<div><div>Reference evapotranspiration (ET<sub>0</sub>) is essential for the management of water resources, particularly for scheduling irrigation and assessing the water needs of crops. However, accurately estimating ET<sub>0</sub> is often difficult in economically developing nations due to insufficient availability of climatic data and the reliance on restricted datasets. This research assessed the effectiveness of three machine learning (ML) models—Random Forest (RF), Artificial Neural Networks (ANN), and Long Short-Term Memory (LSTM)—in predicting ET<sub>0</sub> employing various input parameters groupings. The study utilized 38 years of meteorological data obtained from the IMD for three districts in Haryana, incorporating inputs such as maximum and minimum temperatures (Tmax, Tmin), relative humidity (RH), wind speed (WS), and solar radiation (SR), with ETo-FAO-56-PM values serving as the target outputs. The performance of the models was evaluated using statistical metrics, including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), coefficient of determination (R<sup>2</sup>), and Mean Absolute Percentage Error (MAPE). The results demonstrated that all models achieved accurate ET<sub>0</sub> predictions, with the full dataset identified as the optimal input combination. For limited datasets, combinations including temperature, wind speed, and solar radiation were found to be the most effective. In cases of minimal dataset using only temperature data (Tmax, Tmin), RF yielded the best performance during the training phase (R<sup>2</sup> = 0.93–0.94). However, during testing, LSTM outperformed RF and ANN across all districts, achieving higher accuracy (R<sup>2</sup> ≈ 0.77) and lower errors (MAPE ≈ 17–18 %). Additionally, an uncertainty analysis was conducted to assess the robustness of the models using a Monte Carlo-based approach. The results indicated that LSTM captured extreme ET<sub>0</sub> values with broader confidence intervals, reflecting higher sensitivity but lower prediction uncertainties overall, whereas ANN produced tighter intervals with lower variability, and RF offered a balanced performance between accuracy and uncertainty. These findings confirm that LSTM is the most reliable model for ET<sub>0</sub> estimation under data-scarce conditions. The temperature based Hargreave-Samani model outperformed the radiation based Priestely-Taylor model in estimation of ET0. The analysis revealed that the LSTM model exhibited lower prediction uncertainties compared to RF and ANN, further highlighting its reliability for ET<sub>0</sub> estimation under data-scarce conditions. The results of this research offer a dependable approach for estimating ET<sub>0</sub> in semi-arid regions with limited data availability. These findings provide a robust approach for ET<sub>0</sub> estimation in semi-arid regions, offering practical guidance for efficient water management and supporting climate-resilient agricult
{"title":"Modeling daily reference evapotranspiration and evaluating uncertainty analysis in machine learning under limited meteorological data conditions for Northern India","authors":"Shaloo, Himani Bisht, Bipin Kumar, Jitendra Rajput, Pothula Srinivasa Brahmanand","doi":"10.1016/j.jastp.2025.106696","DOIUrl":"10.1016/j.jastp.2025.106696","url":null,"abstract":"<div><div>Reference evapotranspiration (ET<sub>0</sub>) is essential for the management of water resources, particularly for scheduling irrigation and assessing the water needs of crops. However, accurately estimating ET<sub>0</sub> is often difficult in economically developing nations due to insufficient availability of climatic data and the reliance on restricted datasets. This research assessed the effectiveness of three machine learning (ML) models—Random Forest (RF), Artificial Neural Networks (ANN), and Long Short-Term Memory (LSTM)—in predicting ET<sub>0</sub> employing various input parameters groupings. The study utilized 38 years of meteorological data obtained from the IMD for three districts in Haryana, incorporating inputs such as maximum and minimum temperatures (Tmax, Tmin), relative humidity (RH), wind speed (WS), and solar radiation (SR), with ETo-FAO-56-PM values serving as the target outputs. The performance of the models was evaluated using statistical metrics, including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), coefficient of determination (R<sup>2</sup>), and Mean Absolute Percentage Error (MAPE). The results demonstrated that all models achieved accurate ET<sub>0</sub> predictions, with the full dataset identified as the optimal input combination. For limited datasets, combinations including temperature, wind speed, and solar radiation were found to be the most effective. In cases of minimal dataset using only temperature data (Tmax, Tmin), RF yielded the best performance during the training phase (R<sup>2</sup> = 0.93–0.94). However, during testing, LSTM outperformed RF and ANN across all districts, achieving higher accuracy (R<sup>2</sup> ≈ 0.77) and lower errors (MAPE ≈ 17–18 %). Additionally, an uncertainty analysis was conducted to assess the robustness of the models using a Monte Carlo-based approach. The results indicated that LSTM captured extreme ET<sub>0</sub> values with broader confidence intervals, reflecting higher sensitivity but lower prediction uncertainties overall, whereas ANN produced tighter intervals with lower variability, and RF offered a balanced performance between accuracy and uncertainty. These findings confirm that LSTM is the most reliable model for ET<sub>0</sub> estimation under data-scarce conditions. The temperature based Hargreave-Samani model outperformed the radiation based Priestely-Taylor model in estimation of ET0. The analysis revealed that the LSTM model exhibited lower prediction uncertainties compared to RF and ANN, further highlighting its reliability for ET<sub>0</sub> estimation under data-scarce conditions. The results of this research offer a dependable approach for estimating ET<sub>0</sub> in semi-arid regions with limited data availability. These findings provide a robust approach for ET<sub>0</sub> estimation in semi-arid regions, offering practical guidance for efficient water management and supporting climate-resilient agricult","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106696"},"PeriodicalIF":1.9,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145691517","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}
