Physics and Chemistry of the Earth最新文献

{"title":"Experimental study of the intrinsic specific energy of water-induced softening rocks under confining pressure condition","authors":"Mingchen Ding ,&nbsp;Mingming He ,&nbsp;Yangping Yao","doi":"10.1016/j.pce.2025.104218","DOIUrl":"10.1016/j.pce.2025.104218","url":null,"abstract":"<div><div>Rocks undergo physical and chemical changes on account of interplay with water, their material characteristics undergo deterioration. This behavior is characterized as water-induced softening. Drilling in water-bearing rock layers is more susceptible to engineering accidents such as collapse and instability under the influence of ground stress. This study conducted drilling experiments on four types of rocks at three levels of saturation and four confining pressures to understand the mechanical response of rock in drilling engineering. The recorded drilling parameters were used to calculate the drilling strength (<em>S</em>) and drilling specific energy (<em>E</em>). A drilling softening coefficient (<em>K</em>) was defined based on the <em>E</em>. The relationship between <em>E</em> and <em>S</em> under varying confining pressures and saturation levels was examined. In addition, the depth-dependent evolution of <em>K</em> during drilling was analyzed. These analyses were then used to investigate the mechanism of water-induced rock softening under different confining pressures. The strength parameters of rocks at different saturation levels were introduced to confirm the dependability of the presented <em>K</em>. Experimental findings indicated that <em>K</em> decreases as saturation rises, while it increases with higher confining pressure. Among the rocks, red sandstone exhibited the largest reduction and increase as 46 % and 32 %. A rebound phenomenon in the <em>K</em> occurred with higher confining pressure for limestone, red sandstone and shale. This phenomenon is associated with the coupled effects of water-induced rock degradation and drilling-induced rock failure. These findings offer new insights into the study of water–rock–drill interactions. They contribute to improved efficiency and safety when drilling through deep water-rich rock formations.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104218"},"PeriodicalIF":4.1,"publicationDate":"2025-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vertical distribution of different phase particles in summer topographic clouds over Liupan Mountain","authors":"Tong Lin ,&nbsp;Zhiliang Shu ,&nbsp;Peiyun Deng ,&nbsp;Lei Tian ,&nbsp;Yanqiao Sun ,&nbsp;Le Jia ,&nbsp;Ning Cao ,&nbsp;Hanbing Bai","doi":"10.1016/j.pce.2025.104212","DOIUrl":"10.1016/j.pce.2025.104212","url":null,"abstract":"<div><div>This study uses observation data from Ka-band millimeter-wave cloud radar (reflectivity factor, Doppler radial velocity, spectral width) and temperature profiles detected by microwave radiometers, and adopts a fuzzy logic algorithm to identify and retrieve cloud particle phases in orographic clouds over the Liupan Mountains. The results show that the cloud particle phases in the Liupan Mountains present a vertical distribution of “liquid in the lower layer, mixed phase in the middle layer, and ice crystals in the upper layer”, which is the result of the combined effects of orographic lifting, stratification structure, and local ascending airflows. Moreover, the cloud radar observation data exhibit obvious characteristics of changes with cloud particle phase states, which can serve as a basis for phase identification. Changing the feature threshold has a significant impact on the retrieval results. This study adjusts the threshold locally in combination with regional terrain and climatic characteristics, making the identification results more reasonable, consistent with the actual situation, and improving the applicability of the data. It is of great significance and application value for local weather modification operations.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104212"},"PeriodicalIF":4.1,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BAMPP: A novel Bayesian network enhanced by average marginal posterior probabilities to identify critical ground truth meteorological stations for drought monitoring","authors":"Rizwan Niaz ,&nbsp;Saman Munir ,&nbsp;Muhammad Ahmad Raza ,&nbsp;Rifat Tur ,&nbsp;Sadegh Partani ,&nbsp;Ali Danandeh Mehr","doi":"10.1016/j.pce.2025.104215","DOIUrl":"10.1016/j.pce.2025.104215","url":null,"abstract":"<div><div>This study introduces a new approach for identifying critical meteorological stations essential for analyzing spatiotemporal dynamics of drought events at regional scale. We propose a Bayesian network enhanced by Average Marginal Posterior Probabilities (AMPP) to evaluate stations based on frequency, severity, and persistence of Standardized Precipitation Index (SPI) at multiple timescales (SPI-3, SPI-6, and SPI-12). The method is demonstrated across the province of Ankara, Türkiye, effectively capturing the probabilistic relationships and interdependencies governing drought propagation among stations. Our analysis revealed distinct spatiotemporal patterns across the region at all time scales. For short-term droughts (SPI-3), critical station identity varied seasonally, indicating localized dynamics; for instance, Esenboga was key station in February, March, July, October and December, while Beypazari was influential in the other months. In contrast, for medium- and long-term droughts (SPI-6, SPI-12), Beypazari was the most critical station across all months, establishing it as the representative station for long-term drought monitoring in the region. This method provides a robust, probabilistic tool for optimizing drought monitoring networks and enhancing regional water resource management.