International Journal of Climatology最新文献

{"title":"Atmospheric Rivers Amplify the Severity of Summer Humid Heatwaves in Northern China","authors":"Xuelei Han,&nbsp;Bo Liu,&nbsp;Shuanglin Li,&nbsp;Xupeng Ji","doi":"10.1002/joc.70500","DOIUrl":"https://doi.org/10.1002/joc.70500","url":null,"abstract":"<div>\u0000 \u0000 <p>Humid heatwaves (HHWs) pose severe risks to human health, agriculture, and economics, yet the modulation of these events by atmospheric rivers (ARs) remains poorly understood in East Asia. This study investigates the impact of ARs on summertime HHWs across mainland China. Overall, ARs increase the average HHW intensity in mainland China by 13.0%, with pronounced intensifications of 19.6% in Northwest China and 19.3% in Northeast China. Under AR scenarios, the proportions of extreme HHWs in Northwest China and Northeast China show remarkable relative amplifications of 93.9% and 237.9%, respectively. Mechanism analyses reveal a competing interplay between radiative cooling and moisture advection. While AR-induced cloud cover significantly attenuates surface shortwave radiation and slightly cools the near-surface air, this effect is overwhelmed by intense moisture transport. The resulting increase in humidity ultimately drives an increase in wet-bulb temperature. These findings underscore the importance of AR monitoring for forecasting and early warning of extreme HHWs in China.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 12","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163285","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":"Comparison of Azores High and ISMR Relationship During June and September","authors":"Priyanka N. Maraskolhe,&nbsp;Ramesh Kumar Yadav","doi":"10.1002/joc.70493","DOIUrl":"https://doi.org/10.1002/joc.70493","url":null,"abstract":"<div>\u0000 \u0000 <p>This study investigates the relationship between the Azores High and Indian summer monsoon during June and September. An opposite correlation pattern is observed during June and September, with significant positive correlation over the Gangetic Plain and north Peninsular India during June, and significant negative correlation over Central India during September. A diagnosis based on monthly ERA5 reanalyzed circulation products archived on finer grids reveals that the sustenance of positive rainfall anomalies over the Gangetic Plain and north Peninsular India during June is supported by the strengthened Azores High near its mean position, zonal extension and northward shift of the Tibetan Anticyclone from its mean position, and strengthening of the Asian jet over the Eurasian region, whereas the sustenance of negative rainfall anomalies over Central India during September is supported by the Azores High, which is shifted to northeast of the North Atlantic, that is, away from its mean position, mid-latitude waves propagating at higher latitude, hence not affecting Indian summer monsoon rainfall due to their absence towards north India, weakened Tibetan Anticyclone, and weakening of the Asian jet over the Eurasian region.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 12","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163221","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":"Spatial and Temporal Patterns of Extreme Hourly Rainfall in the Hawaiian Islands","authors":"Maxime Gayte,&nbsp;Yu-Fen Huang,&nbsp;Yinphan Tsang,&nbsp;Pao-Shin Chu,&nbsp;Thomas W. Giambelluca,&nbsp;Hanpei Zhang","doi":"10.1002/joc.70501","DOIUrl":"https://doi.org/10.1002/joc.70501","url":null,"abstract":"<p>Climate-driven changes in extreme precipitation and floods severely impact societies and ecosystems, yet regional spatial and temporal nuances remain poorly understood, including in the Hawaiian Islands. This study utilised stationary and non-stationary Generalised Extreme Value (GEV) distributions, annual maximum series (AMS), and circular analysis to examine extreme hourly rainfall across 117 gauges on the five most populated Hawaiian Islands (Kauaʻi, Oʻahu, Maui, Molokaʻi, and the Big Island) from 1966 to 2020. Stationary GEV results show that Kauaʻi, Oʻahu, and the Big Island exhibited higher return levels (the event magnitude at a given return period) than the other islands, with windward sides consistently exceeding leeward sides. The 1990–2020 AMS revealed that most places showed no trend in annual maximum hourly rainfall, while some significant positive and negative trends were identified across the islands. Non-stationary GEV results showed that extreme rainfall is spatially heterogeneous—Oʻahu, Molokaʻi, and Maui are dominated by decreasing return-level trends, while the Big Island and Kaua‘i show predominantly increasing trends, particularly for rare 20- and 100-year events. Notably, Maui exhibited consistent island-wide decreases regardless of frequency or duration. Circular analysis identified two primary, persistent seasonal peaks for extreme events: October—December and February—March. These findings highlight a critical duration dependence: short-duration infrequent extremes are intensifying across most islands, even where frequent events are decreasing, posing a significant threat to emergency responses. As the first study investigating hourly extreme rainfall in Hawai‘i, this work provides a vital understanding of non-stationarity on tropical islands to mitigate future flooding threats.