International Journal of Climatology最新文献

{"title":"The Emergence of Near-Permanent Marine Heatwave State in the Tropical Indian Ocean During 2023–2024","authors":"Mohan Soumya","doi":"10.1002/joc.70014","DOIUrl":"10.1002/joc.70014","url":null,"abstract":"<div>\u0000 \u0000 <p>In 2023/24, global mean surface temperatures exceeded 1.5°C above pre-industrial levels, and the Tropical Indian Ocean (TIO) experienced a record-breaking basin mean anomalous warming of 0.88°C. This unprecedented warming in the TIO is linked to the severe and long-lasting marine heatwave (MHW) events ever recorded in the region, reconciling with the ongoing long-term warming and internal climate variabilities. The MHW events of 2023/24 were primarily centred in the Arabian Sea (AS) and southwestern TIO regions, with mean intensities of 0.73°C and 0.89°C, respectively. The prolonged MHW event developed in the AS region in August 2023 and in the southwestern TIO in July 2023 due to increased oceanic heat gain associated with increased insolation and reduced latent heat loss. The MHW event in the AS was sustained throughout the remainder of the year and the following year by subsurface warming due to the convergence of surface winds in the AS and suppressed cooling by vertical processes. In the southwestern TIO, the event intensified and lasted till December 2024, driven by thermocline warming induced by downwelling Rossby waves, triggered by intensified easterlies associated with an anomalously westward extended cold tongue in the equatorial Indian Ocean, linked to the co-occurrence of strong El Niño and extreme equatorial positive Indian Ocean Dipole (PIOD) events. The extreme warming of the TIO during 2023/24 underscores the ongoing impact of climate change on global ocean surface warming.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 9","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647774","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":"Assessment of the Spatiotemporal Dynamics of Agricultural Drought in the Tekeze Watershed, Northern Ethiopia","authors":"Yonas T. Tela,&nbsp;Simachew B. Wassie,&nbsp;Mehretie B. Ferede","doi":"10.1002/joc.70016","DOIUrl":"https://doi.org/10.1002/joc.70016","url":null,"abstract":"<div>\u0000 \u0000 <p>Agricultural droughts often disrupt cropping patterns in the rain-scarce regions of Ethiopia. Understanding their temporal trends and geographical variations can greatly aid farmers in planning their farming activities. This paper examines the temporal trends, geographical extent, and severity of agricultural droughts in the Tekeze watershed, Ethiopia. Data were acquired from MODIS NDVI using the Earth Engine Data Catalogue and from the Central Statistics Agency (CSA) of Ethiopia. The normalised difference vegetation index (NDVI), enhanced vegetation index (EVI), vegetation condition index (VCI) and Random Forest Regression model were used for data analysis. Findings showed that August and September sustained the highest vegetation cover and health, whilst June and July had the lowest. Over the 24-year period analysed using the VCI, 14 years experienced drought conditions, with areal coverage percentages ranging from 52.45% in 2003 to 78.1% in 2015. The temporal EVI values show that all the years of the study period fall under mild drought conditions on average. Spatially, the EVI drought ranges from 66.1% in 2023 to 82.1% of the total area in 2014. The integrated drought class map created using weighted overlay analysis showed three drought categories (moderate, mild &amp; no drought; consistently covering 0.38%, 63.9% and 35.9% of the area). Over 50% of the area was found affected by various drought levels for several years. The analysis of all indices indicates that the drought recurrence period is approximately 2 years, suggesting a deteriorating situation over time. The EVI analysis indicated that all the summer months during the study period were facing mild droughts, and none of the area was totally free from droughts. Furthermore, NDVI, EVI and VCI were moderately correlated with crop yields, explaining approximately 66%–73% of the variations observed in crop performance. These numerical results highlight the severity and distribution of drought conditions in the watershed. These results not only highlight the urgent need for effective drought management strategies but also stress the importance of continuous monitoring and adaptive planning for farmers in order to mitigate the adverse effects on crop yields.