Journal of Atmospheric and Solar-Terrestrial Physics最新文献

{"title":"Automatic detection of equatorial plasma bubbles using deep neural networks","authors":"Ting Zhang ,&nbsp;Yifu Luo ,&nbsp;Bin Zhang ,&nbsp;Fang Jiang ,&nbsp;Tianfang Wang ,&nbsp;Si Xiao ,&nbsp;Xuesong Bai ,&nbsp;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":"2026-01-01","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}

{"title":"Influence of target spectrum selection in wind spectrum fitting on fatigue damage assessment accuracy for wind turbine blades","authors":"Jiantao Liu ,&nbsp;Yibing Liu ,&nbsp;Chao Zhou ,&nbsp;Qingfeng Gao ,&nbsp;Haolin Yin","doi":"10.1016/j.jastp.2025.106703","DOIUrl":"10.1016/j.jastp.2025.106703","url":null,"abstract":"<div><div>In wind turbine fatigue damage assessment, commonly used wind spectrum models often deviate from actual wind power spectral density (PSD). Directly using these spectra to generate simulated wind fields leads to deviations in fatigue assessment results. Addressing this issue, this study focuses on wind turbine blades to compare damage fatigue accuracy under different fitting target spectra. First, the integral scale parameter-related terms and denominator exponent terms in the Kaimal spectrum were designated as parameters to be fitted, proposing a three-parameter fitting model. Then, the classic periodogram-estimated spectrum of measured wind speed data was calculated, and blade damage values under the wind field generated from this spectrum were regarded as estimated actual damage values. Finally, damage assessment accuracy was compared between least squares fitted spectra using the classic periodogram-estimated spectrum as the target spectrum and those using the Welch-estimated spectrum as the target spectrum, while quantitatively comparing their improvement degrees over the Kaimal spectrum.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106703"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796868","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":"Sequence of space storm effects in ionospheric anomalies and geomagnetic activity","authors":"T.L. Gulyaeva","doi":"10.1016/j.jastp.2025.106710","DOIUrl":"10.1016/j.jastp.2025.106710","url":null,"abstract":"<div><div>Ionospheric inhomogeneities have shown asymmetry in the Arctic and Antarctic, but the extent of similar effects from pole to magnetic equator remains less investigated. Here we present a Net Volume index (NT) characterizing the deviation of the total electron content, dTEC, from the quiet reference in 6 bands of magnetic latitude, Φ: two auroral zones exceeding ±60°, two ranges in the middle latitudes between ±40° and ±60°, and two subequatorial zones from ±2.5° to ±37.5°. The NT instantaneous index is derived from the JPL GIM-TEC converted to a geomagnetic coordinate system. The observed dTEC ionospheric anomalies during three severe magnetic storms (May 11, 2024, January 1, 2025, and June 1, 2025) illustrate the diversity of NT storm profiles across six magnetic latitude ranges. The total sample of 97 intense storms was selected according to the criteria of synchronous occurrence of the merged interplanetary electric field Em ≥ 5 mW/m, geomagnetic indices Hpo ≥ 7 i.u., Apo ≥ 132 nT, Dst ≤ −100 nT and the planetary ionospheric index Wp ≥ 5 i.u. from 1995 to 2025. Superimposed epoch analysis was performed with zero epoch time, t₀ = 0, set at Apo peak, main storm phase within 24 h preceding t₀, and recovering phase within 47 h thereafter. The reference quiet TECq was selected from GIM-TEC during 24 h before the main phase, from t₀-48h to t₀-25h. Asymmetry of the ionospheric anomalies of the positive peak dTECp &gt; 0 and the negative peak dTECn &lt; 0 was observed in the Northern and Southern hemispheres in all 6 Φ zones, with the intensity gradually decreasing from pole to magnetic equator. For the first time in the literature, the intensity of the geomagnetic storm, Apo peak, is determined by ionospheric anomalies (range ΔdTEC = dTECmax – dTECmin) and the intensity of the interplanetary electric field Em during the main phase of the storm. The opposite scenario is used to estimate the intensity of the ionospheric storm, dTECp and dTECn, in six magnetic latitudinal zones depending on the peak of Apo and season (day of year) during the recovery phase.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106710"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145836667","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":"On the geospace conditions in relation to the IntelSat-33e satellite fatal failure in October 2024","authors":"Renato Gomes da Silva ,&nbsp;José Henrique Fernandez ,&nbsp;Giuliani Paulineli Garbi","doi":"10.1016/j.jastp.2025.106694","DOIUrl":"10.1016/j.jastp.2025.106694","url":null,"abstract":"<div><div>The geostationary satellite <em>IntelSat-33e</em> experienced a catastrophic failure on October 19, 2024, resulting in the generation of approximately 500 debris fragments. This study examines the satellite anomaly in light of intense space weather conditions observed in the preceding days. A multi-parameter analysis was performed using geomagnetic indices (Dst, Kp and Ap), solar wind data from the OMNI database (IMF Bz, solar wind speed, and dynamic pressure), and high-energy electron fluxes (<em>&gt;</em> 2 MeV) from GOES-16. The results indicate that spatial conditions began to change significantly after the arrival of solar wind shock fronts, evolving into a geomagnetic storm that began on October 6. A new, even more intense storm occurred on October 10. These events were driven by compound solar wind disturbances composed of coronal mass ejections followed by high-speed solar wind stream. Such combined drivers are known to enhance magnetospheric convection, substorm activity, and chorus/ULF wave generation, which in turn accelerateelectrons to relativistic energies within the outer radiation belt. This sustained high-radiation environment likely caused internal charging processes in the satellite, culminating in its fatal failure. These findings emphasize the need for real-time space weather monitoring, improved coronal mass ejections impact prediction, and resilient satellite designs for geosynchronous orbit missions.