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 12","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.70501","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Climatic Drivers of the Area Burned by Winter Wildfires in Northern Italy","authors":"Alice Baronetti,&nbsp;Paolo Fiorucci,&nbsp;Antonello Provenzale","doi":"10.1002/joc.70496","DOIUrl":"https://doi.org/10.1002/joc.70496","url":null,"abstract":"<p>This study explores the climatic drivers influencing the monthly Burned Area (BA) during the winter fire season (November–April) in northern Italy from 2008 to 2022 at 0.11° spatial resolution, providing an example of the current climatic dynamics affecting mountains. The results of the analysis indicated that the Alps and northern Apennines are mainly characterised by a winter fire regime. In these mountain areas, the Western Alps experienced the largest wildfire events, with return periods lower than 6 years. Parallel to BA data, 150 daily precipitation and temperature ground series were collected, converted to monthly scale, quality controlled, and gridded at the 0.11° spatial resolution. Several climatic indices were computed for precipitation, temperature, and droughts. To find the best BA predictors, we checked the correlations of BA with different temporal aggregations of climatic indices. For each pixel of the grid, we performed multilinear regression models using all possible combinations of the significant drivers. The selection of the best regression models was based on an out-of-sample procedure, and the model performance was tested by comparing the predicted BA with the observed data, estimating explained variance and correlation. While rising temperatures are often assumed to be the main driver of BA under climate change, our study revealed that low precipitation and water balance deficit from December to March played the most significant role in influencing BA during the winter fire season.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 12","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.70496","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Time Series Analysis of Temperature and Precipitation Dynamics Using CETA and MCETA Methods","authors":"Sajid Gul,&nbsp;Guo Mingyan,&nbsp;Xia Cui,&nbsp;Ahmet Iyad Ceyhunlu,&nbsp;Hamza Pir,&nbsp;Gokmen Ceribasi","doi":"10.1002/joc.70484","DOIUrl":"https://doi.org/10.1002/joc.70484","url":null,"abstract":"<div>\u0000 \u0000 <p>In order to comprehend climate variability and extremes, it is essential to evaluate hydro-climatic trends at various risk levels. The annual mean temperature and total precipitation data from 11 meteorological stations in the Khyber Pakhtunkhwa region of Pakistan were subjected to the Crossing Empirical Trend Analysis (CETA) and Modified Crossing Empirical Trend Analysis (MCETA) methods in this investigation. In CETA framework, upper and lower trend slopes are derived from maximum and minimum values identified in the first and second halves of the time series. In contrast, MCETA determines pivot values directly from cumulative distribution function (CDF)–based critical thresholds corresponding to selected risk levels (5%, 50% and 95%), enabling a risk-oriented trend assessment. The results show that temperature series generally exhibit increasing trends across most stations, particularly at median and higher risk levels, indicating intensified thermal conditions. Precipitation trends display greater spatial variability, with several stations showing increasing trends at higher risk levels and decreasing trends at lower levels, suggesting a tendency towards more intense but less frequent precipitation events. The results indicate that MCETA outperforms both CETA and conventional trend analysis methods by offering a more comprehensive and distribution-sensitive assessment of hydro-climatic trends. MCETA, in contrast to conventional methods, effectively captures slope variability across various segments of the data distribution, thereby facilitating the identification of heterogeneous trend behaviours that are associated with differing risk levels. The implementation of CETA and MCETA in conjunction demonstrates that hydro-climatic trends are not consistent throughout the distribution. This underscores the importance of risk level specific trend assessment in order to enhance hydro-climatic analysis, climate variability interpretation and climate risk evaluation.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 12","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163282","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":"Temporal Dynamics of Gross Primary Productivity in India: From Historical to High Emission Scenarios","authors":"Smrati Gupta,&nbsp;Yogesh K. Tiwari,&nbsp;Ravi K. Kunchala,&nbsp;Ankur Srivastava,&nbsp;Akhilesh S. Raghubanshi","doi":"10.1002/joc.70490","DOIUrl":"https://doi.org/10.1002/joc.70490","url":null,"abstract":"<div>\u0000 \u0000 <p>Understanding how terrestrial primary productivity responds to climate change is essential for regional carbon budgeting and climate adaptation planning. This study investigated historical (1985–2014) and future (2015–2100) changes in Gross Primary Productivity (GPP) over India using biogeochemically coupled Earth system models (ESMs) from CMIP6, together with a comparative assessment of CMIP5 and CMIP6 simulations under high-emission scenarios. Model projections are evaluated in the context of climatic variability, land-cover changes and biosphere–climate interactions. Results indicate a robust increase in annual GPP over India during the historical period, with continued enhancement under the SSP5–8.5 scenario. CMIP6 projects substantially stronger future GPP increases than CMIP5, with future GPP trends up to ~2.5 times the historical trend magnitude over the country. Spatially, the largest increases occur over the Indo-Gangetic