This study presents a reconstruction scheme aimed at enhancing the accuracy of initial conditions (ICs) and lateral boundary conditions (LBCs) within the convective-allowing ensemble forecast system (CAEFS). Initially, we assessed the impact of ICs and LBCs on CAEFS, highlighting how their perturbations predominantly influence the uncertainty in short- and long-range forecasts. Subsequently, methods for reconstructing ICs and LBCs in CAEFS were developed. This process involved refining the initial conditions (ICs) and lateral boundary conditions (LBCs) - originally derived from downscaling a coarse-resolution global ensemble forecast system (GEFS) - through assimilation of high-quality global deterministic forecasts. To address changes in uncertainty characteristics after reconstruction, we implemented a scheme for adjusting perturbation amplitudes in ICs and LBCs. Our findings indicate the following: Due to limitations in GEFS quality, the downscaling approach exhibited significant forecast errors and overspread. The reconstruction scheme improved CAEFS forecast accuracy; however, overspread persisted due to large-scale perturbation amplitudes from global ensemble. Combining reconstruction with perturbation amplitude adjustment not only enhanced the accuracy of control forecast but also effectively mitigated overspread issues in CAEFS. Furthermore, this approach retained small-scale uncertainty information, thereby sharpening focus on small-scale forecasting uncertainty and improving CAEFS reliability.
{"title":"Study on the reconstruction of initial and lateral boundary conditions for a convective-allowing ensemble forecast system","authors":"Yu Xia , Hanbin Zhang , Xin Liu , Shuting Zhang , Xiang-Yu Huang","doi":"10.1016/j.jastp.2025.106697","DOIUrl":"10.1016/j.jastp.2025.106697","url":null,"abstract":"<div><div>This study presents a reconstruction scheme aimed at enhancing the accuracy of initial conditions (ICs) and lateral boundary conditions (LBCs) within the convective-allowing ensemble forecast system (CAEFS). Initially, we assessed the impact of ICs and LBCs on CAEFS, highlighting how their perturbations predominantly influence the uncertainty in short- and long-range forecasts. Subsequently, methods for reconstructing ICs and LBCs in CAEFS were developed. This process involved refining the initial conditions (ICs) and lateral boundary conditions (LBCs) - originally derived from downscaling a coarse-resolution global ensemble forecast system (GEFS) - through assimilation of high-quality global deterministic forecasts. To address changes in uncertainty characteristics after reconstruction, we implemented a scheme for adjusting perturbation amplitudes in ICs and LBCs. Our findings indicate the following: Due to limitations in GEFS quality, the downscaling approach exhibited significant forecast errors and overspread. The reconstruction scheme improved CAEFS forecast accuracy; however, overspread persisted due to large-scale perturbation amplitudes from global ensemble. Combining reconstruction with perturbation amplitude adjustment not only enhanced the accuracy of control forecast but also effectively mitigated overspread issues in CAEFS. Furthermore, this approach retained small-scale uncertainty information, thereby sharpening focus on small-scale forecasting uncertainty and improving CAEFS reliability.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106697"},"PeriodicalIF":1.9,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145691514","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}
Pub Date : 2025-11-25DOI: 10.1016/j.jastp.2025.106689
Qianjun Mao , Shuangshuang Liu
To evaluate the impact of carbon neutrality strategies on the atmospheric environment in megacities, this study took Shenzhen as a case study. Multi-source satellite remote sensing, ground-based observations, and surface monitoring data (2015–2024) were integrated to systematically analyze air quality trends and the driving mechanisms of PM2.5. The results revealed that aerosol pollution in Shenzhen has been significantly improved, with AOD and PM2.5 concentrations reduced by 12.2 % and 20 %, respectively. PM2.5 levels were found to be highly sensitive to local emission sources such as traffic and industry, exhibiting a pronounced weekly cycle with a 28.6 % decrease on weekends. Multiple regression analysis further identified SO2, OC, and NO2 as the most significant drivers of PM2.5. This study confirms that Shenzhen has effectively curbed aerosol pollution through energy structure optimization and emission control measures. Future efforts should focus on addressing the rising O3 pollution and enhancing coordinated emission reductions of key precursors. These findings provide a scientific framework for low-carbon development and targeted pollution control in rapidly urbanizing regions.
