Journal of Atmospheric and Solar-Terrestrial Physics最新文献

{"title":"A note on effects of fossil fuel reduction policies on atmospheric carbon dioxide buildup and global warming","authors":"Baris Baykant Alagoz ,&nbsp;Cemal Keles ,&nbsp;Burhan Baran","doi":"10.1016/j.jastp.2026.106724","DOIUrl":"10.1016/j.jastp.2026.106724","url":null,"abstract":"<div><div>Global warming is a near-future major problem that has serious consequences on life on Earth. Accumulation of CO₂ emission in the atmosphere becomes a dominating factor in the global warming process. This study introduces a global temperature uptrend model that considers effects of atmospheric CO₂ buildup because of combustion of natural gas, oil and coal fuels. The model is based on earth's energy balance modeling and estimates impacts of fossil fuel-based CO₂ emission on the average global temperature. To evaluate effects of fossil fuel reduction policies, this model is used to study yearly 3 %, 5 % and 7 % fossil fuel reduction scenarios on 2013–2022 global fuel consumption data. This backward projection indicated that the cumulative carbon dioxide emission of 10-year global fuel consumption has potential of about +0.023 °C/y global temperature rise between 2013 and 2022 years. Moreover, this model is also used for forward projections to discuss the effects of these 10-year-long fossil fuel reduction programs on future trends of global temperature anomaly.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"279 ","pages":"Article 106724"},"PeriodicalIF":1.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145940744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A hybrid deep learning based framework for prediction of rice yield through integration of biophysical parameters and optical remote sensing data in India","authors":"Rafath Samrin ,&nbsp;Pundru Chandra Shaker Reddy ,&nbsp;K. Arun Kumar ,&nbsp;Natha Deepthi ,&nbsp;C. Mithra ,&nbsp;S Bhargavi Latha ,&nbsp;Sucharitha Yadala ,&nbsp;Gopal Kumar Thakur","doi":"10.1016/j.jastp.2026.106734","DOIUrl":"10.1016/j.jastp.2026.106734","url":null,"abstract":"<div><div>India is the dominant player in the cultivation of rice around the world. Rice yield prediction can be considered as a problem that needs to be solved. Accurate and timely prediction of rice yield can provide meaningful benefits to crop yield. Time series models are widely used for rice yield prediction, but their accuracy remains inadequate. Despite their prominence, they often fail to deliver the required precision. This study considers one of the most practical machine learning (ML) methods for predicting rice yield, allowing forecasts for the next five years. The research carried out shows the rice yield prediction done using the hybrid framework which integrates multiple linear regression (MLR) with long-short-term memory (LSTM) and its performance is compared with state-of-the-art models. The yield is forecasted from the current year through the next five years, up to 2029. The data used for the prediction model will be 1998 to 2023 from four districts of West Bengal and Uttar Pradesh. An important finding of the study was that it is possible to predict rice harvest five years in advance of actual harvest, providing useful information for agricultural decision making and planning. Researchers, policy makers and farmers can all benefit from better food security planning and resource management thanks to the study's findings, which shed light on the possibilities of combining remote sensing with biophysical parameters using ML models. Measures used to assess the suggested model include R², RMSE, MAE, MSE, accuracy (Acc), F1 score (F1), recall (Re) and precision (Pe), among others. The suggested approach yields improved accuracy, R², RMSE, MAE, and MSE values of 0.9823, 0.956, 0.1436, 0.021, and 0.198, respectively.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"279 ","pages":"Article 106734"},"PeriodicalIF":1.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145979917","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":"Multifractal, recurrence, and information–Theoretic characterization of coupled proton dynamics in the solar wind","authors":"A.O. Adelakun","doi":"10.1016/j.jastp.2025.106713","DOIUrl":"10.1016/j.jastp.2025.106713","url":null,"abstract":"<div><div>This study applies a unified nonlinear framework–combining multifractal detrended fluctuation analysis (MF–DFA), recurrence quantification analysis (RQA), and transfer entropy (TE)–to investigate the dynamical coupling between proton density (PD), temperature (PT), and speed (PS) in the solar wind. The results reveal a consistent hierarchy across all diagnostics: temperature-speed coupling dominates (<span><math><mrow><mi>PT − PS</mi><mo>&gt;</mo><mi>PD − PS</mi><mo>&gt;</mo><mi>PD − PT</mi></mrow></math></span>), governing the principal pathway of energy redistribution. The PT–PS pair exhibits the broadest joint singularity spectrum and the strongest multifractal asymmetry, while recurrence metrics show sustained synchronization and structured determinism. Transfer–entropy analysis confirms a thermal–compressive <span><math><mo>→</mo></math></span> kinetic directionality, with PD and PT acting as information sources (<span><math><mrow><mi>PD</mi><mo>=</mo><mo>+</mo><mn>0</mn><mo>.