Plain, Northeastern India and the Western Ghats region. These modelled trends are broadly consistent with observed increases in forest and crop cover. However, CMIP models generally underestimate the magnitude of GPP relative to flux tower and satellite-based estimates. A comparison between CMIP5 and CMIP6 indicates that CMIP6 multimodel average (MMA) projections show stronger GPP trends than CMIP5, particularly after mid-century. However, improvements in the strength of the climate–GPP correlation are not statistically significant. The enhanced GPP trends projected by CMIP6 appear to be linked to stronger precipitation increases together with coupled CO₂ fertilisation effects. Spatial attribution analyses suggest a moderate coupling between increasing rainfall and increasing GPP, particularly across semi-arid and water-limited ecosystems. Detrended analyses further suggest that higher rainfall years generally enhance productivity, whereas higher temperature years suppress GPP through heat and moisture stress. However, partial correlation and regression analyses reveal substantially weaker climate–GPP relationships after detrending, indicating a strong influence of shared long-term forcing. Overall, the study demonstrates that long-term greening over India appears to be associated with combined CO₂ fertilisation and enhanced precipitation trends. In contrast, regional rainfall anomalies and temperature-related stress responses modulate interannual variability in productivity. These findings highlight the importance of accurately representing hydroclimatic processes and biosphere–atmosphere interactions in projecting future terrestrial productivity over monsoon-dominated regions.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 12","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163103","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":"Multi-Scale Meteorological Drought Return Periods and Climatic Associations in the Guangxi Karst Region Based on SPEI and 3D C-Vine Copula","authors":"Hu SiYi,&nbsp;Tang Xiangling,&nbsp;Li Wei,&nbsp;Han YiSong,&nbsp;Li Jianhong,&nbsp;Tang Yaoguo,&nbsp;Wu YeZheng","doi":"10.1002/joc.70498","DOIUrl":"https://doi.org/10.1002/joc.70498","url":null,"abstract":"<div>\u0000 \u0000 <p>Based on ERA5 reanalysis data (1940–2023), this study integrates trend tests, a three-dimensional C-vine Copula model, and cross-wavelet analysis to assess multi-scale meteorological drought in the Guangxi Karst Region, a typical humid subtropical karst ecosystem. Our results show that Guangxi exhibits an overall warming-drying trend, with significant increases in drought duration, severity, and peak since the early 21st century; however, only continuous karst regions show a statistically significant warming-drying trend. Drought risk is generally higher in karst regions than in non-karst regions, with differences showing scale and return period dependence. The joint risk of 20-year return period extreme drought follows a “low in the northeast, high in the southwest” spatial pattern. Extreme heat (TX90p) exhibits the strongest statistical association with annual-scale drought, contributing more than consecutive dry days (CDD) and ENSO. While short- to medium-term droughts have shown recent alleviation, annual-scale drought has intensified persistently. These findings provide a scientific basis for refined drought risk management in humid subtropical karst regions.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 12","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163284","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":"Preseason Tropical Cyclones and Springtime Environmental Changes in the North Atlantic (1980–2023)","authors":"Adam Szczapiński,&nbsp;Ewa Bednorz,&nbsp;Bartosz Czernecki","doi":"10.1002/joc.70499","DOIUrl":"https://doi.org/10.1002/joc.70499","url":null,"abstract":"<div>\u0000 \u0000 <p>This study examines the atmospheric and oceanic conditions associated with preseason North Atlantic tropical cyclones (TCs)—those forming in April and May prior to the official June 1 season start—over the period 1980–2023. Using HURDAT2 track data and ERA5 reanalysis, we analyse sea surface temperature (SST), mid-tropospheric relative humidity (RH at 600 hPa), vertical wind shear (VWS), low-level relative vorticity (RV), and two integrated diagnostics—Potential Intensity (PI) and the Genesis Potential Index (GPI). A total of 12 preseason TCs were identified, all reaching tropical storm intensity but none achieving hurricane strength. A statistically significant trend toward earlier tropical storm onset was detected at −12.3 days per decade (<i>p</i> &lt; 0.01). Ten of the twelve systems developed from non-tropical or hybrid precursors—stalled frontal boundaries, upper-level troughs, or extratropical cyclones undergoing tropical transition—rather than the classical tropical-wave pathway, distinguishing preseason cyclogenesis fundamentally from peak-season activity. Composite anomaly analysis reveals that preseason TC formation was associated with modest but significant positive SST and PI anomalies in the western Atlantic, locally elevated RH near Cuba, reduced VWS in parts of the eastern Atlantic, and enhanced low-level cyclonic vorticity near the Straits of Florida—a region that concentrates the majority of the preseason events. Springtime trend analysis identifies statistically significant SST warming (up to +0.4°C per decade) in the Gulf of Mexico and along the Gulf Stream corridor, RH increases in parts of the western basin, and notably, a significant VWS reduction over the Florida Peninsula (exceeding −2.0 m/s per decade)—a combination that may progressively lower barriers to early-season cyclogenesis. Positive PI trends exceeding +3 m/s per decade along the Gulf Stream axis reinforce this picture, while GPI positive trends, though spatially more limited, are consistent with an expanding environmental window for preseason activity. Together, these findings suggest that springtime conditions in the western North Atlantic are becoming incrementally more favourable for preseason TC formation, with the Florida Peninsula region emerging as a particularly sensitive hotspot warranting enhanced early-season monitoring.