{"title":"Spatiotemporal patterns of aerosol optical depth and PM2.5 concentrations derived from multi-source remote sensing","authors":"Qianjun Mao , Shuangshuang Liu","doi":"10.1016/j.jastp.2025.106689","DOIUrl":"10.1016/j.jastp.2025.106689","url":null,"abstract":"<div><div>To evaluate the impact of carbon neutrality strategies on the atmospheric environment in megacities, this study took Shenzhen as a case study. Multi-source satellite remote sensing, ground-based observations, and surface monitoring data (2015–2024) were integrated to systematically analyze air quality trends and the driving mechanisms of PM<sub>2.5</sub>. The results revealed that aerosol pollution in Shenzhen has been significantly improved, with AOD and PM<sub>2.5</sub> concentrations reduced by 12.2 % and 20 %, respectively. PM<sub>2.5</sub> levels were found to be highly sensitive to local emission sources such as traffic and industry, exhibiting a pronounced weekly cycle with a 28.6 % decrease on weekends. Multiple regression analysis further identified SO<sub>2</sub>, OC, and NO<sub>2</sub> as the most significant drivers of PM<sub>2.5</sub>. This study confirms that Shenzhen has effectively curbed aerosol pollution through energy structure optimization and emission control measures. Future efforts should focus on addressing the rising O<sub>3</sub> pollution and enhancing coordinated emission reductions of key precursors. These findings provide a scientific framework for low-carbon development and targeted pollution control in rapidly urbanizing regions.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106689"},"PeriodicalIF":1.9,"publicationDate":"2025-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145621936","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}
Pub Date : 2025-11-22DOI: 10.1016/j.jastp.2025.106690
G. Hubert , G. Herbert , A. Tilhac , R. Rey , B. Bourlès
This paper presents the operation of a neutron spectrometer onboard the R/V La Thalassa during the PIRATA (Prediction and Research Moored Array in the Tropical Atlantic) oceanographic cruises in the equatorial Atlantic. The cruises took place from February to April in 2019 and 2020. We analyze cosmic ray-induced neutrons measured by the spectrometer, accounting for various physical factors influencing neutron detection, including environmental and systematic effects primarily driven by atmospheric pressure and water vapor content variations. Additionally, the study incorporates the influence of short-term fluctuations in primary cosmic rays to investigate the geomagnetic cutoff rigidity dependence. Detailed analyses of count rates, fluxes, and neutron spectra are provided, facilitating cross-comparison of radiation fields. The mobile neutron spectrometer enables latitude-dependent surveys, assessing the impact of geomagnetic cutoff rigidity on neutron spectra. Equivalent 3-NM64 count rates were derived from PIRATA measurements and compared with previous results.
