pure and applied geophysics最新文献

{"title":"A Robust Hybrid Deep Learning Model for GHI Forecasting Incorporating EEMD, CSA Optimization, and Transformer–GRU Networks","authors":"Girijapati Sharma,&nbsp;Subhash Chandra,&nbsp;Arvind Kumar Yadav","doi":"10.1007/s00024-026-04054-4","DOIUrl":"10.1007/s00024-026-04054-4","url":null,"abstract":"<div><p>Solar energy is a sustainable and environmentally friendly energy source; however, its intermittent and highly dynamic nature makes accurate Global Horizontal Irradiance (GHI) forecasting a challenging task. Reliable GHI prediction is crucial for efficient photovoltaic power generation, grid stability, and renewable energy integration. To address this challenge, this study proposes a hybrid EEMD-CSA-VTX-GRU forecasting framework that combines Ensemble Empirical Mode Decomposition (EEMD), Cuckoo Search Algorithm (CSA)-based hyperparameter optimization, and a Transformer-enhanced Gated Recurrent Unit (VTX-GRU) model for solar irradiance prediction. The EEMD technique is employed to decompose nonlinear and non-stationary irradiance signals into intrinsic mode functions, improving feature representation and reducing noise effects. The Transformer module captures long-range temporal dependencies using an attention mechanism, while the GRU network effectively models short-term sequential patterns. Furthermore, CSA is utilized to optimize model hyperparameters, enhancing convergence stability and forecasting accuracy. The proposed framework was evaluated using the Jodhpur solar irradiance dataset under different forecasting scenarios. Its performance was compared with conventional GRU and other benchmark models using RMSE, MAE, nRMSE, MAPE, and R² metrics. Experimental results demonstrated superior forecasting performance, achieving an MAE of 31.48, RMSE of 46.64, nRMSE of 0.0442, and MAPE of 10.56%. Sensitivity and statistical analyses further confirmed the robustness and stability of the proposed model across varying training configurations and forecasting horizons. Although the framework was validated on a single geographical region, the results indicate its effectiveness for short-term solar irradiance forecasting. Future work will focus on multi-regional validation, lightweight optimization strategies, and improved forecasting robustness under highly dynamic atmospheric conditions.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"183 9","pages":"4627 - 4663"},"PeriodicalIF":2.1,"publicationDate":"2026-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986275","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":"Comparative Evaluation of Hybrid ARIMA-XGBoost and Machine Learning Models for SO2 Forecasting in Gaziantep City","authors":"Efdal Kaya,&nbsp;Halil Baris Ozel,&nbsp;Muge Agca,&nbsp;Ilknur Zeren Cetin,&nbsp;Riza Altunay,&nbsp;Dilek Birgul Zeren","doi":"10.1007/s00024-026-04063-3","DOIUrl":"10.1007/s00024-026-04063-3","url":null,"abstract":"<div><p>Air pollution represents a major public health challenge, particularly in rapidly developing urban environments. Accurate forecasting of sudden fluctuations in air pollutant concentrations is therefore essential for effective air quality management and environmental decision-making. In this study, SO₂ concentrations (µg/m³) were forecast using four categories of forecasting approaches: statistical forecasting models, including Auto-Regressive Integrated Moving Average (ARIMA), Exponential Smoothing (ETS), and Prophet; standard machine-learning models, including linear regression (LR), k-nearest neighbours (KNN), multilayer perceptron neural networks (MLP), and support vector regression (SVR); ensemble-learning models, including Random Forest (RF) and Extreme Gradient Boosting (XGBoost); and hybrid forecasting models, including ARIMA-Boost and Prophet-Boost. A comprehensive comparative framework integrating statistical, machine-learning, ensemble-learning, and hybrid forecasting approaches was developed and systematically evaluated. Daily SO₂ concentration data collected between 01/01/2020 and 31/07/2024 were obtained from the official air quality monitoring station operated by the Ministry of Environment, Urbanization and Climate Change in Gaziantep Province, Türkiye. Model performance was evaluated using mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean squared error (RMSE). Among the evaluated models, the hybrid ARIMA-Boost framework achieved the best overall forecasting performance, producing the lowest MAE (2.61) and RMSE (3.71) values, whereas the ARIMA model yielded the lowest MAPE value (26.51). The findings demonstrate that hybrid statistical-machine-learning forecasting frameworks can substantially improve SO₂ prediction accuracy compared with conventional statistical methods and standalone machine-learning approaches.