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228133","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":"Evaluation of the Performance of HighResMIP CMIP6 in Simulating Extreme Precipitation in Madagascar","authors":"Mirindra Finaritra Rabezanahary Tanteliniaina,&nbsp;Zhai Jun,&nbsp;Mihasina Harinaivo Andrianarimanana","doi":"10.1002/joc.70011","DOIUrl":"10.1002/joc.70011","url":null,"abstract":"<div>\u0000 \u0000 <p>This study assesses the performance of 17 High-Resolution Model Intercomparison Project (HighResMIP) from the Coupled Model Inter-comparison Project Phase 6 (CMIP6) and their ensemble mean in simulating extreme precipitation in Madagascar. For this purpose, nine extreme precipitation indices were used, namely consecutive dry days (CDD), consecutive wet days (CWD), heavy precipitation days (R10mm), very heavy precipitation days (R20mm), simple daily intensity (SDII), maximum 1-day precipitation (RX1day), maximum 5-day precipitation (RX5day), very wet days (R95P) and extremely wet days (R99p). Furthermore, two gridded data sets, the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and ERA5, were employed as the reference data. The performance of the models was assessed using Normalised Root Mean Squared Error (NRMSE), percentage of bias (PBIAS) and Taylor Skill Score (TSS). In addition, this study used a comprehensive model ranking (MR) to provide an inclusive assessment of the models. The results suggest that most HighResMIP models fairly reproduce the precipitation climatology in Madagascar. We also found that except for the simulation of R99P, most of the models have satisfactorily good results in simulating extreme precipitation indices over the study area. A further comparison between HighResMIP models and their CMIP6 counterparts showed that most of the high-resolution models have better performance; yet improving model parametrization is still important. In line with previous research, by crossing the results from CHIRPS and ERA5, we found that the multi-model mean outperformed individual models. Nevertheless, individual models such as HadGEM3-GC31-HH, HadGEM3-GC31-HM, ECMWF-IFS-HR and EC-Earth3P-HR have relatively good results. On the contrary, the worst performance is attributed to HIRAM-SIT-LR and INM-CM5-h. The outputs and results from this research deliver a comprehensive assessment of the performance of the new HighResMIP in simulating precipitation extremes at a local study, which are essential for policymakers and climate modellers.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 11","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145102195","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":"A New Exploration of the Evaluation of Multisource Snow Data and Variations in Snow on the Qinghai–Tibet Plateau","authors":"Zhengze Li,&nbsp;Zhigang Wei,&nbsp;Cunde Xiao,&nbsp;Xianru Li,&nbsp;Li Ma","doi":"10.1002/joc.70012","DOIUrl":"10.1002/joc.70012","url":null,"abstract":"<div>\u0000 \u0000 <p>Snow is considered a climate indicator. The Qinghai–Tibet Plateau (QTP) is covered largely with typical alpine snow, influencing the local water–heat balance and the surrounding regional climate. However, there are large uncertainties in land surface snow data. A comprehensive, quantitative multimetric evaluation is an urgent need. In this study, five snow datasets are comprehensively evaluated on the basis of station-observed snow depth data. The temporal and spatial variations in snow depth over the QTP from 1979 to 2022 are analysed, and a new indicator is proposed to represent the overall snow variation on the QTP in a more reasonable way. The main conclusions are as follows: (1) In terms of snow depth on the QTP, the China Long Time Series Snow Depth dataset (CLSD) has the best performance, followed by ERA5-Land and NOAA (V3). The bias of the Northern Hemisphere Long Time Series Day-by-Day Snow Depth dataset (NHSD) is small compared with the observation. (2) The first EOF mode of snow depth on the QTP, in annual, autumn, winter and spring, shows a reversal spatial distribution between the main area of QTP and the northwestern Hengduan Mountains. The main area of QTP in snow depth has a decreasing trend, and the northwestern Hengduan Mountains in snow depth has an increasing trend. (3) After detrending, the main characteristic of EOF mode in snow depth on the QTP is consistent variations throughout the region. The variation indicator of snow depth on the QTP (QTPSDI) reflects the variation of the snow depth over the overall plateau. The QTPSDI has a significant 2–7 year periodicity. Therefore, we emphasise that the selection of accurate and applicable snow data is as important as the reasonable representation of snow cover variations.