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106694"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145691515","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":"Spatiotemporal patterns of aerosol optical depth and PM2.5 concentrations derived from multi-source remote sensing","authors":"Qianjun Mao ,&nbsp;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_2.5. The results revealed that aerosol pollution in Shenzhen has been significantly improved, with AOD and PM_2.5 concentrations reduced by 12.2 % and 20 %, respectively. PM_2.5 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 PM_2.5. 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.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106689"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","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}

{"title":"Modeling daily reference evapotranspiration and evaluating uncertainty analysis in machine learning under limited meteorological data conditions for Northern India","authors":"Shaloo,&nbsp;Himani Bisht,&nbsp;Bipin Kumar,&nbsp;Jitendra Rajput,&nbsp;Pothula Srinivasa Brahmanand","doi":"10.1016/j.jastp.2025.106696","DOIUrl":"10.1016/j.jastp.2025.106696","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Reference evapotranspiration (ET&lt;sub&gt;0&lt;/sub&gt;) is essential for the management of water resources, particularly for scheduling irrigation and assessing the water needs of crops. However, accurately estimating ET&lt;sub&gt;0&lt;/sub&gt; 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&lt;sub&gt;0&lt;/sub&gt; 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&lt;sup&gt;2&lt;/sup&gt;), and Mean Absolute Percentage Error (MAPE). The results demonstrated that all models achieved accurate ET&lt;sub&gt;0&lt;/sub&gt; 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&lt;sup&gt;2&lt;/sup&gt; = 0.93–0.94). However, during testing, LSTM outperformed RF and ANN across all districts, achieving higher accuracy (R&lt;sup&gt;2&lt;/sup&gt; ≈ 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&lt;sub&gt;0&lt;/sub&gt; 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&lt;sub&gt;0&lt;/sub&gt; 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&lt;sub&gt;0&lt;/sub&gt; estimation under data-scarce conditions. The results of this research offer a dependable approach for estimating ET&lt;sub&gt;0&lt;/sub&gt; in semi-arid regions with limited data availability. These findings provide a robust approach for ET&lt;sub&gt;0&lt;/sub&gt; 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":"2026-01-01","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}

{"title":"Short-term wind speed combination prediction based on decomposition and reconstruction","authors":"Dezhi Hao","doi":"10.1016/j.jastp.2025.106705","DOIUrl":"10.1016/j.jastp.2025.106705","url":null,"abstract":"<div><div>Wind speed forecasting is a research hotspot in meteorology, which is of great importance in the fields of energy industry, environment, architecture and so on. For the power system, accurate short-term wind speed foreasting is directly related to the operation efficiency and stability of wind farms. This study designes a short-term wind speed prediction approach based on decomposition and reconstruction. Firstly, considering the non-stationary characteristics of short-term wind speed samples, the complete ensemble empirical mode decomposition with adaptive noise algorithm is used to decompose the samples, and multiple components containing different local feature information are generated, which effectively reduces the complexity of the original samples. Then, the decomposed components are input into the bidirectional long short-term memory model with attention mechanism for prediction. The introduction of attention mechanism can not only capture the long-term dependence on the historical short-term wind speed samples, but also deal with importance-based sampling and improve the prediction ability of the model. The particle swarm optimization algorithm is used to optimize the hyper-parameters of the bidirectional long short-term memory model to further reduce the prediction error. Finally, the forecasted results of these components are added to generate the expected predicted values. Two sets of public short-term wind speed datasets are served as experiment object, and a variety of evaluation indicators are adopted and compared with state-of-the-art models. The results reveal that for different two datasets, the predicted error of the designed prediction approach is smaller, and it has outbalance results than other comparision models, which verifies the foreasting accuracy of the proposed approach.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106705"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796867","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":"Climatological analysis in identification of hotspot regions of pre-monsoon convective conditions for the occurrence of disastrous thunderstorms over West Bengal","authors":"Anup Mahato,&nbsp;A.N.V. Satyanarayana","doi":"10.1016/j.jastp.2025.106700","DOIUrl":"10.1016/j.jastp.2025.106700","url":null,"abstract":"<div><div>This study investigates the climatological variations of convective parameters over West Bengal, India, during the pre-monsoon season (March–May) from 1980 to 2020 using high (0.25° × 0.25°) horizontal resolution of ECMWF reanalysis (ERA-5) and hourly time interval data. Based on the analysis of spatial patterns of inter-annual variability and spatial patterns of trends employing the Mann-Kendall test of Convective Available Potential Energy (CAPE), Convective Inhibition (CIN), CAPE/CIN ratio, and K-index, an attempt has been made to identify potential convective zones for the occurrence of disastrous thunderstorms. The