本文介绍了R/V La Thalassa号在赤道大西洋PIRATA（热带大西洋预测与研究系泊阵列）海洋巡航中中子星光谱仪的工作情况。这些游轮分别于2019年和2020年的2月至4月举行。我们分析了由光谱仪测量的宇宙射线诱导中子，考虑了影响中子探测的各种物理因素，包括主要由大气压力和水蒸气含量变化驱动的环境和系统效应。此外，该研究还纳入了初级宇宙射线短期波动的影响，以研究地磁截止刚度的依赖性。提供了计数率、通量和中子谱的详细分析，便于辐射场的交叉比较。移动中子星能谱仪可以进行纬度相关的测量，评估地磁截止刚度对中子能谱的影响。等效的3-NM64计数率由PIRATA测量得出，并与先前的结果进行比较。
{"title":"Analysis of cosmic ray-induced neutron spectra recorded during PIRATA oceanographic cruises","authors":"G. Hubert , G. Herbert , A. Tilhac , R. Rey , B. Bourlès","doi":"10.1016/j.jastp.2025.106690","DOIUrl":"10.1016/j.jastp.2025.106690","url":null,"abstract":"<div><div>This paper presents the operation of a neutron spectrometer onboard the R/V La Thalassa during the PIRATA (Prediction and Research Moored Array in the Tropical Atlantic) oceanographic cruises in the equatorial Atlantic. The cruises took place from February to April in 2019 and 2020. We analyze cosmic ray-induced neutrons measured by the spectrometer, accounting for various physical factors influencing neutron detection, including environmental and systematic effects primarily driven by atmospheric pressure and water vapor content variations. Additionally, the study incorporates the influence of short-term fluctuations in primary cosmic rays to investigate the geomagnetic cutoff rigidity dependence. Detailed analyses of count rates, fluxes, and neutron spectra are provided, facilitating cross-comparison of radiation fields. The mobile neutron spectrometer enables latitude-dependent surveys, assessing the impact of geomagnetic cutoff rigidity on neutron spectra. Equivalent 3-NM64 count rates were derived from PIRATA measurements and compared with previous results.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106690"},"PeriodicalIF":1.9,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145621946","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}
Pub Date : 2025-11-21DOI: 10.1016/j.jastp.2025.106688
Özlem Hacıoğlu , Elif Çiftçi , Burak Kotan
The Gannon geomagnetic superstorm of May 2024, classified as a G5-level event, significantly disturbed Earth's magnetosphere and ionosphere. This study examines storm-time ionospheric responses over Europe by integrating Global Navigation Satellite System-derived Total Electron Content (GNSS-derived TEC) parameters (vTEC, ΔTEC, and rTEC) with ground-based geomagnetic field observations, while also considering equatorial features such as the equatorial ionization anomaly (EIA). TEC data from the Centre for Orbit Determination in Europe (CODE) revealed substantial ionospheric restructuring with clear diurnal and latitudinal variability. During the main phase, the nighttime EIA exhibited hemispheric asymmetries, with partial suppression over the African and Atlantic sectors, driven by prompt penetration electric fields (PPEFs) arising from enhanced solar wind–magnetosphere coupling shortly after the storm sudden commencement (SSC) on 10 May. These fields contributed to concurrent TEC reductions of −20 to −25 TECu over Europe. In the early recovery phase, plasma suppression became evident, primarily driven by disturbance dynamo electric fields (DDEFs) and thermospheric composition changes. Daytime TEC depletions exceeding −35 TECu (rTEC < −0.8) persisted for over 18 h between 30°N and 50°N, confirming one of the most prolonged negative phases reported at European mid-latitudes. Perturbations in horizontal (H) and vertical (Z) magnetic field components further supported the role of intensified ring current activity and large-scale field-aligned currents (FACs). These findings highlight the dominant electrodynamic drivers, with contributions from thermospheric processes, and underscore the importance of space weather impacts for modern technological systems.
{"title":"European ionospheric response to the May 2024 Gannon geomagnetic storm","authors":"Özlem Hacıoğlu , Elif Çiftçi , Burak Kotan","doi":"10.1016/j.jastp.2025.106688","DOIUrl":"10.1016/j.jastp.2025.106688","url":null,"abstract":"<div><div>The Gannon geomagnetic superstorm of May 2024, classified as a G5-level event, significantly disturbed Earth's magnetosphere and ionosphere. This study examines storm-time ionospheric responses over Europe by integrating Global Navigation Satellite System-derived Total Electron Content (GNSS-derived TEC) parameters (vTEC, ΔTEC, and rTEC) with ground-based geomagnetic field observations, while also considering equatorial features such as the equatorial ionization anomaly (EIA). TEC data from the Centre for Orbit Determination in Europe (CODE) revealed substantial ionospheric restructuring with clear diurnal and latitudinal variability. During the main phase, the nighttime EIA exhibited hemispheric asymmetries, with partial suppression over the African and Atlantic sectors, driven by prompt penetration electric fields (PPEFs) arising from enhanced solar wind–magnetosphere coupling shortly after the storm sudden commencement (SSC) on 10 May. These fields contributed to concurrent TEC reductions of −20 to −25 TECu over Europe. In the early recovery phase, plasma suppression became evident, primarily driven by disturbance dynamo electric fields (DDEFs) and thermospheric composition changes. Daytime TEC depletions exceeding −35 TECu (rTEC < −0.8) persisted for over 18 h between 30°N and 50°N, confirming one of the most prolonged negative phases reported at European mid-latitudes. Perturbations in horizontal (H) and vertical (Z) magnetic field components further supported the role of intensified ring current activity and large-scale field-aligned currents (FACs). These findings highlight the dominant electrodynamic drivers, with contributions from thermospheric processes, and underscore the importance of space weather impacts for modern technological systems.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106688"},"PeriodicalIF":1.9,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145621945","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}
