Weather and Climate Extremes最新文献

{"title":"The opposite trends in precipitation total and extremes during two rain-seasons across Ethiopia, the Water Tower of Africa","authors":"Tewodros Addisu Yate ,&nbsp;Guoyu Ren","doi":"10.1016/j.wace.2025.100813","DOIUrl":"10.1016/j.wace.2025.100813","url":null,"abstract":"<div><div>This study assesses trends in precipitation total and extremes across Ethiopia from 1980 to 2019, using datasets of daily gauge observations. Following quality control and homogenization, daily precipitation data from 110 stations are gridded onto a 1° × 1° latitude-longitude grid cells. Precipitation anomaly percentage (PAP) and the Expert Team on Climate Change Detection and Indices (ETCCDI) indices are applied to represent precipitation total and extremes, respectively. Regional time series are constructed using area-weighted averages derived from the grid-level data. The Theil-Sen estimator and the modified Mann-Kendall test are employed to evaluate the statistical significance of trends at the 5 % level. The results indicate an annual and Jun–Sep seasonal increase in both precipitation total and extremes, characterized by rising frequency and intensity of extreme events. The Theil-Sen slope estimates a regional annual PAP increase of 0.92 % per decade, with a more pronounced rise of 4.6 % per decade for the Jun–Sep season (main precipitation season). Significant upward regional trends are observed in extreme indices such as RX1day, R95p, R99p, R10, R25, and R40 during the forty years. Spatial analysis highlights central, northwestern, and northeastern Ethiopia as areas experiencing robust increases in precipitation total and extremes. The observed rise in precipitation total is predominantly driven by increases in precipitation extremes within the region, as demonstrated by spatial correlations between precipitation total and extremes. Conversely, the Feb–May season (secondary precipitation season) exhibits significant regional decreases in precipitation total and extremes, particularly in northeastern, eastern, and southern areas. This includes declines in frequency-related indices (R5, R10, R25) and prolonged dry spells as measured by CDD. The causes for the increase in frequency and intensity of annual and Jun–Sep seasonal precipitation in Ethiopia over recent decades need to be investigated, though it is in accordance with the expectation that anthropogenic global warming can result in a rise in precipitation extremes over most regions of the world. However, the significant changes in precipitation observed in both Jun–Sep and Feb–May seasons are a cause for concern, as they may exert a major impact on sectors and areas of the country where these two seasons hold critical importance.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"50 ","pages":"Article 100813"},"PeriodicalIF":6.9,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145320857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling the effects of rainstorm adaptation strategies on maize yield among rural farmers in Ekiti State, Nigeria","authors":"Adewale Isaac Olutumise ,&nbsp;Lawrence Olusola Oparinde ,&nbsp;Akinyemi Gabriel Omonijo ,&nbsp;Igbekele Amos Ajibefun ,&nbsp;Taye Timothy Amos ,&nbsp;Yiseyon Sunday Hosu ,&nbsp;Julius Olumide Ilesanmi ,&nbsp;Dayo Temitope Oguntuase","doi":"10.1016/j.wace.2025.100814","DOIUrl":"10.1016/j.wace.2025.100814","url":null,"abstract":"<div><div>The increased recurrence of rainstorms remains a concern for productivity and economic development, especially in developing countries. Therefore, focusing on rainstorm adaptation and its impact on agricultural productivity will play a vital role in shaping policy decisions. Based on this fact, the study models the effects of rainstorm adaptation strategies on maize yield among rural farmers in Ekiti State, Nigeria, using an endogenous switching regression model. By the cross-sectional data of 293 farmers, the model accounts for selectivity bias. The result recognised that the rainstorm event had caused economic and environmental damage. However, the farmers do make proactive efforts to adapt to rainstorms in the area. The results further revealed that age, education, income, fertilizer applications, hill region, participation in training, and climate information determine the adoption of rainstorm adaptation decision-making. Our findings show that the adoption of rainstorm adaptation increased maize yield, as an average farmer who adopted it produced nearly 57 % more than farmers who did not adopt it. Again, adopters would have lost about 44 % value of yield if they had decided not to adopt, whereas approximately 28 % value of yield would have accrued by the non-adopters if they had adopted. Again, the number of assets owned, fertilizer application, climate belief, and participation in climate-related training are the significant factors explaining higher adopters’ yield. Therefore, the study suggests policy interventions that will promote the wide adoption of rainstorm adaptations. Also, improved weather forecasting services and better access to relevant climate information can help farmers make better decisions and plan their agricultural activities.