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"183 9","pages":"4665 - 4684"},"PeriodicalIF":2.1,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986119","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":"Climatic Extreme in a High-Resolution Dataset over Densely Populated Cities of Middle Gangetic Plain, India","authors":"Prabhat Kumar,&nbsp;P. Parth Sarthi,&nbsp;Archisman Barat,&nbsp;Sunny Kumar","doi":"10.1007/s00024-026-04049-1","DOIUrl":"10.1007/s00024-026-04049-1","url":null,"abstract":"<div><p>The current study investigates the climatic extremes using high-resolution datasets over densely populated cities of the Middle Gangetic Plain, India. Extreme weather events significantly impact urban infrastructure, public health, and the economy, with these effects intensifying due to climate change. The Climpact2 package was used to analyse nine temperature-based and six precipitation-based indices from high-resolution Climate Hazards Center datasets (CHIRTS and CHIRPS) spanning from 1983 to 2016. The Mann–Kendall test and Sen’s slope estimator were employed to evaluate trends in extreme climatic events. Results reveal a significant increase in warm temperature indices and a decrease in cold temperature indices across most cities. Warm days (TX90P) increased up to 0.406% days/year over Bhagalpur, while warm nights (TN90P) increased by 0.509% days/year, indicating comparatively stronger nighttime warming. The Warm Spell Duration Indicator (WSDI) and Heatwave Frequency (HWF) also showed increasing trends, reaching 0.561 days/year and 0.548 days/year, respectively. In contrast, cool nights (TN10P) decreased significantly by − 0.489% days/year over Muzaffarpur, while the Cold Spell Duration Indicator (CSDI) declined by − 0.592 days/year, suggesting shorter and less frequent cold conditions. These trends indicate intensified urban warming and increasing thermal stress over the selected cities, particularly after 2005, possibly associated with rapid urban expansion, increasing built-up areas, urban heat island effects, and aerosol interactions. Precipitation indices exhibited mixed but statistically non-significant trends across the study region. Annual total wet-day precipitation (PRCPTOT) showed increasing tendencies over Muzaffarpur (2.887 mm/year) and Patna (2.087 mm/year), while maximum 5-day precipitation (RX5day) increased by 0.301 mm/year over Patna. However, the Simple Daily Intensity Index (SDII) generally exhibited decreasing trends across all cities, indicating reduced rainfall intensity in several urban locations. These heterogeneous precipitation patterns may be influenced by variations in urban morphology, land cover, topography, moisture availability, aerosol loading, and regional monsoon variability, leading to differing city-scale climatic responses. The findings further suggest that neighbouring cities sharing similar physiographic settings may still exhibit substantially different climatic behaviour due to variations in urban structure and local meteorological conditions. Overall, the study provides new insights into urban-scale climatic extremes over the Middle Gangetic Plain and highlights the urgent need for city-specific climate adaptation strategies, resilient urban planning, and improved infrastructure to minimise climate-related risks and support sustainable urban development.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"183 8","pages":"4291 - 4306"},"PeriodicalIF":2.1,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148751972","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":"Coupled Eulerian–Lagrangian Based Nonlinear Seismic Sloshing Analysis of Reinforced Concrete Elevated Circular Water Tanks","authors":"G. S. Arun Kumar,&nbsp;Amit S. Waddar,&nbsp;M. B. Niyaz Ahamed,&nbsp;Gururaj Hatti,&nbsp;Saleemsab Doddamani","doi":"10.1007/s00024-026-04048-2","DOIUrl":"10.1007/s00024-026-04048-2","url":null,"abstract":"<div><p>Elevated reinforced concrete (RC) water tanks are highly susceptible to seismic loading due to hydrodynamic sloshing effects, which can significantly increase structural responses and compromise operational safety. This study presents a nonlinear fluid–structure interaction (FSI)-based numerical investigation of the seismic behaviour of an elevated RC circular water tank, with particular emphasis on the effectiveness of baffle walls in mitigating sloshing-induced demands. Three-dimensional dynamic simulations were performed in ABAQUS using a coupled Eulerian–Lagrangian (CEL) framework, incorporating material nonlinearity and realistic interaction between the contained water and the tank structure. The 2001 Bhuj earthquake ground motion was applied as horizontal base excitation to evaluate the tank response under half-filled conditions for configurations with and without baffle walls. The seismic performance was assessed in terms of fluid displacement, velocity, acceleration, structural displacement, base shear, and S11 stress distribution. The results demonstrate that the incorporation of baffle walls significantly suppresses sloshing activity and improves the overall seismic response of the tank. Compared with the unbaffled configuration, the baffled tank exhibited reductions of approximately 83% in maximum water displacement, 50% in fluid velocity, and 44% in fluid acceleration. Furthermore, the base shear was reduced by approximately 36%, while the S11 stress distribution showed lower stress concentrations and a more uniform stress pattern in the tank wall and staging system. Structural displacement, velocity, and acceleration responses were also significantly reduced in the presence of baffles.