Pub Date : 2025-11-20DOI: 10.1016/j.jastp.2025.106687
Ting Zhang , Yifu Luo , Bin Zhang , Fang Jiang , Tianfang Wang , Si Xiao , Xuesong Bai , Liping Fu
The equatorial plasma bubble (EPB) is one of the most important phenomena in the Earth's ionosphere. In this paper, we propose a method for the EPB image data processing and automatic labeling, utilizing the Global-scale Observations of the Limb and Disk (GOLD) 135.6 nm nightglow data. The method extracts the central position of EPBs, significantly reducing the workload of manual labeling. Through manual analysis, a dataset of 1,380 image samples was established. Based on the unique features of EPB images, a deep learning model was developed to improve detection accuracy. After optimization and validation, the YOLO-LessHead model achieved a mean Average Precision ([email protected]) of 78.39 %, enabling automatic and accurate identification of EPB images. We used the developed model to identify and statistically analyze the GOLD airglow image data from October 2018 to December 2024. The results indicate that EPB occurrence rates show strong seasonal and longitudinal variability, with distinct seasonal patterns across different longitudes. The zonal drift velocities of EPBs increase with enhanced solar radio flux (F10.7) and decrease as geomagnetic activity (Ap index) intensifies. Drift speeds are generally higher and more variable at the magnetic equator, while the northern and southern EIA regions exhibit similar values and trends.
赤道等离子体泡是地球电离层中最重要的现象之一。本文提出了一种利用GOLD (Global-scale Observations of the Limb and Disk) 135.6 nm夜光数据对EPB图像数据进行处理和自动标记的方法。该方法提取epb的中心位置，大大减少了人工标记的工作量。通过人工分析，建立了1380个图像样本的数据集。基于EPB图像的独特特征，开发了一种深度学习模型来提高检测精度。经过优化和验证，YOLO-LessHead模型的平均平均精度（[email protected]）达到78.39%，实现了EPB图像的自动准确识别。利用该模型对2018年10月至2024年12月的GOLD气辉图像数据进行识别和统计分析。结果表明，EPB的发生具有较强的季节和纵向变异性，在不同的经度上具有明显的季节特征。epb的纬向漂移速度随太阳射电通量（F10.7）的增强而增大，随地磁活动（Ap指数）的增强而减小。在磁赤道，漂移速度一般较高，变化更大，而北部和南部的EIA区域表现出相似的值和趋势。
{"title":"Automatic detection of equatorial plasma bubbles using deep neural networks","authors":"Ting Zhang , Yifu Luo , Bin Zhang , Fang Jiang , Tianfang Wang , Si Xiao , Xuesong Bai , Liping Fu","doi":"10.1016/j.jastp.2025.106687","DOIUrl":"10.1016/j.jastp.2025.106687","url":null,"abstract":"<div><div>The equatorial plasma bubble (EPB) is one of the most important phenomena in the Earth's ionosphere. In this paper, we propose a method for the EPB image data processing and automatic labeling, utilizing the Global-scale Observations of the Limb and Disk (GOLD) 135.6 nm nightglow data. The method extracts the central position of EPBs, significantly reducing the workload of manual labeling. Through manual analysis, a dataset of 1,380 image samples was established. Based on the unique features of EPB images, a deep learning model was developed to improve detection accuracy. After optimization and validation, the YOLO-LessHead model achieved a mean Average Precision ([email protected]) of 78.39 %, enabling automatic and accurate identification of EPB images. We used the developed model to identify and statistically analyze the GOLD airglow image data from October 2018 to December 2024. The results indicate that EPB occurrence rates show strong seasonal and longitudinal variability, with distinct seasonal patterns across different longitudes. The zonal drift velocities of EPBs increase with enhanced solar radio flux (F10.7) and decrease as geomagnetic activity (Ap index) intensifies. Drift speeds are generally higher and more variable at the magnetic equator, while the northern and southern EIA regions exhibit similar values and trends.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106687"},"PeriodicalIF":1.9,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145621947","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}
Cloud-to-ground lightning is recognized as a major weather hazard in India, with mortality and losses persisting. A reproducible lightning-risk framework for India is developed and demonstrated for the peninsular state of Andhra Pradesh, using lightning-occurrence data together with topography from CartoDEM, land cover from NRSC's LULC, and socio-economic and infrastructure indicators derived from SECC-2011 and OpenStreetMap. Guided by the UNDRR hazard–exposure–vulnerability concept and FEMA's National Risk Index factorization, the study combines a Lightning Hazard Index (LHI) and a six-factor Lightning Vulnerability Index (LVI) to generate seasonal Lightning Risk Index (LRI) maps. Hazard mapping reveals a monsoon concentration along the north-coastal corridor, a post-monsoon southward shift, and minimal winter risk, while vulnerability peaks along the urban–industrial chain and within the Krishna–Godavari deltas. These season-resolved, decision-ready LRI maps are expected to be highly useful for targeted lightning protection, early-warning placement, and community preparedness. The proposed framework offers a transferable model for lightning risk mapping across India, supporting climate-aware disaster mitigation strategies.