</mo><mn>869</mn></mrow></math></span>, <span><math><mrow><mi>PT</mi><mo>=</mo><mo>+</mo><mn>0</mn><mo>.</mo><mn>457</mn></mrow></math></span>) and PS acting as the receiver (<span><math><mrow><mi>PS</mi><mo>=</mo><mo>−</mo><mn>1</mn><mo>.</mo><mn>326</mn></mrow></math></span>). These findings depict the solar wind as a self-organized, multiscale system in which intermittent synchronization between thermal and kinetic processes regulates flow variability. The integrated multifractal–recurrence–entropy framework provides a new diagnostic tool for identifying regime transitions and improving space-weather predictability.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"279 ","pages":"Article 106713"},"PeriodicalIF":1.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145897868","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":"Prediction of Cameroon's global solar radiation using deep learning and machine learning algorithms","authors":"Fodoup Cyrille Vincelas Fohagui ,&nbsp;Yemeli Wenceslas Koholé ,&nbsp;Clint Ameri Wankouo Ngouleu ,&nbsp;Donald Noutchogouin Tedom ,&nbsp;Ghislain Tchuen","doi":"10.1016/j.jastp.2026.106733","DOIUrl":"10.1016/j.jastp.2026.106733","url":null,"abstract":"<div><div>For solar photovoltaic and solar thermal systems to be effectively integrated into the energy grid, accurate prediction of solar radiation in a given area is essential. This prediction facilitates more effective planning, management, and optimization of energy production by utilities and renewable energy providers. From this vantage point, this article aims to forecast the daily global solar irradiation data of five cities in Cameroon (Bamenda, Bertoua, Ebolowa, Maroua, and Yaounde), which primarily differ in terms of solar irradiation distribution. In the study, ten different machine learning algorithms (Artificial Neural Network (ANN), Linear Regression (LR) algorithms, K-Nearest Neighbors (K-NN), Convolutional Neural Networks (CNNs), Random Forest (RF), Gradient Boosting Machine (GBM), Decision Tree (DT), Long-Short Term Memory (LSTM), Feed forward Neural Network (FNN), and Recurrent Neural Network (RNN)) are used. In the training of these algorithms, date, UT time, temperature, relative humidity, pressure, wind speed, wind direction, rainfall and solar irradiation of these cities are used. The data originate from the National Aeronautics and Space Administration and span the forty-one years (January 1, 1980, to December 31, 2021). Seven distinct statistical indicators are discussed to evaluate the effectiveness of these algorithms: t-statistic, Mean Absolute Percentage Error (MAPE), Maximum Absolute Bias Error (MABE), Means Bias Error (MBE), Root Mean Squared Error (RMSE), R-squared (R²) and relative Root Mean Squared Error (rRMSE). According to the findings, the R², MAPE, and RMSE values of every algorithm range from 0.718 to 0.937, from 12.2 % to 25.9 %, and from 232 to 978 kJ/m², respectively. When it came to R² and MAPE metrics, LR consistently showed the worst performance, and the algorithms that surpassed the t-critic value were KNN, RF, and ANN. The current study concludes that, although each of the machine learning techniques investigated in this research have the ability of reliably forecasting data on global solar radiation, the KNN algorithm proves to be the most suitable choice. Next in order of precedence are RF, LSTM, ANN, GBM, CNN, RNN, FNN, DT, and LR.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"279 ","pages":"Article 106733"},"PeriodicalIF":1.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034949","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":"Nighttime light data as a proxy for assessing air pollution in urban landscapes of India: A remote sensing perspective","authors":"Anisha Jalathota ,&nbsp;Mahesh Pathakoti ,&nbsp;Jaya Saxena ,&nbsp;Kanchana Lakshmi Asuri ,&nbsp;Mahalakshmi Venkata Dangeti ,&nbsp;Ramesh H. Gowda ,&nbsp;Sampath Kumar ,&nbsp;Srinivasa Rao Goru ,&nbsp;Prakash Chauhan","doi":"10.1016/j.jastp.2026.106732","DOIUrl":"10.1016/j.jastp.2026.106732","url":null,"abstract":"<div><div>Deterioration of air quality due to increasing anthropogenic activities adversely affect human health and the environment. This study presents the space-time variability of primary pollutants, namely columnar concentrations of atmospheric Carbon monoxide (<em>X</em>CO), Nitrogen dioxide (<em>X</em>NO₂), and Sulphur dioxide (<em>X</em>SO₂), across four major Indian cities, Hyderabad, New Delhi, Chandigarh, and Guwahati during 2019–2023 using the Sentinel-5P/TROPOMI open datasets from Google Earth Engine platform. Across the study sites, atmospheric CO indicates less variability, ranging from ±5.78 ppb to ±7.7 ppb, whereas atmospheric NO₂ and SO₂ observed moderate to high variability of distribution ranging from ±0.04 ppb to ±0.12 ppb, and ±0.99 ppb to ±1.52 ppb, respectively. The Suomi-NPP VIIRS night-time light product used in this study signifies the extent and intensity of urbanization. Alarming trends in spatially and temporally increased pollutant concentrations are observed in Guwahati due to rapid urban expansion and unregulated biomass burning. TROPOMI and MOPITT sensors demonstrated strong agreement in CO retrievals, with a relative biases ranging from −0.40 % to 5.16 %. TROPOMI derived <em>X</em>CO and <em>X</em>NO₂ retrievals show good agreement with Central Pollution Control Board measurements data. Thus, comprehensive analysis of these pollutants over these cites revealed a general increase in pollutant concentrations driven by urban development and seasonal wind patterns. The findings demonstrate the robustness of multi-sensor remote sensing datasets and urbanization indicators for monitoring air quality over rapidly developing Indian cities. The study provides valuable baseline information for developing and strengthening city-specific action plans to achieve clean air under the National Clean Air Programme (NCAP).