International Journal of Climatology最新文献

{"title":"An Unexpected Outcome Followed an Apparent Seasonal Forecast of Opportunity and Prolonged Drought in Southwest Asia","authors":"Andrew Hoell,&nbsp;Melissa L. Breeden,&nbsp;Rochelle P. Worsnop,&nbsp;Rachel Robinson,&nbsp;Laurie Agel,&nbsp;Weston Anderson,&nbsp;Mathew Barlow,&nbsp;Harikishan Jayanthi,&nbsp;Amy McNally,&nbsp;Shradhannand Shukla,&nbsp;Kimberly Slinski,&nbsp;James Verdin,&nbsp;Fahim Zaheer","doi":"10.1002/joc.8851","DOIUrl":"https://doi.org/10.1002/joc.8851","url":null,"abstract":"<p>Despite forecasts to the contrary, Southwest Asia precipitation was unexpectedly below normal in October–December 2023, which extended an ongoing three-year drought that was responsible for water shortages and acute food insecurity. Expectations for above-normal precipitation in this season were based on predictions made the prior September from initialized forecast systems, which indicated a greater than 60% chance of such an occurrence. Confident above-normal precipitation predictions, making October–December 2023 an apparent forecast of opportunity, were due to attendant El Niño and positive Indian Ocean Dipole (PIOD) events. An ensemble of model simulations during 1991–2020 indicates that the simultaneous behaviour of these two phenomena is related to the tropical forcing of the mid-latitude circulation over Asia resembling a Gill–Matsuno response over India and China, which is associated with precipitation-enhancing low pressure over Southwest Asia. The co-action of these two modes is related to greater chances of above-normal Southwest Asia precipitation than if El Niño were acting alone. Southwest Asia precipitation in October–December 2023 was 13 mm below average (15 percentile) and was principally caused by two periods of protracted dryness that each lasted up to 3 weeks. During 26 November to 14 December, high pressure moved slowly eastward across western Asia at the same time as a strong MJO event moved across the Indian Ocean in its Phases 4 and 5, which are related to below-average Southwest Asia precipitation. Cumulative regional precipitation while the MJO was in Phases 4 and 5 during this period was −6 mm, accounting for 46% of the seasonal precipitation deficit in the region. During 26 October to 19 November, high pressure persisted with very little eastward movement over Southwest Asia while the MJO was weak, which suggests that the precipitation deficit during this time was caused by internal atmospheric variability in the extratropics.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8851","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315397","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":"Changes in Precipitation Patterns in Poland Derived From Projected Downscaled Future Climate Data From CMIP5 and CMIP6","authors":"Agnieszka Rutkowska,&nbsp;Patrick Willems,&nbsp;Santiago Mendoza Paz,&nbsp;Agnieszka Ziernicka-Wojtaszek","doi":"10.1002/joc.8822","DOIUrl":"https://doi.org/10.1002/joc.8822","url":null,"abstract":"<div>\u0000 \u0000 <p>Climate change is affecting the intensity and frequency of precipitation. The main objective was to assess future changes in precipitation patterns in Poland. Ensembles of daily precipitation projections for 70 stations from CMIP5 and CMIP6 under RCP(SSP)4.5, RCP(SSP)8.5 pathways were statistically downscaled using the Quantile Perturbation Method (QPM), covering the reference period 1961–1990 and future period 2071–2100. We assessed annual and seasonal (winter, summer) changes in 12 extreme Precipitation Indices (PIs), their distributions across Poland, and shifts in design annual maximum (AM) precipitation intensities. Statistical measures included distribution fitting, Intensity-Duration-Frequency curves, and return periods. The projected changes (CMIP6-8.5) in summer include: increase in the length of consecutive dry days (5%, on average), number of heavy precipitation days (4%) and 1-, 3-, 5-day maximum intensity (8%, 6%, 5%), and decrease in the number of wet days (6%) and length of consecutive wet days (6%). In winter, projections show an increase in the number of heavy precipitation days (30%), 1-,3-, 5-day maximum intensity (15%, 13%, 12%), and total precipitation (11%). The changes vary across Poland, with a more intense increase in the number of heavy precipitation days in the north-west (summer) and in the 1-day maximum intensity