{"title":"Framework for the lightning risk assessment over India – a case study over a peninsular state","authors":"Nambi Manavalan Rajan , Alok Taori , Degala Venkatesh , M. Mallikarjun , Sameer Saran , Rajiv Kumar , Dhiroj Kumar Behra , Goru Srinivasa Rao , Prakash Chauhan","doi":"10.1016/j.jastp.2025.106680","DOIUrl":"10.1016/j.jastp.2025.106680","url":null,"abstract":"<div><div>Cloud-to-ground lightning is recognized as a major weather hazard in India, with mortality and losses persisting. A reproducible lightning-risk framework for India is developed and demonstrated for the peninsular state of Andhra Pradesh, using lightning-occurrence data together with topography from CartoDEM, land cover from NRSC's LULC, and socio-economic and infrastructure indicators derived from SECC-2011 and OpenStreetMap. Guided by the UNDRR hazard–exposure–vulnerability concept and FEMA's National Risk Index factorization, the study combines a Lightning Hazard Index (LHI) and a six-factor Lightning Vulnerability Index (LVI) to generate seasonal Lightning Risk Index (LRI) maps. Hazard mapping reveals a monsoon concentration along the north-coastal corridor, a post-monsoon southward shift, and minimal winter risk, while vulnerability peaks along the urban–industrial chain and within the Krishna–Godavari deltas. These season-resolved, decision-ready LRI maps are expected to be highly useful for targeted lightning protection, early-warning placement, and community preparedness. The proposed framework offers a transferable model for lightning risk mapping across India, supporting climate-aware disaster mitigation strategies.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"277 ","pages":"Article 106680"},"PeriodicalIF":1.9,"publicationDate":"2025-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568234","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}
Pub Date : 2025-11-15DOI: 10.1016/j.jastp.2025.106678
Costas A. Varotsos , Ferdenant A. Mkrtchyan , Vladimir Yu. Soldatov
In honor of the 75th anniversary of the JASTP, which was founded by Edward Victor Appleton whose work greatly advanced the field of ionospheric science, we present a summary of our research on forecasting and monitoring tropical cyclones. Over the past three decades, radio occultation techniques have greatly improved our ability to monitor the Earth by employing satellite technology to accurately detect atmospheric and ionospheric qualities through novel calculations and approaches. Radio occultation advances our understanding of atmospheric dynamics and is highly accurate compared to terrestrial monitoring. This emphasizes its importance in contemporary meteorological and environmental research. While radio occultation holds potential for improving climate predictions, its shortcomings in accurately tackling tropical cyclogenesis highlight the demand for advanced algorithms and integrated data analysis. The study suggests that remote sensing technologies, particularly microwave surveillance, greatly enhance our understanding of sea-atmosphere system instability and enable timely tropical cyclone detection. By offering crucial measurements of heat fluxes and the vertical distribution of atmospheric gases, this approach advances cyclone prediction and addresses major scientific challenges in meteorology. The analysis showed that from 1995 to 2023, hurricanes in the North Atlantic (0°–20° N, 30°–70° W) mainly formed near tectonic faults, following a week of increased sensible and latent heat fluxes. Also, key calculations are included, and the determination of four Stock's coefficients is explored. These are vital for identifying cloud and rain formation as signs of tropical cyclone development. Finally, it proposes a global monitoring system using radio occultation to enhance cyclone forecasting.