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"183 8","pages":"3921 - 3938"},"PeriodicalIF":2.1,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148751973","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 Assessment of Agricultural Drought in Semiarid Northern Nigeria Using MODIS Data and Explainable Random Forest (2000–2025)","authors":"Muhammad Lawal Abubakar,&nbsp;Asmau M. Ahmed,&nbsp;Sidikatu Aliyu,&nbsp;Saadatu Umaru Baba,&nbsp;Muhammad Sambo Ahmed,&nbsp;Khalid Ibrahim Richifa","doi":"10.1007/s00024-026-04046-4","DOIUrl":"10.1007/s00024-026-04046-4","url":null,"abstract":"<div><p>Agricultural drought poses a persistent threat to food security in Katsina State, a semiarid region of northern Nigeria, yet the relative contributions of thermal stress and moisture deficit to vegetation health remain poorly understood. In this study, spatiotemporal agricultural drought dynamics from 2000 to 2025 were assessed using the vegetation health index (VHI), integrating MODIS-derived NDVI and land surface temperature (LST), CHIRPS rainfall, ERA5-Land soil moisture, and SRTM topographic data. A random forest regression model, interpreted with SHAP values, was employed to quantify the influence of biophysical drivers on vegetation health. The results indicate severe drought conditions in the early 2000s, with marked improvement after 2015 associated with lower thermal stress and improved vegetation conditions. The model demonstrated strong predictive performance (R² = 0.89; root mean square error (RMSE) = 8.29), identifying the LST as the dominant predictor of the VHI (59.3%), whereas rainfall exerted weaker direct effects (14.9%), reflecting the mediating role of soil moisture and temperature interactions in this semiarid system. These results suggest that early warning and adaptation strategies for drought in semiarid northern Nigeria should prioritize thermal stress indicators alongside conventional rainfall metrics.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"183 8","pages":"4397 - 4410"},"PeriodicalIF":2.1,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148751969","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":"3D Structural and Petrophysical Modelling for Reservoir Characterization of the Poseidon Gas Field, Browse Basin, NW Shelf, Australia","authors":"Maryam Dahiru Usman,&nbsp;John Oluwadamilola Olutoki,&nbsp;Mohamed Elsaadany,&nbsp;Hassan Salisu Mohammed","doi":"10.1007/s00024-026-04038-4","DOIUrl":"10.1007/s00024-026-04038-4","url":null,"abstract":"<div><p>This study presents an integrated reservoir characterization of the Poseidon Gas Field, located in the Browse Basin, offshore northwestern Australia. The field, known for its complex geological structure, was investigated using a multi-disciplinary approach that combined petrophysical analysis, 3D seismic interpretation, and structural modelling to delineate key reservoir properties and improve understanding of subsurface architecture to support hydrocarbon exploration and development strategies. Petrophysical analysis of well log data, including gamma-ray, resistivity, density, and neutron logs, was conducted to estimate porosity, permeability, and fluid saturation. Results revealed significant spatial variability in porosity (2–26%) and permeability (300–1700 mD), with higher porosity zones concentrated in the northeastern part of the field. These findings provided essential insights into the reservoir's storage and flow potential. Key structural features, including faults and horizon surfaces, were mapped to understand reservoir compartmentalization and identify potential hydrocarbon traps. Structural analysis indicated the presence of normal fault systems that significantly influence reservoir continuity and trap configurations. A 3D stochastic model incorporating seismic, petrophysical, and well log data was developed to visualize the spatial distribution and heterogeneity of the Plover Formation reservoirs. The model highlights the dominance of sand and silt facies with high hydrocarbon saturation (~ 80%). The integrated analysis confirms the presence of laterally continuous yet heterogeneous reservoirs between 4000 and 5500 feet, with promising hydrocarbon potential. The study enhances the geological understanding of the Poseidon Field and offers valuable input for reducing exploration risk, optimizing well placement, and improving recovery efficiency in similar deepwater gas reservoirs.