in the south (winter), higher precipitation totals in the south, southeast and coastal areas (winter), and a decrease in total precipitation in the south and east (summer). Uncertainty is large for the number of heavy precipitation days and maximum intensities, while it is low for total precipitation and the number of wet and dry days. Future return periods of extreme events are projected to shorten. A 100-year 1-day AM intensity can become a <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>49</mn>\u0000 <mo>−</mo>\u0000 <mn>66</mn>\u0000 </mrow>\u0000 </semantics></math>-year intensity. The results can be applied in flood and drought management plans, helping to adapt to future changes in precipitation patterns.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256488","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 Morphology of the Stratospheric Polar Vortex Under Stratospheric Aerosol Intervention Scenarios","authors":"Khalil Karami,&nbsp;Christoph Jacobi,&nbsp;Anish Kumar","doi":"10.1002/joc.8838","DOIUrl":"https://doi.org/10.1002/joc.8838","url":null,"abstract":"<p>Even though it is widely acknowledged that the stratospheric polar vortex (SPV) strengthens under stratospheric aerosol intervention (SAI), little is known about how the SPV's size, duration, location, and edge change under SAI compared to the present-day climate. Here, we address these issues using two large ensemble SAI simulations, namely GLENS (2060–2079) with extreme forcing and ARISE (2050–2069) with more moderate forcing. It is found that the wintertime Arctic and Antarctic stratospheric wind responses to SAI compared to the control (CTL) climate in GLENS (2060–2079) are roughly two times as large as in ARISE (2050–2069). While the zonal wind acceleration in ARISE (2050–2069) is hemispherically symmetric at 3–4 m s⁻¹ in the stratosphere of both hemispheres, the responses in GLENS (2060–2079) are hemispherically asymmetric, being two to three times larger in the Southern Hemisphere (SH, ~15 m s⁻¹) compared to the Northern Hemisphere (NH). While the edge of the vortex in GLENS (2060–2079) intensifies under SAI, similar changes are not found in ARISE (2050–2069). Such intensification of the vortex edge in GLENS is limited to lower stratosphere levels and does not extend to greater heights (~10 hPa). SAI has no discernible effect on the NH vortex morphology in ARISE simulations. However, the edge of the vortex intensifies in terms of Ertel's potential vorticity (EPV) gradient under SAI in the NH in GLENS. The greatest change that the SPV consistently shows under SAI in both GLENS and ARISE simulations is the SH spring vortex's behaviour. Under SAI, at 530 and 600 K, the vortex edge is weaker, its area is smaller, and it breaks up earlier than in the CTL runs.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8838","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315186","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":"ENSO Diversity Regulation of the Impact of MJO on Extreme Snowfall Events in the Peruvian Andes","authors":"Juan Sulca","doi":"10.1002/joc.8790","DOIUrl":"https://doi.org/10.1002/joc.8790","url":null,"abstract":"<p>Extreme snowfall events (ESEs) in the Peruvian Andes (10°–18.4° S, &gt; 4000 m) result in considerable economic losses. Despite their importance, how El Niño-Southern Oscillation (ENSO) diversity modulates the impact of the Madden–Julian Oscillation (MJO) on ESEs in the Peruvian Andes remains unexplored. Daily ERA5 reanalysis data from 1981 to 2018 were analysed. This study examines 16 ESEs. A bandpass filter with a 20–90-day range was applied to isolate the intraseasonal component of the daily anomalies. Additionally, time series data from the real-time multivariate MJO (RMM) index and Eastern and Central ENSO (E and C) indices were utilised. Composites were performed to describe the atmospheric circulation patterns related to ESEs in the Peruvian Andes under neutral, El Niño and La Niña conditions in the central and eastern Pacific Ocean. Under non-ENSO conditions, the MJO alone does not trigger ESEs in the Peruvian Andes during the DJF season. The absence of a well-organised convection system over the Peruvian Andes prevents ESEs. Conversely, during the JJA season, MJO Phases 5, 6 and 7 induce ESEs in the southern Peruvian Andes by enhancing moisture flux from the east through the equatorward propagation of an extratropical Rossby wave train that crosses South America and reaches the Altiplano region. In terms of ENSO diversity, the combined effects of the Central La Niña and MJO Phases 6 + 7 induce ESEs across the Western Cordillera of the southern Peruvian Andes during the DJF season. During austral winter, the interaction between the Central El Niño and MJO Phases 8 + 1, Eastern El Niño and MJO Phases 2 + 3, and Eastern La Niña and MJO Phases 8 + 1 induce ESEs across the Peruvian Andes.