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 11","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145102387","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":"Synoptic Control and Surface Conditions of Hail Events Over the Beijing Metropolitan Region in Warm Seasons","authors":"Mingxin Li,&nbsp;Fan Zhang,&nbsp;Jinfang Yin,&nbsp;Yaqiong Hu","doi":"10.1002/joc.70002","DOIUrl":"10.1002/joc.70002","url":null,"abstract":"<div>\u0000 \u0000 <p>The fine spatial characteristics of hail events and their associated environmental conditions across the Beijing metropolitan region (BMR) under distinct circulation patterns are examined, using direct hail observation from quality-controlled disaster dataset, L-band rawinsondes, surface automated weather stations and global reanalysis data during the warm season of 2011–2021. Four dominant circulation patterns: the northwest flow in front of ridge (NW), straight westerly flow (STW), cold vortex (CV) and pre-trough (PreT) have been identified with an objective classification method. Results show that weak synoptic forcing (NW/STW) favours localised hail events despite high convective available potential energy; while strong synoptic forcing patterns (CV/PreT) promote extensive hail events, especially for those with significant vertical wind shear. Two primary hail hotspots emerge, the northern mountains and urban core, with distinct environmental controls. The terrain–flow interaction and the relatively thinner melting layer favour hail events over the northern mountains in all circulation patterns. In contrast, urban hail distribution exhibits synoptic dependence: with weak west to southwest low-level flows and mid- to high-tropospheric cold air brought by strong northwesterly (NW/CV), hail events tend to concentrate over the urban area with surface warmer air and organised wind convergence, which favour the initiation and enhancement of storms as they move southeastwards. With strong low-level southerly flow dominating BMR and warm mid- to high troposphere due to weak westerlies (STW/PreT), hailstorms tend to move eastwards, preferentially producing hail over the northern mountains through orographic lifting, rather than the urban region. These results suggest the modification of the urban environment and mountain–plain circulations on the distribution of hail under varying circulation patterns.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 11","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145102166","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":"Forecasting Intense Radar Reflectivity Using Machine Learning and Deep Learning Algorithms","authors":"Ximena Orsi,&nbsp;Rodrigo Hierro,&nbsp;Pablo Llamedo,&nbsp;Pedro Alexander,&nbsp;Alejandro de la Torre","doi":"10.1002/joc.8919","DOIUrl":"10.1002/joc.8919","url":null,"abstract":"<div>\u0000 \u0000 <p>Over the past 50 years, numerous studies have been conducted in the Cuyo region of Argentina, South America, investigating the relationship between meteorological variables and hail precipitation. These studies have led to the development of various models aimed at classifying hydrometeors, determining their precipitation, size, and the resulting surface damage. Based on 16 years of observations using a three-radar network in the Cuyo region, this paper presents preliminary results from a hail prediction study employing machine learning and deep learning techniques applied to radar data. Algorithms random forest (RF), gradient boosting (GB) and logistic regression (LR) in addition to a recurrent neural network, were used to predict hail occurrence based on radar data. Storm cells were classified as hail or no-hail when their reflectivity reached or exceeded 55 dBZ during their evolution. Reflectivity was found to be the most suitable variable among over 50 radar variables for studying hail occurrence. Results showed that considering the temporal evolution of radar observations, by including data at different time steps (from Results showed that considering the temporal evolution of radar observations, by including data at different time steps (from <i>t</i> = 1 to <i>t</i> = 5), significantly improved the algorithms ability to predict hail occurrence). This can be attributed to both a reduction in forecast lead time and the relevance of the temporal evolution of the variables. The inclusion of global model data, such as reanalysis from ECMWF (ERA5) did not demonstrate any significant improvement in our predictions. Models such as recurrent neural networks (RNN) have the potential to deliver enhanced performance since they explicitly account for temporal dynamics.