MODIS) products, including Evapotranspiration (ET), Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), and Land Surface Temperature (LST), along with supplementary datasets such as Open Land Map Soil attributes (clay and sand fractions), NASA SRTM Digital Elevation Model (30 m), and MODIS land cover classifications (MCD12Q1), this research effectively executes the downscaling of GLDAS data. These methodological enhancements produce more precise soil moisture estimations for assessing agricultural droughts. To ensure alignment with empirical observations, this methodology incorporates Quantile Mapping (QM) bias correction, thereby enhancing the accuracy of the GLDAS data about in-situ measurements gathered over 20 years across six agricultural regions in Oklahoma. Following an evaluation of the significance of each predictor via p-value analysis, the Enhanced Vegetation Index (EVI) was omitted due to its high p-value, indicating a negligible impact on the accuracy of soil moisture estimations. The research validates the downscaled soil moisture estimations through performance metrics, including Root Mean Square Error (RMSE) Correlation Coefficients (CC), and coefficient of determination (R²), resulting in an average RMSE of 0.06 (m³/m³), which signifies concordance between the downscaled data and the observed measurements. Seasonal examination reveals that the highest correlation is observed during autumn, attributed to consistent precipitation patterns, with CC and R² values reaching a maximum of 0.74 and 0.85 in humid regions; conversely, correlations decrease in semi-humid and arid regions, likely due to the influence of irrigation practices and diminished rainfall variability. In the final phase, the application of QM bias correction further mitigates errors, particularly improving accuracy in humid areas. These findings underscore the effectiveness of downscaled GLDAS data, augmented with various ancillary datasets, for regional drought monitoring and agricultural management. This study is a reliable resource for addressing data limitations and supporting informed decision-making of farming sectors facing resource constraints.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"268 ","pages":"Article 106454"},"PeriodicalIF":1.8,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143348093","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":"Characteristics of decametric hectometric (DH) type IIs, CMEs and flares of geoeffective and non-geoeffective storm events in Solar Cycle 24","authors":"Charita Pant,&nbsp;Bimal Pande,&nbsp;Seema Pande","doi":"10.1016/j.jastp.2025.106440","DOIUrl":"10.1016/j.jastp.2025.106440","url":null,"abstract":"<div><div>In this paper, a statistical study on geoeffectiveness of CMEs integrated with decametric hectometric (DH) type-II radio bursts, association of Dst with plasma and interplanetary field parameters (T,V,P, <span><math><mi>β</mi></math></span>, Bz,Bt,E) and their product function BzV for solar cycle 24 is presented. We have selected 119 DH-CME events from March 2008 to December 2015. Based on minimum Dst index <span><math><mrow><mo>≤</mo><mo>−</mo><mn>50</mn></mrow></math></span> nT of geomagnetic storm, the events are assorted into two groups, specifically (i) Geoeffective events (ii) Non-geoeffective events. The geoeffective events are found to have high start frequency, low end frequency, broad bandwidth, long duration, slower drift rate than non-geoeffective events. CME speed and flare flux for geoeffective events are moderately correlated(r=0.50) which shows that flares may be related to geomagnetic storms through CMEs. Higher speed of CMEs associated with geoeffective events suggests that CME speed is an important parameter for geoeffectiveness. A large fraction of CME associated with DH-type-II radio bursts are linked with geomagnetic storm which again indicates that CMEs accompanied by DH-type-II radio bursts are effectively responsible for producing geomagnetic storms. A good correlation of Dst with BzV(r<span><math><mrow><mo>&gt;</mo><mn>0</mn><mo>.</mo><mn>5</mn></mrow></math></span>) reflects that interplanetary field and plasma parameters also play an important role in the occurrence of geomagnetic storms.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"268 ","pages":"Article 106440"},"PeriodicalIF":1.8,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177707","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":"Assessment of the impact of WRF microphysical schemes on precipitation forecasting during spring in the Democratic People's Republic of Korea","authors":"Hyok-Chol Kim,&nbsp;Ju-Song Kim,&nbsp;Kum-Ryong Jo,&nbsp;Song-Nam Ri","doi":"10.1016/j.jastp.2025.106449","DOIUrl":"10.1016/j.jastp.2025.106449","url":null,"abstract":"<div><div>In this study, the WRF model was used to evaluate the impact of microphysics schemes on the prediction of rainfall during spring in the Democratic People's Republic of Korea (DPRK). The rainfall event was divided into two categories according to the daily accumulative rainfall amount and rainfall distribution: rainfall events with small precipitation(&lt;10 mm/d) and partial coverage of the precipitation area (hereafter SPRE) and rainfall event with relatively large precipitation(≥10 mm/d) and entirely covered area (hereafter LERE), and numerical simulations were carried out for six typical rainfall events (three days for each category) in 2021–2022. The simulation results confirmed that the effects of microphysics schemes differ from each other according to the precipitation event. In the analysis of the simulation results, the accuracy was evaluated using the critical success index (CSI) and false alarm ratio (FAR) indices for SPRE, and MODE analysis was used to assess the agreement with centers of rainfall patterns for LERE. For SPRE, the one-moment bulk microphysics scheme is rather efficient than the more sophisticated two-moment bulk microphysics scheme, and the Ferrier scheme performs best. For LERE, the two-moment bulk microphysics scheme performs better than the one-moment microphysics scheme. In particular, the Thompson and Thompson aerosol-aware schemes have a higher performance than the other schemes. The results of this study suggest that seasonal effective physical process schemes should be selected for operational forecasting, and will help to improve the accuracy of the forecast for spring in the DPRK.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"268 ","pages":"Article 106449"},"PeriodicalIF":1.8,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177696","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}