</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"279 ","pages":"Article 106732"},"PeriodicalIF":1.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145979916","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":"How the East Asian subtropical westerly jet shapes the interannual variability of the South China Sea summer monsoon onset and the associated thermal forcing effect from the Tibetan plateau","authors":"Chengyu Song ,&nbsp;Jing Wang ,&nbsp;Yanju Liu","doi":"10.1016/j.jastp.2026.106736","DOIUrl":"10.1016/j.jastp.2026.106736","url":null,"abstract":"<div><div>Based on the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data and the Global Precipitation Climatology Project (GPCP) data, this research examines the atmospheric anomalies associated with the interannual variability of the South China Sea (SCS) summer monsoon (SCSSM) onset, focusing particularly on its connection with positional changes of the subtropical westerly jet (SWJ) and thermal conditions over the eastern Tibetan Plateau (TP). The analysis reveals distinct difference of the circulation patterns between early and late monsoon onset years, marked by pronounced cyclonic anomalies with intensified rainfall during early onsets, contrasted by anticyclonic patterns and reduced precipitation during delayed onsets. A key finding demonstrates that early SCSSM onset years coincide with a southward displacement of the upper-level SWJ north of the SCS. This positional shift generates upper-level ageostrophic southerly winds over the SCS, establishing a dipole pattern of vertical motion. Upper-level divergence and low-level convergence happen over the SCS (south of the jet core), and upper-level convergence with low-level divergence occur over the Yangtze River basin (north of the jet). Such configuration amplifies the meridional circulation anomaly, enhancing ascending motions in low-latitude East Asia while strengthening subsidence in mid-latitude regions. The study also further shows that thermal anomalies over the eastern TP significantly affect SWJ positioning and subsequent monsoon onset timing. Positive heating anomalies initiate an upper-tropospheric anticyclone, triggering eastward-propagating Rossby waves and downstream cyclonic circulation. This prompts a southward migration of the SWJ east of the TP, altering East Asian circulation patterns to facilitate an earlier SCSSM establishment. These results shed new light on the TP's role in regional climate modulation via upper-level jet dynamics, offering potential predictive value for monsoon onset forecasting.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"279 ","pages":"Article 106736"},"PeriodicalIF":1.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145979918","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":"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 ,&nbsp;Junyu Li ,&nbsp;Yibin Yao ,&nbsp;Lilong Liu ,&nbsp;Bao Zhang ,&nbsp;Liangke Huang ,&nbsp;Zhangyu Sun ,&nbsp;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":"2026-01-01","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}

{"title":"Urbanization-driven secondary climatic changes: Re-envisioning response of fast growing cities of Northern India","authors":"Koyel Sur,&nbsp;Sarabjit Singh,&nbsp;Vipan Kumar Verma,&nbsp;Brijendra Pateriya","doi":"10.1016/j.jastp.2025.106706","DOIUrl":"10.1016/j.jastp.2025.106706","url":null,"abstract":"<div><div>Urbanization and climatic changes are concomitant to each other. Urbanization induces climate change through enhanced greenhouse gas emissions, industrial processes, and energy consumptions. In developing countries like India, with the increase in population and change in lifestyle, there has been substantial rise in demand and use of energy and fuel, which consequently leads to conversion of agricultural land to built up area. This leads to rise in land surface temperature (LST) and adversely impact the micro-climate of a region in close vicinity of urban entities. The present study aims to analyze the association between built-up, green cover and land surface temperature for selected cities and corresponding districts i.e. Amritsar, Jalandhar, and Ludhiana of Punjab State, India, the main contributors to green revolution. Adopting remote sensing based approach, district-level analysis of the normalized differential built-up index (NDBI), normalized differential vegetation index (NDVI) and land surface temperature (LST) was carried out using Landsat 5 for the years 1990, 1999 and 2009, and Landsat 8 (OLI/TIRS) for 2019. To analyze the relationship between built-up and green cover with LST, correlation analysis was carried out indicating (a) alarming rising trend of built-up is 1.72 % in Amritsar, 2.99 % in Jalandhar and 3.3 % in Ludhiana (b) relatively higher temperature in core and the peri-urban built-up areas generate warmer surface temperatures than the surroundings (c) reduced area under agricultural land and (d) rising stress on water bodies.