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8790","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256504","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":"Thunderstorm Forecasting by Using Machine Learning Techniques: A Comparative Model Analysis Leveraging Historic Climatic Records of Bangladesh","authors":"Mahiyat Tanzim,&nbsp;Sabina Yasmin","doi":"10.1002/joc.8853","DOIUrl":"https://doi.org/10.1002/joc.8853","url":null,"abstract":"<div>\u0000 \u0000 <p>Accurate thunderstorm forecasting is essential for protecting communities and minimising disruptions to agriculture, infrastructure and human lives, particularly in Bangladesh. However, predicting thunderstorms remains challenging due to the complex interplay of meteorological factors, data limitations and regional variations. This study addresses these challenges by integrating historical meteorological data with advanced machine learning and deep learning techniques to improve prediction accuracy. Using data from the Bangladesh Meteorological Department, we compare various models, evaluating their performance based on the coefficient of determination (<i>R</i>²) and root mean squared error (RMSE). Among traditional machine learning models, the Support Vector Machine (SVM) Regressor performed best with an <i>R</i>² of 0.658 and RMSE of 3.65. Among deep learning models, Convolutional Neural Networks (CNNs) achieved superior accuracy with an <i>R</i>² of 0.743 and RMSE of 3.17, effectively capturing spatial patterns in thunderstorm occurrences. Additionally, deep learning models such as CNN, ANN and LSTM successfully detected annual trends and fluctuations, improving prediction reliability. These findings highlight the potential of deep learning in enhancing thunderstorm forecasting, contributing to more effective disaster preparedness and risk management in thunderstorm-prone regions.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315216","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":"Contrasting Historical Trends in Equatorial Indian Ocean Zonal Sea Surface Temperature Gradient in CMIP6 Models","authors":"Mohan Soumya,&nbsp;Suresh Gopika","doi":"10.1002/joc.8832","DOIUrl":"https://doi.org/10.1002/joc.8832","url":null,"abstract":"<div>\u0000 \u0000 <p>The zonal sea surface temperature (SST) gradient in the tropical Indian Ocean (TIO) has been assessed using 50 climate models. Among these, 38 models exhibit an east–west negative gradient trend, indicating an intensified warming pattern in the Western Equatorial Indian Ocean (WEIO). This strong inter-model spread in representing the zonal SST gradient in the TIO mainly arises from the large variability of SST trends in the eastern Indian Ocean. The multi-model mean shows a westward SST gradient trend, which is approximately four-fold higher than the observed zonal gradient trend. However, models such as E3SM-1-1 and NESM3 realistically represent SST trends in both the eastern and western equatorial Indian Ocean regions, thereby capturing SST gradients close to observation. To investigate gradient variability and the underlying mechanisms, we categorised models into two groups, each comprising five models. The first group, comprising CESM2-FV2, EC-Earth3-Veg-LR, EC-Earth3-Veg, CAS-ESM2.0, and CIESM, demonstrates pronounced negative SST gradient trends. Conversely, the second group, consisting of CESM2-WACCM-FV2, CESM2, CESM2-WACCM, CMCC-CM2-SR5, and MIROC6, exhibits relatively subdued positive gradients, attributable to the slower warming of the WEIO. The inconsistent warming pattern formation, associated with eastward (westward) intensification of SST trends in positive (negative) gradient models, leads to larger gradient magnitudes compared to observations. The wind-evaporation-SST (WES) feedback plays a predominant role in shaping the SST warming pattern in both groups of models, while the mean state SST bias has a secondary role. The Bjerknes feedback is weak in positive zonal SST gradient models, whereas both Bjerknes and WES feedbacks act to enhance the zonal SST gradient in models with negative gradient trends. This study underscores the dominant role of air-sea interaction processes in forming SST warming patterns and highlights the unrealistic zonal SST gradient in the equatorial Indian Ocean.