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"50 ","pages":"Article 100814"},"PeriodicalIF":6.9,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Atmospheric Rivers intensify extreme precipitation and flooding across Australia","authors":"Sucheta Pradhan ,&nbsp;Conrad Wasko ,&nbsp;Murray C. Peel","doi":"10.1016/j.wace.2025.100812","DOIUrl":"10.1016/j.wace.2025.100812","url":null,"abstract":"<div><div>Atmospheric rivers (ARs) are narrow corridors of intense water vapor transport in the atmosphere. While the link between atmospheric rivers and extreme precipitation has been established across many regions of the world, the relationship between atmospheric rivers and flooding, the ultimate hazard resulting from extreme precipitation, remains poorly understood. Utilizing 467 Hydrologic Reference Stations (HRS) across Australia, the contribution of ARs to extreme precipitation and flooding is investigated by calculating the probability of occurrence of an AR on peak over threshold (POT) event days using different lag periods. By examining the tail behaviour of heavy precipitation and flooding caused by ARs, using the Generalized Pareto distribution (GPD), the magnitude to which ARs impact extreme events, and how this varies with event severity, is also quantified. Here, we find that southeast Australia has the highest AR concurrence (around 75–100 %) with extreme precipitation and streamflow events. The median magnitude of extremes is 20–70 % higher in the presence of an AR. In addition, the return periods of extreme flood and precipitation events of a given magnitude are on average 2 to 12 times shorter when they coincide with an AR compared to when they do not coincide with an AR. Our study highlights that ARs are a major factor in significantly increasing the frequency of extreme weather events in different regions of Australia. This suggests a need to incorporate AR impacts in hydrological modelling to enable better water resource management and flood risk assessment.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"50 ","pages":"Article 100812"},"PeriodicalIF":6.9,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impacts of climate change on extreme weather indices in Ecuadorian cities: A socioeconomic analysis","authors":"Diego Portalanza ,&nbsp;Malena Torres-Ulloa ,&nbsp;Eduardo Alava ,&nbsp;Jussen Facuy ,&nbsp;Cristian Zuluaga ,&nbsp;Rina Bucaram ,&nbsp;Angelica Durigon ,&nbsp;Simone Ferraz","doi":"10.1016/j.wace.2025.100810","DOIUrl":"10.1016/j.wace.2025.100810","url":null,"abstract":"<div><div>Climate change poses a significant threat to Ecuador, a nation characterized by diverse climates and geographical features. This study investigates the impacts of climate change on extreme weather events and socioeconomic variables across nine key Ecuadorian cities using the RegCM4 regional climate model and the Global Gridded Relative Deprivation Index (GRDI). The analysis includes historical trends and future projections under RCP2.6 and RCP8.5 scenarios for three extreme climatic indices: Consecutive Dry Days (CDD), Cold Nights (TN10p), and Warm Spell Duration Indicator (WSDI). Our findings indicate a consistent increase in CDD and WSDI, with significant decreases in TN10p across all cities over the past four decades, which are projected to continue under future climate scenarios. A Random Forest model was employed to explore the socio-economic impacts by predicting future changes in GRDI, highlighting how urban and rural deprivation might evolve in response to climatic changes. The results underscore the need for targeted adaptation strategies to address the unique vulnerabilities of each city and emphasize the critical role of land-use and land-cover changes (LULCC) in mitigating climate change impacts. This study provides essential insights for policymakers and stakeholders, emphasizing the urgency of integrating climate resilience into urban development to ensure sustainable futures for urban centers in Ecuador.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"50 ","pages":"Article 100810"},"PeriodicalIF":6.9,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating non-stationarity and uncertainty in design life levels based on climatological time series","authors":"Occitane Barbaux ,&nbsp;Philippe Naveau ,&nbsp;Nathalie Bertrand ,&nbsp;Aurélien Ribes","doi":"10.1016/j.wace.2025.100807","DOIUrl":"10.1016/j.wace.2025.100807","url":null,"abstract":"<div><div>This work focuses on inferring design life levels for extreme events under non-stationary conditions. Its objectives are twofold. The first one is to provide a single indicator that summarizes relevant and interpretable information about large values in time series, even when stationarity cannot be assumed. Classical risk indicators such as the 100-year return level become difficult to interpret in a non-stationary framework. To address this, we leverage the existing concept of the equivalent reliability (ER) level. Under stationarity, the ER level coincides with the classical return level, but it differs otherwise. More precisely, the ER level ensures that the probability of having all observations below the ER level during a specified design period is controlled. This definition ensures interpretability in terms of safety or failure risk. A second objective is to capture stochastic and estimation uncertainty, a key aspect in any risk analysis, as uncertainties due to inference schemes can grow with extreme intensities. We incorporate both by using the Bayesian predictive distribution. Although well known in Bayesian statistics, the predictive distribution has rarely been applied to climatological time series risk analysis.