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104215"},"PeriodicalIF":4.1,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on the characteristics of rainfall variation in the Huaihe River Basin based on multi-method analysis","authors":"Pengxin Cao ,&nbsp;Chengcheng Xu ,&nbsp;Chuiyu Lu ,&nbsp;Kaixuan Guo ,&nbsp;Ao Sun ,&nbsp;Xinang Li","doi":"10.1016/j.pce.2025.104213","DOIUrl":"10.1016/j.pce.2025.104213","url":null,"abstract":"<div><div>Against the backdrop of intensifying global climate change, extreme weather events have become increasingly frequent, posing significant challenges to watershed water resource management and ecological security due to altered precipitation patterns. To comprehensively reveal the spatiotemporal evolution of precipitation in the Huaihe River Basin, this study integrates multiple analytical methods, including the Mann-Kendall trend test, wavelet transform, and multifractal detrended fluctuation analysis (MFDFA), to systematically analyze monthly precipitation data from 16 representative meteorological stations across the basin during the period 1923–2023. The results indicate a general upward trend in precipitation, with particularly notable increases observed in the upstream regions. Spatially, precipitation intensity exhibits a gradient increase from the northwest to the southeast. Wavelet analysis identifies significant periodic fluctuations at both 2–12 years (interannual to decadal) and 20–40 years (multi-decadal) time scales. The Mann-Kendall test detects multiple abrupt change points, predominantly after the year 2000, indicating regime shifts in precipitation dynamics. The MFDFA and its improved variant, wavelet-based MFDFA (W-MFDFA), reveal widespread multifractal characteristics in the precipitation series, with pronounced nonlinear behaviors observed at specific stations such as Fuyang and Zhoukou. These findings enhance the understanding of regional climate variability mechanisms and provide theoretical support and decision-making references for optimized water resource allocation and flood risk management.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104213"},"PeriodicalIF":4.1,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145625413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Indirect mineral carbonation of CO2 using municipal incinerator bottom ash","authors":"Zahra Sarkarpour,&nbsp;Azadeh Hemmati","doi":"10.1016/j.pce.2025.104209","DOIUrl":"10.1016/j.pce.2025.104209","url":null,"abstract":"<div><div>Rising atmospheric CO₂ levels and their impact on global warming necessitate the development of efficient carbon capture and storage (CCS) methods. Among these, mineral carbonation offers a safe and permanent solution. This study investigates indirect CO₂ mineralization using bottom ash from a municipal waste incinerator as a calcium source. The effects of temperature, reaction time, and acid molarity on extraction efficiency were examined. Bottom ash was treated with hydrochloric acid (1 M and 2 M) at 80 °C for 30, 60, and 120 min. The resulting leachate underwent a pH-swing process using 1 M NaOH to precipitate impurities. A purified, calcium-rich solution was then reacted with Na₂CO₃ produced by bubbling CO₂ through 2 M NaOH to precipitate calcium carbonate. Laboratory results show that low pH favors the removal of iron and other impurities, while high pH (9–10) is optimal for calcium carbonate precipitation. Under these conditions, a carbonation efficiency of approximately 45 % and a product purity of 96 % were achieved, as confirmed by XRF analysis. Mass balance data indicate that 12 g of ash treated with 400 mL of HCl yields 2.3 g of calcium carbonate. ICP analysis identified 80 °C, 1 M acid, and 120 min as optimal parameters for maximum extraction efficiency. This study provides a scalable method for converting waste ash into valuable CaCO₃ while capturing CO₂, offering both environmental and economic benefits.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104209"},"PeriodicalIF":4.1,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Insightful frameworks for zeta potential of various clays in different brine compositions","authors":"Junhou Wang ,&nbsp;Farag M.A. Altalbawy ,&nbsp;Suranjana V. Mayani ,&nbsp;R. Manjunatha ,&nbsp;Debasish Shit ,&nbsp;M. Nirmala ,&nbsp;Ajay Sharma ,&nbsp;Sarbeswara Hota ,&nbsp;Barno Abdullaeva ,&nbsp;Fadhil Faez Sead ,&nbsp;Khursheed Muzammil ,&nbsp;Mehrdad Mottaghi","doi":"10.1016/j.pce.2025.104219","DOIUrl":"10.1016/j.pce.2025.104219","url":null,"abstract":"<div><div>Zeta potential is essentially the electrical charge on tiny particles suspended in a liquid. This charge is super important because it controls how stable these particles are and how they interact with each other. The zeta potential of clay particles is incredibly important for how colloidal suspensions behave, especially in industries like oil and gas. Knowing and being able to predict this electrical charge is crucial for tackling big challenges. This work presents an inclusive approach to forecasting the zeta potential of clay