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"183 8","pages":"4113 - 4132"},"PeriodicalIF":2.1,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148751971","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":"Detecting and Identifying Geomagnetic Anomalies Caused by Diversified Interferences with Ground Observations","authors":"Busheng Xie,&nbsp;Lixin Wu,&nbsp;Wenfei Mao","doi":"10.1007/s00024-026-04043-7","DOIUrl":"10.1007/s00024-026-04043-7","url":null,"abstract":"<div><p>Multi-source geomagnetic interferences have detrimental impacts on the magnetic field of geomagnetic observatories, resulting in reduced data availability and reliability. The detection and identification of potential magnetic disturbances with clear or unknown causes contributes to enhancing the anti-interference capability of international geomagnetic networks. In this study, we presented an integrated framework for detecting and identifying some typical magnetic interferences, which includes signal characteristic discrimination, detection algorithm design, correlation verification, and performance evaluation. Two INTERMAGNET stations in Japan and one geomagnetic observatory in China are used in this study. We analyzed the characteristics of magnetic disturbances caused by solar activity, climate activity, and human activities on ground observations referring to mechanisms. Considering three basic characteristics (amplitude, frequency, and morphology), various algorithms for interferences are developed for detecting geomagnetic anomalies. The detected anomalies are further identified using the verification of spatiotemporal correlation between the anomalies and interferences. The performance of the presented algorithms was evaluated using recall rate, precision, and accuracy, demonstrating their accuracy and effectiveness. Accordingly, the two-step method, sliding window method, time–frequency analysis method, and one-dimensional convolutional neural network model (1D CNN) are considered the optimal algorithms for identifying the anomalies caused by geomagnetic storms, thunderstorms, subway operations, and high-voltage direct current transmission (HVDC), respectively. This study provides a reference paradigm for addressing diversified interferences, facilitating the screening of weak magnetic disturbances generated by unknown factors such as geophysical activities, and providing a potential solution for pioneering applications.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"183 8","pages":"4003 - 4024"},"PeriodicalIF":2.1,"publicationDate":"2026-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148751199","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":"Temporal Analysis of the Contamination Plume from the Bauru Landfill","authors":"Marina Fernandes Sanches Barros,&nbsp;Mariana Barbosa Juarez,&nbsp;Andrea Teixeira Ustra,&nbsp;Heraldo Luiz Giacheti,&nbsp;Marcelo Cesar Stangari,&nbsp;Vagner Roberto Elis","doi":"10.1007/s00024-026-04041-9","DOIUrl":"10.1007/s00024-026-04041-9","url":null,"abstract":"<div><p>Improper disposal of municipal solid waste is a major source of soil and groundwater contamination, posing risks to ecosystems and public health. In this context, continuous and low-impact monitoring techniques are essential for tracking contaminant plume evolution around landfill sites. This study aims to evaluate the temporal evolution of a leachate-contamination plume at the Bauru Municipal Landfill (São Paulo State, Brazil) by integrating geoelectrical and hydrochemical data collected at different times. The analysis combines Electrical Resistivity Tomography (ERT) data obtained in 2008 using the direct-current (DC) method with new surveys conducted in 2022 using capacitive resistivity (CR), which allows resistivity measurements without electrode insertion and enables rapid, minimally invasive data acquisition. These geophysical datasets were integrated with groundwater chemical analyses from 2006 and 2023, focusing on electrical conductivity and major dissolved ions. The results reveal an expansion of low-resistivity zones beyond the landfill boundaries, preferentially in the east–northwest direction, consistent with regional groundwater flow. Time-lapse comparison indicates an increase in the spatial extent and intensity of conductive anomalies between 2008 and 2022, accompanied by significant rises in chloride and major cation concentrations (Na⁺, K⁺, and Ca²⁺), confirming the progressive influence of leachate migration within the aquifer. These findings demonstrate that leachate impact has not only persisted after landfill closure but has intensified over time. The strong agreement between geoelectrical and hydrochemical data highlights the robustness of the integrated approach for long-term environmental monitoring. In addition, the CR method proved to be particularly suitable for repeated surveys due to its operational efficiency and reduced surface disturbance, supporting its application in routine monitoring programs and in the assessment of containment system performance and remediation strategies.