</div><div>Our approach is demonstrated on simulated data and on a case study of annual maxima of temperatures at a site in Southern France. To do so, a non-stationary Bayesian hierarchical extreme value model is used to combine data from 26 CMIP6 general circulation model simulations (SSP2-4.5, 1850-2100) with observations. The resulting predictive ER levels clearly indicate that non-stationarity over a design period of interest, as well as sampling and estimation uncertainty, have to be taken into account for risk assessment. For example, the 1000-year posterior predictive ER level for 2050-2100 is higher than any non-stationary 1000-year return level median estimate over the same period, reflecting the increasing risk due to the non-stationarity of the SSP 2-4.5 pathway.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"50 ","pages":"Article 100807"},"PeriodicalIF":6.9,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145254524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Projected impacts of climate and land use changes on streamflow extremes in the upper awash Basin, Ethiopia","authors":"Selamawit Haftu Gebresellase ,&nbsp;Zhiyong Wu ,&nbsp;Wada Idris Muhammad ,&nbsp;Gebremedhin Gebremeskel Haile","doi":"10.1016/j.wace.2025.100806","DOIUrl":"10.1016/j.wace.2025.100806","url":null,"abstract":"<div><div>This study examines the projected effects of climate and Land Use and Land Cover (LULC) changes on streamflow extremes in the Upper Awash Basin (UAB), Ethiopia. Using high-performing CMIP6 climate models under SSP4.5 and SSP8.5, and future LULC scenarios under Business-As-Usual (BAU) and Governance (GOV) for the 2030s and 2060s, the SWAT model was employed to simulate hydrological responses. Results revealed that climate change significantly affects streamflow extremes, with high-flow indices; Maximum High Flow (MHF), counts of High-Flow Pulses (HPC), and duration of High-Flow Pulses (HPD) showing pronounced increases, while low-flow indices; Minimum Low Flow (MLF), counts of low-flow pulses (LPC), and duration of low-flow pulses (LPD) exhibited substantial declines. For instance, under SSP8.5 in the 2060s, MHF, HPC, and HPD increased by 63.16 %, 26.85 %, and 14.96 %, respectively, whereas MLF, LPC, and LPD decreased by 67.11 %, 34.40 %, and 5.95 %. In contrast, LULC changes demonstrated statistically nonsignificant effects on both high- and low-flow indices across all scenarios and periods. The BAU scenario projected substantial urban and cropland expansion, resulting in decreased forest and shrubland areas, while the GOV scenario emphasized sustainable land management, controlling urban sprawl and increasing forest cover. Despite these differences, LULC-induced changes in streamflow extremes remained marginal compared to the overwhelming influence of climate change. This study highlights climate change as the dominant driver of future hydrological extremes in the UAB, emphasizing the need for climate-focused adaptation strategies to mitigate adverse impacts on water resources and livelihoods in the region.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"50 ","pages":"Article 100806"},"PeriodicalIF":6.9,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing global hindcast of extreme sea levels: Insights from a 65-year study","authors":"Pengcheng Wang ,&nbsp;Natacha B. Bernier","doi":"10.1016/j.wace.2025.100805","DOIUrl":"10.1016/j.wace.2025.100805","url":null,"abstract":"<div><div>Extreme sea levels (ESLs) are a leading cause of coastal hazards. Assessing risks and associated impacts requires reliable ESL statistics. These are typically derived from long but sparsely available tide-gauge records or through records obtained from long hindcasts. Here we present a 65-year global hindcast of hourly total sea levels that dynamically includes contributions from storm surges, tides, changes in water density (or baroclinicity) and their interactions. Evaluation shows good agreement between modelled and available observed sea levels, including extremes driven by extratropical and tropical cyclones. Significant improvements over other simulations result from our efforts in addressing underestimated reanalysis winds and incorporating baroclinicity, both of which have been overlooked in other global studies. The improvements can translate into reductions of return periods for given critical levels by decades. We therefore provide improved global estimates of ESL. In a first step toward developing seasonal forecast of flood risk, we also quantified ENSO-induced ESL modulations. The modulations show coherent spatial variabilities, consistent with ENSO-induced changes in the atmosphere and ocean. We also highlight the relevance of the often-overlooked neutral phase in regions where both El Niño and La Niña may suppress sea level variabilities.