particles using advanced machine learning techniques, thereby addressing a key challenge in analyzing the electrochemical behavior of clays under varying environmental conditions. Experimental data from recent academic literature included 226 data points, comprising four input variables: clay type, pH, total dissolved solids (TDS), and ionic strength. After statistical analysis and outlier detection using the Monte Carlo Outlier Detection (MCOD), Gradient Boosting Machine (GBM) models were developed and optimized. To fine-tune these models, we employed a range of optimization algorithms, such as Evolution Strategy (ES), Self-Adaptive Differential Evolution (SADE), Batch Bayesian Optimization (BBO) and Bayesian Probability Improvement (BPI). The models' function was appraised using k-fold cross-validation, and their predictive accuracy was measured based on metrics such as mean squared error (MSE) and R². The results demonstrated that ES, BBO, and BPI algorithms achieved superior predictive accuracy, with R² values exceeding 0.92 for the test data, while SADE exhibited relatively lower efficiency. Sensitivity and SHAP (SHapley Additive exPlanations) analysis revealed that clay type was the most influential feature. Our novel application of Gradient Boosting and optimization algorithms effectively captures the complex, non-linear relationships between various factors and zeta potential. This methodological approach offers enhanced predictive power over traditional methods, marking a significant advancement for fields like environmental remediation, colloid stability assessment, and enhanced oil recovery, where understanding clay-fluid interactions is vital.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104219"},"PeriodicalIF":4.1,"publicationDate":"2025-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of climate change over the potential evolution of the glaciers of Antizana volcano","authors":"Génesis Buitrón-Cachipuendo ,&nbsp;Doris Cevallos-Sánchez ,&nbsp;Oscar Rosales-Enríquez ,&nbsp;Paúl Arias-Muñoz ,&nbsp;Roberto Chang-Silva ,&nbsp;Luis Maisincho ,&nbsp;Gabriel Jácome-Aguirre","doi":"10.1016/j.pce.2025.104214","DOIUrl":"10.1016/j.pce.2025.104214","url":null,"abstract":"<div><div>Glaciers cover approximately 10 % of the Earth's land surface and are sensitive indicators of climate change, particularly in the tropical Andes, where small climatic variations can significantly impact their extent. This study analyzed the glacial retreat of the Antizana Glacial System (AGS) by identifying influential variables, assessing glacial evolution using satellite imagery, and developing a predictive model for 2060 under two climate change scenarios (SSP1-2.6 and SSP5-8.5). Historical climate data, including temperature, precipitation, solar radiation, and wind speed were used alongside Partial Least Squares Regression (PLS-R) to relate these variables to glacier surface evolution. Results showed that temperature and precipitation are the most important variables in the predictive model. The glacier area decreased from 18.31 km² in 1990 to 15 km² in 2020, a reduction of 18.07 %. The PLS-R model explained 84 % of the variability in glacier coverage, with a Root Mean Square Error (RMSE) of 0.3. Climate projections for 2060 indicate that glacier area could decrease to 6.34 km² under an optimistic scenario (SSP1-2.6) and 4.84 km² under a pessimistic scenario (SSP5-8.5), representing losses of 65.37 % and 73.56 %, respectively, compared to 1990. These findings underscore the vulnerability of tropical glaciers to global warming, affecting biodiversity and water availability for local communities. Continuous monitoring is crucial to better understand their future evolution amid climate change. This study provides a foundation for decision-making on glacier conservation and mitigating the impacts of climate change on water resources and regional climate.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104214"},"PeriodicalIF":4.1,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cenozoic geodynamic and tectonomagmatic evolution of Andean margin, implications for metallogenic endowment of orogenic belts","authors":"Juan Pablo Bello-González ,&nbsp;Eduardo Contreras-Reyes ,&nbsp;Ítalo Payacán ,&nbsp;Felipe Quiero ,&nbsp;Paula Araya-Jaraquemada ,&nbsp;Pablo Moreno-Yaeger ,&nbsp;Pamela Jara ,&nbsp;Carlos Bazaes","doi":"10.1016/j.pce.2025.104202","DOIUrl":"10.1016/j.pce.2025.104202","url":null,"abstract":"<div><div>The genesis and distribution of porphyry copper deposits have long been studied due to the pivotal role this commodity has in economic development. However, they remain poorly understood and continue to be a topic of global interest. Although porphyry formation is typically associated with convergent plate margins, these deposits and their associated magmatic arcs are not uniformly distributed along such boundaries, which calls for alternative or complementary hypotheses to explain these differences. In this contribution, we explore the processes that play a role in the metal endowment of the continental crust, focusing on the heterogeneity of the subducting and overriding plates during the Cenozoic in the Central Andes. By reconstructing the tectonic interactions of oceanic and continental plates and analyzing a large set of 2355 igneous rock compositions (1770 pre-Quaternary), we examine these dynamics along the Andean margin, from northern Peru to central Chile. A significant finding is the pronounced spatio-temporal relationship between the subduction of hotspot tracks (from Easter, San Félix and Juan Fernández hotspots) and the genesis of porphyry copper deposits in the region, which are predominantly situated south of the hotspot tracks. Additionally, the trace element composition and distance to the trench of magmatic events display a distinct contrast between the northern and southern segments of the hotspot ridge subduction along the Andes. These observations suggest that seamount chain subduction may have played a primary role in lithospheric deformation and magma composition in the Andean orogen during the Cenozoic.