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 11","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101981","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":"Future Climate Changes on the Qinghai–Tibetan Plateau Under CMIP6 Global Climate Models","authors":"Rizwan Karim,&nbsp;Shufeng Li,&nbsp;Tao Su,&nbsp;Brian Odhiambo Ayugi,&nbsp;Hassen Babaousmail,&nbsp;Shumei Xiao","doi":"10.1002/joc.70005","DOIUrl":"10.1002/joc.70005","url":null,"abstract":"<div>\u0000 \u0000 <p>Rapid climate change on the Qinghai-Tibetan Plateau (QTP) is reshaping ecosystems, altering water availability and affecting human livelihoods. Understanding the timing and distribution of these changes is now critical. This study examines precipitation and temperature changes from 1980 to 2100 using CMIP6 global climate models (GCMs) and high-resolution observational data. It examined seasonal and annual variability, model biases and projected changes for various climate scenarios. Our findings show that climate models consistently overestimated precipitation, particularly in southeastern QTP, while cold biases are prevalent in central and western regions in the past. Seasonal precipitation patterns exhibit significant variation across QTP. Bias corrections enhanced model reliability, reinforcing projections of wetter conditions and continued warming across QTP. Future projections indicate wetter conditions in winter and summer, though some areas may experience a slight decline in annual accumulations. Temperature trends project pronounced warming across all seasons, with the strongest increases expected in winter. Both maximum and minimum temperatures project significant upward trends, particularly at higher elevations. These findings indicate a shift toward a warmer and wetter climate at QTP, with potential environmental and socio-economic impacts. The study underscores the urgency of adaptive strategies to mitigate climate risks and enhance resilience in this high-altitude environment.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 11","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101976","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":"Changing Rainfall Patterns and Their Climatic Drivers in One of the Rainiest Places on Earth, Debundscha, Gulf of Guinea","authors":"Elias Nkiaka,&nbsp;Suiven John Paul Tume","doi":"10.1002/joc.70009","DOIUrl":"10.1002/joc.70009","url":null,"abstract":"<p>Debundscha is ranked amongst the top rainiest places on Earth, yet there is a paucity of information on rainfall trends and their drivers in the area. However, the increasing frequency and intensity of hydrometeorological disasters, declining crop yields, and rising water scarcity in the area underscore the urgent need to investigate changing rainfall patterns and the climatic modes influencing rainfall in the area. Trend analysis using the Mann-Kendall test shows non-statistically significant declining trends in annual and seasonal rainfall in Debundscha (1972–2009) and other stations, except Limbe, which exhibits statistically significant increasing trends in annual and seasonal rainfall (1985–2015). Statistical analysis using partial least squares regression reveals that the Atlantic Multidecadal Oscillation (AMO), Southern Oscillation Index, Indian Ocean Dipole Western Pool Index, global sea surface temperature (GSST), Multivariate ENSO Index, and El Niño-Southern Oscillation are the dominant climatic modes influencing annual and seasonal rainfall in the study area. However, a different set of climatic modes affects rainfall at each station, with AMO and GSST strongly associated with annual rainfall in Debundscha. Analysing rainfall in high precipitation areas like Debundscha is essential for understanding how these regions are affected by changing climate patterns. On the other hand, identifying the main climatic modes influencing local rainfall is crucial for creating accurate seasonal and sub-seasonal forecasts. These forecasts can help reduce hydrometeorological risks, improve water management, and increase agricultural productivity.