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315184","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 Snow Decrement on the Tibetan Plateau in Early Spring of 2022","authors":"Chuying Deng,&nbsp;Xiuzhen Li,&nbsp;Yuan Zhao","doi":"10.1002/joc.8835","DOIUrl":"https://doi.org/10.1002/joc.8835","url":null,"abstract":"<div>\u0000 \u0000 <p>In early spring (March–April) of 2022, the snow depth on the Tibetan Plateau (TP) witnessed a historic decrement, breaking its records in the past few decades. The snow decrement was marked by an early beginning, a rapid pace of decline and extensive spatial coverage, which may play an important role in triggering the extreme events in the upcoming summer. This study investigated the underlying causes of this extreme snow decrement from the perspectives of local air–land interaction and crucial atmospheric circulations modulation. The extreme snow decrement can be attributed to a combination of factors, including an initial surplus in snow depth, anomalously high solar radiation influx, reduced precipitation and warm surface air temperature. Amongst these, the latter two factors were the key contributors leading to weakened snowfall (lowest) and increased snowmelt. Analysis of large-scale atmospheric circulation reveals the influence of a barotropically abnormal anticyclone (strongest) over the TP. The peripheral flow of this anticyclone suppressed the moisture supply, and the associated sinking motion (second strongest) enhanced the adiabatic heating (second highest). Further investigation suggests that this peculiar anticyclone might be linked to a robust positive North Atlantic Oscillation (NAO) signal. In conjunction with other favourable forcing and atmospheric conditions, the NAO triggered a wave train that propagated to the TP and contributed to the formation of the exceptional anticyclone.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315426","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":"Impact of the CMIP6 Model Resolution on the Future Behaviour of Wind-Driven Wave Climate for the North Indian Ocean","authors":"Athira Krishnan,&nbsp;S. Neetu","doi":"10.1002/joc.8842","DOIUrl":"https://doi.org/10.1002/joc.8842","url":null,"abstract":"<div>\u0000 \u0000 <p>We investigate the past and future variations in wind-driven wave climate over the North Indian Ocean (NIO) region utilising three climate models involved in the High-Resolution Model Intercomparison Project (HighResMIP) within the Coupled Model Intercomparison Project Phase 6 (CMIP6). We analyse the impact of horizontal grid resolution on the accuracy of reproducing past and future changes in wave climate. Wave climate simulated by Global Climate Model (GCM)-forced Wave Watch III (WWIII) simulation outputs from the historical (hist-1950) and future (highres-future) experiments are employed to depict the multi-resolution portrayal of wave climate and to assess any systematic differences arising from resolution enhancements. Compared with ERA5, the GCM with 50 km resolution simulates stronger waves. The pattern of underestimation and overestimation from ERA5 becomes more pronounced in both extent and magnitude as the GCM resolution decreases to 100 km and 250 km. These coarse-resolution models also exhibit deficiencies in representing inter-annual and inter-seasonal variability, particularly in regions impacted by Tropical Cyclones (TCs) such as the Southeastern Bay of Bengal (BoB), Andaman Sea, Southeastern Arabian Sea (AS), offshore of Western India and so forth. This study highlights the critical issue of relying on climate model data without adequately considering their coarse resolutions or inherent biases compared to observational data. In contrast to the historical wave climate, future projections suggest a decrease in 50-year return values (RV50) over the eastern regions and an increase in the western regions of the AS. Specifically, a 1-m rise in RV50 is projected for the Northwestern AS regions. According to the 50 km model simulation, significant changes in annual mean and maximum Significant Wave Height (SWH) and wind speed are observed in the Eastern AS and Southern BoB, where maximum wave heights are projected to decrease. In contrast, increased wave activity is anticipated in the future for the Northwestern AS and Western AS.