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104202"},"PeriodicalIF":4.1,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Landslide susceptibility assessment using AHP and RF techniques: Special reference to Kumaun lesser Himalaya, Uttarakhand, India","authors":"Achla Joshi ,&nbsp;Girish Ch Kothyari ,&nbsp;Atul Kumar Patidar ,&nbsp;Khyati Gupta","doi":"10.1016/j.pce.2025.104191","DOIUrl":"10.1016/j.pce.2025.104191","url":null,"abstract":"<div><div>Landslides represent one of the most pervasive and hazardous geohazards globally, particularly in tectonically active and monsoon-dominated regions such as the Himalayas. The inner lesser and higher Himalayas are extremely susceptible to slope instability due to a fragile geological setup and erratic monsoon precipitation. The study focuses on the eastern Ramganga River basin, located in the Uttarakhand Himalaya, which experiences frequent occurrences of landslides. Therefore, identification and monitoring of hazard-prone zones are essential for risk mitigation and sustainable development planning. This study undertakes a comparative assessment of landslide susceptibility using two distinct approaches, the Analytical Hierarchy Process (AHP), a knowledge-driven multi-criteria decision-making method, and the Random Forest (RF) machine learning (ML) algorithms, a data-driven ensemble technique. A spatial database is developed, incorporating multiple Landslide Explanatory Variables (LEV) such as slope, aspect, curvature (plan and profile), distance to streams, topographic wetness index (TWI), geological units, structural features, lineament density, land use/land cover (LULC), soil type, and normalized difference vegetation index (NDVI). The model performance is evaluated using the area under the curve (AUC) metric. The landslide susceptible zonation analysis indicates a ∼431.93 km² area under high (∼32 %) and 150.68 km² very high (∼12 %) in the RF. However, ∼569.16 km² area under high (∼42 %) to 101.32 km² very high (∼8 %) in AHP. The RF model demonstrated a superior predictive capability (AUC 86 %), which outperformed to AHP model (AUC 70 %). Variable importance analysis revealed that slope, geology, and distance to streams are the most influential parameters controlling landslide dynamics. The comparative analysis between the two aforementioned techniques shows that the outcomes of RF are more reliable for landslide susceptibility analysis, owing to no subjectivity and bias compared to AHP. Overall, this study attributes the effectiveness of ML techniques for accurately marking the susceptible zones of the landslide and related hazards.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104191"},"PeriodicalIF":4.1,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extreme events and infant mortality: A mathematical modeling approach to understand climate-induced vulnerability in India","authors":"Aditi Chaturvedi,&nbsp;Mohammad Younus Bhat","doi":"10.1016/j.pce.2025.104192","DOIUrl":"10.1016/j.pce.2025.104192","url":null,"abstract":"<div><div>Extreme climate events have increased the frequency and intensity of environmental extremes, impacting children, particularly infants. To systematically investigate how infant mortality is temporally related to extreme climate events, we created a mathematical model to demonstrate the transitory nature of the relationships in India over the period 1990–2022, using the Autoregressive Distributed Lag (ARDL) method as an econometric approach with time series mathematical modeling. This method enables to estimate variables dynamic relationships in both the long and short run, and is ideal for addressing the complexity of extreme climatic event interactions. The empirical findings indicate that particulate matter (PM_2.5), and increased frequency of natural disaster events have a significant positive relationship with higher infant mortality rates in both long and short-run, as 1 % rise in disasters and PM_2.5 levels results in 0.05 % and 0.12 % rise in infant mortality rates respectively in the long run. The increased occurrence of vector-borne diseases has revealed mixed results as rise in malaria by 1 % leads to rise in infant mortality rates by 0.21 % in the long-run, while dengue has a negative association in the long-run. The rise in temperature and carbon emissions demonstrated a negative link with the infant mortality rate in both long and short-run. This study highlights the need for climate-resilient health systems and the need for early warning systems to protect infant health amid increasing climate extremes.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104192"},"PeriodicalIF":4.1,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145625412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}