由Edward Victor Appleton创立的JASTP成立75周年，他的工作极大地推动了电离层科学领域的发展，我们在此对我们在热带气旋预报和监测方面的研究进行总结。在过去的三十年里，无线电掩星技术极大地提高了我们监测地球的能力，通过新颖的计算和方法，利用卫星技术精确地探测大气和电离层的质量。无线电掩星提高了我们对大气动力学的理解，与地面监测相比，它非常精确。这强调了它在当代气象和环境研究中的重要性。虽然无线电掩星具有改善气候预测的潜力，但它在准确处理热带气旋形成方面的缺点突出了对先进算法和综合数据分析的需求。该研究表明，遥感技术，特别是微波监测，极大地提高了我们对海-气系统不稳定性的认识，并使及时探测热带气旋成为可能。通过提供热通量和大气气体垂直分布的关键测量，这种方法促进了气旋预测，并解决了气象学中的重大科学挑战。分析表明，1995 - 2023年，北大西洋（0°-20°N, 30°-70°W）的飓风主要形成于构造断裂附近，其后一周感热通量和潜热通量增加。此外，还包括关键计算，并探讨了四个股票系数的确定。这些对于识别云和雨的形成作为热带气旋发展的迹象至关重要。最后，提出了一种利用无线电掩星的全球监测系统，以加强气旋预报。
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Pub Date : 2025-11-14DOI: 10.1016/j.jastp.2025.106677
Congzhen Zhu, Mingzhong Wang, Lu Meng, Ali Mamtimin, Fan Yang, Chenlong Zhou, Honglin Pan, Jiantao Zhang
The long-term evolution of the boundary layer height (BLH) and dust concentration (DC) in the Tarim Basin, particularly their interactions under varying meteorological conditions, remains inadequately characterized. Leveraging decadal observations (2014–2023) and multi-source reanalysis data, this study systematically evaluated BLH and DC products in this hyper-arid region. We established quantitative BLH-DC relationships across meteorological conditions, revealing novel insights into ABL-Dust interactions in extreme environments. ERA5 reanalysis effectively captured BLH diurnal cycles but exhibited minor deficiencies in nocturnal BLH representation within desert interiors. EAC4 data broadly reproduced DC trends despite slight observational deviations. Seasonal patterns revealed that the BLH increased in spring, remained elevated throughout summer, and declined in autumn; the DC increased in spring, peaked in June, and gradually decreased thereafter. Spatially, the DC substantially exceeded the annual average in spring, particularly in the southern region. The BLH and DC exhibited pronounced diurnal variability, with the strongest negative correlation (−0.42) in the afternoon and a positive correlation (0.64) during the pre-sunrise hours. Daytime BLH elevation enhances turbulent diffusion and raises dispersion height, reducing DC, whereas shallow BLH during dust storms promotes near-surface DC accumulation. At night, BLH-driven dispersion changes do not govern DC; instead, dust-radiation warming destabilizes the nocturnal boundary layer, intensifying turbulence, wind, and emission—creating a positive feedback that increases both BLH and DC. This work advances understanding of complex ABL-Dust interactions in hyperarid environments.
{"title":"Correlation between atmospheric boundary layer height and Concentration of dust aerosols in Taklimakan desert","authors":"Congzhen Zhu, Mingzhong Wang, Lu Meng, Ali Mamtimin, Fan Yang, Chenlong Zhou, Honglin Pan, Jiantao Zhang","doi":"10.1016/j.jastp.2025.106677","DOIUrl":"10.1016/j.jastp.2025.106677","url":null,"abstract":"<div><div>The long-term evolution of the boundary layer height (BLH) and dust concentration (DC) in the Tarim Basin, particularly their interactions under varying meteorological conditions, remains inadequately characterized. Leveraging decadal observations (2014–2023) and multi-source reanalysis data, this study systematically evaluated BLH and DC products in this hyper-arid region. We established quantitative BLH-DC relationships across meteorological conditions, revealing novel insights into ABL-Dust interactions in extreme environments. ERA5 reanalysis effectively captured BLH diurnal cycles but exhibited minor deficiencies in nocturnal BLH representation within desert interiors. EAC4 data broadly reproduced DC trends despite slight observational deviations. Seasonal patterns revealed that the BLH increased in spring, remained elevated throughout summer, and declined in autumn; the DC increased in spring, peaked in June, and gradually decreased thereafter. Spatially, the DC substantially exceeded the annual average in spring, particularly in the southern region. The BLH and DC exhibited pronounced diurnal variability, with the strongest negative correlation (−0.42) in the afternoon and a positive correlation (0.64) during the pre-sunrise hours. Daytime BLH elevation enhances turbulent diffusion and raises dispersion height, reducing DC, whereas shallow BLH during dust storms promotes near-surface DC accumulation. At night, BLH-driven dispersion changes do not govern DC; instead, dust-radiation warming destabilizes the nocturnal boundary layer, intensifying turbulence, wind, and emission—creating a positive feedback that increases both BLH and DC. This work advances understanding of complex ABL-Dust interactions in hyperarid environments.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"277 ","pages":"Article 106677"},"PeriodicalIF":1.9,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568235","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}
Pub Date : 2025-11-13DOI: 10.1016/j.jastp.2025.106676