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106706"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145836660","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":"Three-dimensional lightning channel structure reconstruction: An efficient matching TOA algorithm for VHF pulses","authors":"Yueyang Wang,&nbsp;Yun Li,&nbsp;Shi Qiu,&nbsp;Shuangjiang Du,&nbsp;Zheng Sun,&nbsp;Lihua Shi","doi":"10.1016/j.jastp.2025.106702","DOIUrl":"10.1016/j.jastp.2025.106702","url":null,"abstract":"<div><div>To address the underutilization of pulse signals in existing time-of-arrival (TOA) algorithms for lightning radiation source localization, this study proposes a three-dimensional (3-D) lightning TOA localization algorithm based on efficient VHF pulse matching. In the signal segment matching stage, a rotating reference station mechanism is introduced to overcome the bottleneck of single-reference station matching, ensuring full utilization of pulse signals from each detection substation. In the precise time delay alignment stage, the maximum possible time delay of 10 μs caused by the fast development of lightning is determined through Monte Carlo simulation. Overlapping time windows are set via the sliding window method to avoid omissions in pulse matching. During the pulse matching stage, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) temporal clustering method is employed to traverse and match pulse signals within the same time window, and time-amplitude consistency verification is used to filter pulse matching results. Finally, the effectiveness of the novel optimized algorithm is verified through intracloud and cloud-to-ground flash cases. Compared with the existing algorithm, the novel optimized algorithm identifies 2.9 times more radiation sources. Meanwhile, it significantly improves the continuity and length of lightning channels, enabling more detailed reconstruction of complex lightning structures, and provides new technical tools for in-depth research on lightning processes and physical mechanisms.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106702"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145748757","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":"Temperature-sensitive changes in precipitation phases over two distinct glacierized basins of the North-Western Himalayas","authors":"Shanta Kumar ,&nbsp;Ashish Dogra ,&nbsp;Chander Prakash ,&nbsp;Anurag Linda","doi":"10.1016/j.jastp.2025.106691","DOIUrl":"10.1016/j.jastp.2025.106691","url":null,"abstract":"<div><div>The influence of warming on mountain precipitation is a pressing concern, yet the link between rising surface temperatures and changes in precipitation phases i.e., liquid (rainfall) and solid (snowfall) precipitation in the North-western Himalayas (NWH) remains poorly understood. The present study aims to make a maiden attempt of exploring the temperature-sensitive variations in precipitation phases over the two distinct glacierized basins of NWH (Ravi and Bhaga basins) by utilizing data from ERA5 product. For this purpose, we first examined the monthly, inter-annual, and inter-decadal variations in near-surface temperature (T), total precipitation (TP) and precipitation phase separately, as snow fraction (SF) and rain fraction (RF) intensity for the period 1940–2022. Second, we examined the long-term (1940–2022) and bifurcated (based on significance level) temporal variations in T, TP, SF, and RF. Lastly, to provide insights on how rise in T has induced changes in TP, SF, and RF, the percent of changes in respective precipitation patterns were normalized by degree of warming and presented in percent change per Kelvin (%/K) for each basin. During summer months, Bhaga basin showed higher variability in RF and SF than in Ravi basin. Interestingly, in comparison to the inter-annual, inter-decadal oscillations provided better picture of temporal variations in precipitation patterns over these basins. The long-term variations in TP revealed non-significant trend, while opposite significant trends were observed during bifurcated time periods. With respect to the long-term trends in precipitation phases i.e., in RF and SF, significant increasing trend in RF (+0.04 %/year) and an opposite significant decreasing trend in SF (−0.04 %/year) were observed in both basins. Despite the long-term significant trends in precipitation phases, significant opposing trends within each precipitation phase were observed during bifurcated periods. The percent change per Kelvin in TP over Ravi basin was −6.48 %/K, while for Bhaga basin it was +3.28 %/K. Furthermore, the changes in TP over Ravi was mainly contributed by the changes observed in SF (−6.36 %/K), while for Bhaga it was mainly contributed by RF (+8.02 %/K). The findings suggest that warming has shifted the precipitation phase from solid to liquid, indicating an escalation of rain-on-snow events over the glacierized basins in NWH.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"278 ","pages":"Article 106691"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145691516","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}