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"183 8","pages":"4159 - 4177"},"PeriodicalIF":2.1,"publicationDate":"2026-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s00024-026-04041-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148751187","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":"Acceleration Response Spectra for Iran: A Comparative Analysis of Ground Motion Databases including Iranian, Turkey, and PEER Records","authors":"F. Mahdavianfard,&nbsp;M. Zare,&nbsp;H. Zafarani","doi":"10.1007/s00024-026-04036-6","DOIUrl":"10.1007/s00024-026-04036-6","url":null,"abstract":"<div><p>This study investigates acceleration response spectra (ARS) resulting from different strong-motion databases, including Iranian, Turkey, and worldwide records. The study examined 5603 time histories from 404 shallow crustal earthquakes with a moment magnitude greater than M5.0, recorded by 1366 accelerometer stations. Site categorization follows the Iranian seismic design code (Standard No. 2800) procedure which is based on V_S30 (the time-averaged shear-wave velocity to 30 m depth). The ARS with a damping ratio of 5% was computed using 1913 Iranian time histories from 189 earthquakes with moment magnitudes greater than M5.0 at distances up to 80 km. The ARS from other datasets were also calculated and plotted in the same soil type using strong motion data from Turkey (AFAD) and important shallow crustal events around the world (PEER). The study reveals a mild discrepancy between derived record-based spectra for Iran and Standard No. 2800 spectra for different soil classes, particularly in softer ones. The near-field results demonstrate that with increasing in magnitudes, the response spectrum’s peak periods tend to increase at intermediate periods. In the analysis of near-field spectra, the proposed spectrum is significantly higher than the Iranian seismic design code (Standard No. 2800) spectrum in the short- and medium-period range for site class 2, indicating non-conservatism in current designing of short- and medium-rise structures in the near fault region. According to the conducted near-field investigations, it seems that from the statistical point of view, there is no need to apply the near-field coefficient in the standard No. 2800 spectrum.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"183 8","pages":"4025 - 4068"},"PeriodicalIF":2.1,"publicationDate":"2026-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148751188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-Term Trends and Variability in Global and Diffuse Solar Radiation Over India","authors":"Somnath Mahato,&nbsp;Pushpa Saroja,&nbsp;Vijai Kumar,&nbsp;Anjit Anjan,&nbsp;Vijai Kumar Soni,&nbsp;D. S. Pai","doi":"10.1007/s00024-026-04037-5","DOIUrl":"10.1007/s00024-026-04037-5","url":null,"abstract":"<div><p>Surface solar radiation (SSR) changes are of significance to the understanding of the atmospheric processes and regional climate variability. This study aims to provide a detailed analysis of the variations of both global and diffuse solar radiation in India over the past 54 years, based on the observations obtained from 12 stations of India Meteorological Department (IMD) across various parts of the country using quality-controlled pyranometers. To make sure the long-term data set is reliable and consistent, a systematic multi-stage data screening framework was implemented, such as removing outlier values by using IQR, excluding stations with more than 30% missing data, and performing extra data consistency checks for abrupt variability. Results show that there is a statistically significant reduction in solar radiation at all stations with the range of trends between − 0.42 and − 1.07 W m^–2 yr^–1 and maximum reduction in solar radiation is seen over New Delhi. On the contrary, the diffuse components of solar radiation show generally very small and spatially scattered positive trends, for which statistically significant tendencies can be found at a few stations. Seasonal analyses show that in monsoon season, diffuse radiation increases, indicating that the scattering effect of clouds may modulate the radiation components on the surface. Longer time series available until 2023 allows better characterization of the variability in the recent period and also shows high regional gradient in the radiation trends over India. The reductions were greater at stations from the north and west where the aerosol loading and urban emissions over the Indo Gangetic Plain are higher, with moderate changes at stations at coastal/southern stations, due to maritime and monsoonal effects. ERA5 reanalysis data supports this analysis, showing a statistically significant but relatively weak negative correlation between cloud cover and SSR in the recent period from 2001 to 2023 (r =  − 0.22, p &lt; 0.001), suggesting some of the observed variability in the recent period is due to the cloud variability. These findings offer a valuable observational baseline for monitoring long-term SSR variations across India, along with recent research, and reveal significant spatial variability and dynamic radiation patterns. The results of this study highlight the need for future multi-variate analysis using aerosols, cloud properties and atmospheric moisture to better parameterize the drivers of long-term radiation variability.</p></div>","PeriodicalId":21078,"journal":{"name":"pure and applied geophysics","volume":"183 8","pages":"4187 - 4199"},"PeriodicalIF":2.1,"publicationDate":"2026-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148751189","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}