climatological analysis reveals the existence of three distinct zones with unique convective potential over West Bengal. The Coastal zone-1 (21.5°N-23°N, 87°E−89°E) exhibits a consistently favourable environment for convection with high values of positive energy and instability, low convective inhibition, and low spatial variability. The Central zone-2 (23°N-26°N, 86°E−89°E) shows an inconsistent convective environment with moderate spatial patterns of inter-annual variability of CAPE and CIN. The northern zone-3 (26°N-27°N, 88°E−90°E), presents less favourable but occasional convective conditions with generally lower magnitude of CAPE and CIN with highly varying spatial patterns of inter-annual variability. The K-index is sufficient to produce a convective environment in zone-1 than in the other two zones. Accordingly, the observed disastrous thunderstorm events are in alignment with the identified zones. The overall trend shows a clear reduction in storm activity moving from zone-1 to zone-3. The analysis reveals that the number of the observed disastrous thunderstorm events has shown a sudden increase from the year 2000 onwards.</div><div>In the present study, the proposed threshold value of the CAPE/CIN ratio is a useful indicator to identify potential convective zones. The temporal trend analysis of convective parameters over West Bengal during the last four decades reveals a spatial variability of convective potential of the atmosphere. The K-index demonstrated a gradual rise, particularly in the last decade, further supporting increased atmospheric instability. This study provides an important insight into changes in the conducive nature of the convective conditions over West Bengal, susceptible to the occurrences of disastrous thunderstorm activities in the context of global warming and climate change.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106700"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145747524","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":"From drought to deluge: Understanding the atmospheric and climatic forces behind the United Arab Emirates' recent flood event","authors":"Farahnaz Fazel-Rastgar ,&nbsp;Masoud Rostami ,&nbsp;Venkataraman Sivakumar ,&nbsp;Bijan Fallah","doi":"10.1016/j.jastp.2025.106712","DOIUrl":"10.1016/j.jastp.2025.106712","url":null,"abstract":"<div><div>On April 16, 2024, Dubai and surrounding regions experienced unprecedented rainfall, with some areas receiving up to 2.5 times their average annual rainfall in just 24 h, leading to devastating floods and a tragic loss of life. This study investigates the meteorological mechanisms behind this extreme event using multiple reanalysis datasets. This work identifies the key roles played by a deep cold-core cut-off low (COL) system and an anomalous northward shift of the Intertropical Convergence Zone (ITCZ). The COL, originating from the subtropical jet over Saudi Arabia, combined with an intensified Siberian High, created a strong surface pressure gradient and facilitated the influx of moist tropical air into the region. This interaction drove instability, deep convection, and atmospheric river (AR) activity, resulting in record-breaking precipitation. Observations indicate that the COL was characterized by high potential vorticity (∼7.5 PVU), low temperatures (∼204K) at the tropopause, and enhanced stratosphere-troposphere exchange processes. Aerosol optical depth measurements suggest significant stratospheric aerosol injection, likely amplifying the cooling effect in the lower stratosphere. Due to the high potential for deep convection associated with strong updrafts, the tropospheric air was transported across the tropopause during the folding. This study highlights the coupling of tropical and mid-latitude weather systems, exacerbated by climate change, as a crucial driver of such extreme hydrometeorological events. Improved understanding of these mechanisms is vital for enhancing predictive capabilities and mitigating risks in similar arid regions. This study contributes to identifying the occurrence and dynamics of cold weather in subtropical regions, as opposed to a strong warming trend.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106712"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145879942","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":"CFD-based numerical analysis of thermal performance in solar thermal collector system with artificial roughness","authors":"Arbind Kumar Amar ,&nbsp;Dr Ajay Giri ,&nbsp;Dr Mani Kant Paswan","doi":"10.1016/j.jastp.2025.106675","DOIUrl":"10.1016/j.jastp.2025.106675","url":null,"abstract":"<div><div>In solar thermal collector systems, inefficient heat transfer between the absorber plate and flowing air leads to reduced thermal performance. This study investigates the enhancement of heat transfer by introducing artificial roughness to the collector in the form of broken arc-shaped baffles on the absorber surface. A three-dimensional numerical model Computational Fluid Dynamics (CFD) is developed using ANSYS Fluent to simulate turbulent airflow and evaluate the thermal behaviour of a modified Solar Air Heater (SAH). The performance of the roughened collector was compared against a conventional smooth-plate design under varying heat flux conditions. The study further analyzed the influence of pitch ratio at a constant roughness height on heat transfer and pressure drop. The results show a significant improvement, with the modified collector achieving a thermal efficiency of <strong>52.34 %</strong> under a 1000 W/m² heat flux, which substantially outperforms the smooth collector. These findings demonstrate the effectiveness of artificial roughness in improving natural convection and overall thermal performance, offering a viable approach for enhancing solar energy utilization.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106675"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145691509","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}