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 11","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/joc.70009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101880","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":"An Atmospheric Predictor to Estimate the Atmospherically Induced Water Level at Coasts With A Shallow Continental Shelf","authors":"Paula Gomes da Silva,&nbsp;Luana Borato,&nbsp;Antonio Fernando Härter Fetter Filho,&nbsp;Fernando Javier Mendez,&nbsp;Antonio Henrique da Fontoura Klein","doi":"10.1002/joc.8935","DOIUrl":"10.1002/joc.8935","url":null,"abstract":"<p>Due to the connection between atmospheric conditions and the marine climate, previous studies proposed the use of atmospheric data as a predictor to estimate the total water level at the coast. However, none of the previous applications considered the effect that a large and shallow continental shelf may have on the propagation of water level variables, such as the storm surge. The shallow bathymetry facilitates the occurrence of coastal trapped waves, and the storm surge signal may present a strong component generated in remote regions. This phenomenon must be considered when defining the atmospheric predictor in these areas. This work presents a methodology to define the best atmospheric predictor to describe waves, storm surge and total water level in this particular kind of coasts. The method was applied in a location on the southern coast of Brazil (Southwest Atlantic), where the effect of the shallow bathymetry in the storm surge was previously observed. A statistical relationship between the atmospheric predictor and water level variables at three coastal points was established to assess its ability to estimate atmospheric-induced water levels and their components. High Pearson correlation coefficients (<i>r</i> &gt; 0.78 for all variables) and errors comparable to those obtained by traditional numerical methods demonstrate the skill of the predictor to describe the variables related to the water level at the coast. The implications of the atmospheric predictor extend beyond water level estimation, including several applications. Some of these applications are shown here, such as the characterisation of average and extreme marine climate and the assessment of climate-induced variability.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 11","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8935","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145102054","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":"Austral Autumn Precipitation Anomalies Across the Amazon Basin Under the Combined Influences of the Equatorial Pacific and Tropical Atlantic","authors":"Antônio V. Nogueira Neto,&nbsp;Everaldo B. de Souza,&nbsp;Fernanda C. Vasconcellos,&nbsp;Douglas Silva Ferreira,&nbsp;Vania S. Franco,&nbsp;Claudia P. W. da Costa,&nbsp;Edmir S. Jesus,&nbsp;Renata G. Tedeschi","doi":"10.1002/joc.8936","DOIUrl":"10.1002/joc.8936","url":null,"abstract":"<p>Under normal conditions, the austral autumn (March–April–May [MAM]) season represents the onset, peak or end of the rainy season, depending on the Amazon sector. In this study, the relative influences of the equatorial Pacific (EqP) and tropical Atlantic (TA) on precipitation anomalies over northern South America were revisited, focusing on the Amazon Basin and the MAM season. We systematically analysed the combined and isolated influences of the EqP and TA to identify the regions of the Amazon that are most sensitive to the atmospheric and oceanic patterns during MAM and described the main related mechanisms responsible for anomalous precipitation. The main features of the El Niño-Southern Oscillation (ENSO) and the TA meridional sea surface temperature gradient (tropical Atlantic gradient—TAG) were described for each scenario. Our results indicate that a positive (negative) TAG alone increases (decreases) precipitation over the northern and central-eastern regions. On the other hand, the isolated influence of ENSO depends on its persistence during the season, affecting mainly the northern and north-eastern regions, with a stronger impact on La Niña occurrence. Under the occurrence of ENSO events and TAGs of the same sign, the whole equatorial Amazon is affected by the sum of circulation effects. In this context, the driest scenario was observed under the combined influence of an El Niño and a positive TAG, which strongly impacted the northern and central-eastern sectors of Amazon. Finally, TAGs and ENSO events of opposite signs resulted in anomalous precipitation mainly in the northern, north-eastern and western Amazon, where the TAG-related circulation prevailed against the influence of ENSO events. This study improves the current understanding of austral autumn spatial rainfall variability in the Amazon under the influence of ENSO and tropical Atlantic patterns.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 11","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8936","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101463","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}