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315398","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":"Long-Term Changes of Universal Thermal Climate Index (UTCI) Estimated From Weather Stations and Gradient-Boosted Decision Trees Throughout Japan","authors":"Ryoga Hiroki,&nbsp;Alvin C. G. Varquez,&nbsp;Do Ngoc Khanh,&nbsp;Ryza Rynazal,&nbsp;Florent Renard,&nbsp;Lucille Alonso,&nbsp;Manabu Kanda","doi":"10.1002/joc.8843","DOIUrl":"https://doi.org/10.1002/joc.8843","url":null,"abstract":"<p>Evaluating long-term changes in thermal comfort can be useful for considering measures against thermal-related health risks. In this study, spatio-temporal changes in thermal comfort, using the Universal Thermal Climate Index (UTCI), were calculated from observations at 140 weather stations across Japan for the 1980–2020 period. To derive the mean radiant temperature (MRT) values not readily measured at the stations but required in the estimation of UTCI, a machine-learning model (XGBoost) was developed. The model uses the station observations, coarse-resolution radiation data from the ERA-5 reanalyses dataset, and available globe temperature measurements as predictors. The trend of UTCI throughout Japan in summer was found to be significantly positive. Meanwhile, negative trends were found in stations located in northern areas during the winter. This suggests that not only heat stress risks but also cold stress risks should be given careful attention in colder regions. Lastly, a comparison of the estimated UTCI with prefecture-level daily summertime heat-stroke data reveals that the UTCI threshold above which heat-stroke cases rise drastically varies distinctly between warm and cold regions, with the latter having a lower threshold. These findings could contribute to the estimation of risks attributable to climate change and to better planning of climate-change-resilient cities.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8843","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315400","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":"Widespread Multi-Year Droughts in Italy: Identification and Causes of Development","authors":"Salvatore Pascale,&nbsp;Francesco Ragone","doi":"10.1002/joc.8827","DOIUrl":"https://doi.org/10.1002/joc.8827","url":null,"abstract":"<p>Multi-year droughts pose a significant threat to the security of water resources, putting stress on the resilience of hydrological, ecological and socioeconomic systems. Motivated by the recent multi-year drought that affected Southwestern Europe and Italy from 2021 to 2023, here we utilise two indices—the Standardised Precipitation Evapotranspiration Index (SPEI) and the Standardised Precipitation Index (SPI)—to quantify the temporal evolution of the percentage of Italian territory experiencing drought conditions in the period 1901–2023 and to identify Widespread Multi-Year Drought (WMYD) events, defined as multi-year droughts affecting at least 30% of Italy. Seven WMYD events are identified using two different precipitation datasets: 1921–1922, 1942–1944, 1945–1946, 2006–2008, 2011–2013, 2017–2018 and 2021–2023. Correlation analysis between the time series of Italian drought areas and atmospheric circulation indicates that the onset and spread of droughts in Italy are related to specific phases of the winter North Atlantic Oscillation (NAO), the Scandinavian Pattern (SCAND), East Atlantic/Western Russia (EAWR) pattern and the summer East Atlantic (EA) and East Atlantic/Western Russia (EAWR) patterns. Event-based analysis of these drought episodes reveals a variety of atmospheric patterns and combinations of the four teleconnection modes that contribute to persistently dry conditions in Italy during both winter and summer. This study offers new insights into the identification and understanding of the meteorological drivers of Italian WMYD events and serves as a first step toward a better understanding of the impacts of anthropogenic climate change on them.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8827","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315399","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}