Yuxing Wang , Junyu Li , Yibin Yao , Lilong Liu , Bao Zhang , Liangke Huang , Zhangyu Sun , Mingyun Hu
Precipitable Water Vapor (PWV) is a crucial parameter in meteorological studies. The vertical correction of PWV is always applied to tomographic vertical constraints and the fusion of PWV multi-source data. Thus, it significantly influences the accuracy of the latters. The current vertical correction models for PWV do not account for the hourly changes in the PWV lapse rate (β). This research first investigates the hourly variation characteristics of β within a day using the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis (ERA5) monthly average hourly pressure level grid data (1° × 1°). Subsequently, the seasonal variation in the hourly β from 2008 to 2017 is examined using ERA5 data. Based on these analyses, the seasonal variation coefficient for each hourly β is determined through a trigonometric function. An empirical model for PWV vertical correction (H-PWV), which considers the hourly variations in β and features a spatiotemporal resolution of 1° × 1° and 1 h, is then developed. This model notably captures the hourly variations in β, a capability not previously achieved. When tested with 1 h ERA5 PWV profiles from 2018, the MAE, STD, and RMSE of H-PWV are found to be 1.00 mm, 0.96 mm, and 1.25 mm, respectively. Compared to the commonly used exponential model (E-PWV) and the latest model available to the public (C-PWVC1), the MAE, STD, and RMSE improved by 28.57 %, 21.95 %, and 30.56 % and 42.53 %, 18.65 %, and 39.02 %, respectively. Validation with radiosonde data shows that the MAE, STD, and RMSE of H-PWV are 1.00 mm, 1.29 mm, and 0.93 mm, respectively, marking a notable enhancement over the E-PWV and C-PWVC1 models. Moreover, in scenarios involving complex PWV variations and significant elevation differences, H-PWV demonstrates a clear advantage, with decreased differences across spatial and temporal domains. The results confirm that H-PWV provides the most effective vertical correction and highest accuracy among the models studied. H-PWV is anticipated to enhance the vertical correction of PWV and contribute to Atmospheric research.
{"title":"An empirical model for the vertical correction of precipitable water vapor (PWV) over the Chinese mainland and surrounding areas considering hourly variations in the PWV lapse rate","authors":"Yuxing Wang , Junyu Li , Yibin Yao , Lilong Liu , Bao Zhang , Liangke Huang , Zhangyu Sun , Mingyun Hu","doi":"10.1016/j.jastp.2025.106676","DOIUrl":"10.1016/j.jastp.2025.106676","url":null,"abstract":"<div><div>Precipitable Water Vapor (PWV) is a crucial parameter in meteorological studies. The vertical correction of PWV is always applied to tomographic vertical constraints and the fusion of PWV multi-source data. Thus, it significantly influences the accuracy of the latters. The current vertical correction models for PWV do not account for the hourly changes in the PWV lapse rate (β). This research first investigates the hourly variation characteristics of β within a day using the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis (ERA5) monthly average hourly pressure level grid data (1° × 1°). Subsequently, the seasonal variation in the hourly β from 2008 to 2017 is examined using ERA5 data. Based on these analyses, the seasonal variation coefficient for each hourly β is determined through a trigonometric function. An empirical model for PWV vertical correction (H-PWV), which considers the hourly variations in β and features a spatiotemporal resolution of 1° × 1° and 1 h, is then developed. This model notably captures the hourly variations in β, a capability not previously achieved. When tested with 1 h ERA5 PWV profiles from 2018, the MAE, STD, and RMSE of H-PWV are found to be 1.00 mm, 0.96 mm, and 1.25 mm, respectively. Compared to the commonly used exponential model (E-PWV) and the latest model available to the public (C-PWVC1), the MAE, STD, and RMSE improved by 28.57 %, 21.95 %, and 30.56 % and 42.53 %, 18.65 %, and 39.02 %, respectively. Validation with radiosonde data shows that the MAE, STD, and RMSE of H-PWV are 1.00 mm, 1.29 mm, and 0.93 mm, respectively, marking a notable enhancement over the E-PWV and C-PWVC1 models. Moreover, in scenarios involving complex PWV variations and significant elevation differences, H-PWV demonstrates a clear advantage, with decreased differences across spatial and temporal domains. The results confirm that H-PWV provides the most effective vertical correction and highest accuracy among the models studied. H-PWV is anticipated to enhance the vertical correction of PWV and contribute to Atmospheric research.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106676"},"PeriodicalIF":1.9,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145546867","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}
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