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 12","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163192","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":"Causal Inference of Cascading Effects and Their Driving Factors Among Multiple Drought Types in the Yangtze River Basin","authors":"Caiyuan Wang,&nbsp;Peng Yang,&nbsp;Jun Xia,&nbsp;Heqing Huang,&nbsp;Xiang Zhang,&nbsp;Lu Chen,&nbsp;Kaiya Sun,&nbsp;Xixi Lu","doi":"10.1002/joc.70483","DOIUrl":"https://doi.org/10.1002/joc.70483","url":null,"abstract":"<div>\u0000 \u0000 <p>While accurate assessment of drought evolution is a prerequisite for effective early warning and mitigation, conventional methodologies often struggle to characterise the intricate propagation pathways and feedback mechanisms inherent to the Yangtze River Basin (YRB). To address these deficiencies, this study establishes a causal inference framework for drought cascades by integrating convergent cross mapping (CCM), propensity score matching (PSM) and logistic regression. This approach facilitates the quantitative disentanglement of causal interactions among meteorological (MD), agricultural (AD) and hydrological droughts (HD), while effectively isolating confounding environmental variables. Our findings revealed that, in addition to the traditional MD–AD–HD propagation sequence, typically characterised by a 1-month lag, there existed significant, previously overlooked feedback loops (AD–MD, HD–MD and HD–AD) lacking strong lag signals, with a 0-month lag accounting for 63% of the YRB. Notably, the transformation risk from AD to MD was the highest (60%), whereas that from MD to HD was the lowest (20%), indicating that drought feedback mechanisms exert a consistently stronger influence than conventional downward propagation. Furthermore, precipitation (Pre) and vapour pressure deficit (VPD) were identified as the primary mitigating and intensifying drivers of these cascades (both propagation and feedback), respectively, with a unit increase in Pre reducing the drought cascade risk to as low as 0.18 times and a unit increase in VPD amplifying it to more than 3.0 times. The intensity of these interactions is further amplified in regions with lower altitudes and high soil clay content. Overall, this research offers a novel perspective on the bidirectional coupling of hydro-meteorological extremes, providing a robust scientific framework for nuanced drought risk management.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 12","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163252","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":"Forced Response in the Mean State and Interannual Variability of the Indian Summer Monsoon in Future Projections","authors":"K. Nithya,&nbsp;S. Aneesh,&nbsp;S. Sijikumar","doi":"10.1002/joc.70449","DOIUrl":"https://doi.org/10.1002/joc.70449","url":null,"abstract":"<div>\u0000 \u0000 <p>The Indian summer monsoon (ISM) is a complex system that plays a crucial role in the climate of South Asia. The Community Earth System Model 2-Large Ensemble (CESM2-LE) simulations are used to explore the forced response in the mean state and interannual variability of the ISM in future projections. Simulations during historical periods (1980–2009) show that the model could fairly reproduce the mean state and interannual variability of the ISM in terms of excess and deficient rainfall years and its association with strengthening and weakening of monsoon circulation. It is noticed that though the low-level monsoon jet shows a weakening during deficient monsoon years, it has more eastward extension, up to the western Pacific Ocean, compared to excess monsoon years. In simulations for future periods, the rainfall pattern shows an overall enhancement in the near future (2030–2059) and far future (2070–2099) periods. However, both the low-level jet and tropical easterly jet stream are weaker in future periods than that of the historical period. The future projections also exhibit stronger interannual variability, with wetter excess rainfall years and drier deficient years than corresponding historical years. Moreover, the likelihood of deficient years occurring in the future periods may increase with more dry conditions over southern peninsular India. Since the hundred ensemble mean suppresses most of the natural variabilities, changes that exist in the projected mean values are mainly due to the induced forcing (SSP3-7.0) in the model. The difference between with and without ENSO cases in the interannual variability shows that ENSO amplifies the variability in future projections, particularly in deficient rainfall years. Thus, the results obtained from the CESM2-LE simulations are crucial for developing more effective strategies for managing and policy-making efforts aimed at mitigating the impacts of monsoon variability in a warming world.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 11","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148862216","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}