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"50 ","pages":"Article 100805"},"PeriodicalIF":6.9,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increased precipitation variability at multi-timescales in China since the 1960s","authors":"Xuyang Mo ,&nbsp;Wenxia Zhang ,&nbsp;Tianjun Zhou","doi":"10.1016/j.wace.2025.100808","DOIUrl":"10.1016/j.wace.2025.100808","url":null,"abstract":"<div><div>The frequency and intensity of precipitation have changed significantly in China as previously reported. A relevant behavior is the variability of precipitation, which describes temporal fluctuations of precipitation events. Yet it remains unclear how precipitation variability has changed at different timescales over China. In this study, we show that precipitation variability has increased significantly since the 1960s, averaging 2.3 % per decade across China. The increase exists across the synoptic to intraseasonal timescales. The increase in precipitation variability is evident in all seasons with the greatest rate in winter in percentage, which is approximately three times as much as that in summer. Regionally, precipitation variability has risen significantly in northwestern, northeastern, and southeastern China, but has decreased insignificantly along the wet-dry transition belt extending from the north to southwestern China. Compared to trends in mean and extreme precipitation, the increase of precipitation variability is more widespread and with greater magnitudes. The changes in the top 10 % extreme precipitation events contribute ∼75 % of the amplification of precipitation variability nationwide. In addition to long-term trend, summer precipitation variability over eastern China is modulated by the Pacific Decadal Oscillation. This study revealed robust increases in precipitation variability over China since the 1960s across different timescales, seasons, and regions, which have far-reaching impacts on droughts, floods, and water resource management.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"50 ","pages":"Article 100808"},"PeriodicalIF":6.9,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of aerosol forcing on the statistical attribution of heatwaves","authors":"Florian Kraulich,&nbsp;Peter Pfleiderer,&nbsp;Sebastian Sippel","doi":"10.1016/j.wace.2025.100803","DOIUrl":"10.1016/j.wace.2025.100803","url":null,"abstract":"<div><div>Heatwaves are becoming more frequent and intense due to anthropogenic climate change. Accurately attributing changes in their occurrence probability and intensity is crucial for effective climate change adaptation strategies. A common practice for calculating heatwave return periods in observations relies on extreme value statistics, where the Generalized Extreme Value distribution (GEV) shifts linearly with a covariate on global mean temperature (GMT) to capture the global forced response of climate change (‘standard method’, from now onwards). Although generally effective, this approach does not explicitly include regional aerosol trends, which strongly influence local heat extremes by reflecting solar radiation and altering cloud properties. Depending on the region, aerosol forcing trends can amplify or counteract greenhouse gas-induced warming. Here, we assess the impact of regional aerosol trends on statistical extreme event attribution of heatwaves using climate model simulations from the Community Earth System Model 2 (CESM2) large ensemble and single forcing large ensembles. To examine the impact of aerosols on extreme event trends, we introduce aerosol optical depth (AOD) as an additional covariate in the GEV model and compare this approach with the ‘standard method’. Our results show substantial biases of the ‘standard method’ in regions and periods of strong aerosol changes, particularly in industrial regions of North America, Central and Eastern Europe, and East Asia. Including AOD as a covariate significantly reduces these biases and improves return period estimates. This study highlights the importance of incorporating regional aerosol trends into statistical attribution frameworks to improve the estimation of return periods, and thus attribution statements.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"50 ","pages":"Article 100803"},"PeriodicalIF":6.9,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145059757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drought attribution of climate drivers using machine learning techniques","authors":"Milton S. Speer,&nbsp;Lance M. Leslie","doi":"10.1016/j.wace.2025.100801","DOIUrl":"10.1016/j.wace.2025.100801","url":null,"abstract":"","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"50 ","pages":"Article 100801"},"PeriodicalIF":6.9,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}