Pub Date : 2026-01-02DOI: 10.1016/j.wace.2026.100850
Muhammad Afzal , Thanh Mai , Shahbaz Mushtaq , Kathryn Reardon-Smith , Duc-Anh An-Vo
This paper addresses the critical issue of assessing, in a dynamic manner, the livelihood vulnerability of flood-prone rural communities in a developing country. The primary objective was to develop a framework for understanding the evolving nature of vulnerability to floods and to propose system-based intervention strategies to strengthen community resilience. Integrating a systems thinking approach with a sustainable livelihood framework, the study employs a case study in Rajanpur District, Pakistan—a region that has experienced significant flooding in recent decades. The research presents a conceptual model and its associated system archetypes of the community's livelihood system. The conceptual model highlights the underlying feedback structures that shape the district's vulnerability to livelihoods. The identified system archetypes reveal that current flood adaptation policies are maladaptive due to their unintended consequences that compromise the long-term effectiveness of interventions and sustainable management of livelihood resources. To avoid maladaptation and enhance the use of community livelihood capitals, policy efforts must shift from short-term fixes to designing and implementing long-term strategies that improve flood resilience and strengthen livelihood assets in the region. The present study offers valuable insights for reshaping adaptation policies in Pakistan and provides a foundation for knowledge sharing in other regions facing similar climate-related challenges.
{"title":"Assessing livelihood vulnerability in flood-prone communities through systems thinking and the sustainable livelihood framework: A case study of Rajanpur district, Pakistan","authors":"Muhammad Afzal , Thanh Mai , Shahbaz Mushtaq , Kathryn Reardon-Smith , Duc-Anh An-Vo","doi":"10.1016/j.wace.2026.100850","DOIUrl":"10.1016/j.wace.2026.100850","url":null,"abstract":"<div><div>This paper addresses the critical issue of assessing, in a dynamic manner, the livelihood vulnerability of flood-prone rural communities in a developing country. The primary objective was to develop a framework for understanding the evolving nature of vulnerability to floods and to propose system-based intervention strategies to strengthen community resilience. Integrating a systems thinking approach with a sustainable livelihood framework, the study employs a case study in Rajanpur District, Pakistan—a region that has experienced significant flooding in recent decades. The research presents a conceptual model and its associated system archetypes of the community's livelihood system. The conceptual model highlights the underlying feedback structures that shape the district's vulnerability to livelihoods. The identified system archetypes reveal that current flood adaptation policies are maladaptive due to their unintended consequences that compromise the long-term effectiveness of interventions and sustainable management of livelihood resources. To avoid maladaptation and enhance the use of community livelihood capitals, policy efforts must shift from short-term fixes to designing and implementing long-term strategies that improve flood resilience and strengthen livelihood assets in the region. The present study offers valuable insights for reshaping adaptation policies in Pakistan and provides a foundation for knowledge sharing in other regions facing similar climate-related challenges.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"51 ","pages":"Article 100850"},"PeriodicalIF":6.9,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145895033","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}
Pub Date : 2025-12-26DOI: 10.1016/j.wace.2025.100849
I. Manco , O.M. Feitosa , M. Raffa , P. Schiano , G. Rianna , P. Mercogliano
This study is aimed at investigating the spatial-time pattern of extreme daily precipitation events on the entire Italian peninsula using a k-means cluster analysis that is applied to high-resolution climate projections. Research analyzes data from the VHR-PRO_IT dataset with a resolution of 2.2 km and examines both historical (1981–2005) and future periods (2035–2065) under the concentration scenarios RCP4.5 and RCP8.5. The clustering methodology identifies 13 different precipitation patterns and illustrates the decisive influence of complex orography, geographical location and maritime influence in shaping extreme precipitation regimes. The results show considerable seasonal fluctuations in precipitation patterns, with the highest intensities being observed in winter, especially in mountain regions. Future projections indicate an increase in rainfall variability in the entire area, whereby the standard deviation under RCP4.5 scenarios increases by about 19 % and 17 % under RCP8.5 scenarios. One of the remarkable changes includes intensification of precipitation in the Eastern Alps and northern Apennin, while a decreasing trend is observed in Sicily, Sardinia, and generally along the Tyrrhenian coast during the Summer. The k-means clustering analysis highlights the variations in precipitation patterns across different regions of Italy, identifying areas most vulnerable to extreme daily events and linking them to potential large-scale changes associated with future shifts in atmospheric circulation patterns. The high-resolution data (2.2 km) enables the representation of mesoscale phenomena and regional variations, and the results provide data to support climate adaptation planning by mapping precipitation distribution changes under future climate scenarios (RCP4.5 and RCP8.5).
{"title":"Identifying recurring patterns of extreme daily precipitation using K-means algorithm: Uncovering spatial shift driven by climate change over the Italian Peninsula","authors":"I. Manco , O.M. Feitosa , M. Raffa , P. Schiano , G. Rianna , P. Mercogliano","doi":"10.1016/j.wace.2025.100849","DOIUrl":"10.1016/j.wace.2025.100849","url":null,"abstract":"<div><div>This study is aimed at investigating the spatial-time pattern of extreme daily precipitation events on the entire Italian peninsula using a k-means cluster analysis that is applied to high-resolution climate projections. Research analyzes data from the VHR-PRO_IT dataset with a resolution of 2.2 km and examines both historical (1981–2005) and future periods (2035–2065) under the concentration scenarios RCP4.5 and RCP8.5. The clustering methodology identifies 13 different precipitation patterns and illustrates the decisive influence of complex orography, geographical location and maritime influence in shaping extreme precipitation regimes. The results show considerable seasonal fluctuations in precipitation patterns, with the highest intensities being observed in winter, especially in mountain regions. Future projections indicate an increase in rainfall variability in the entire area, whereby the standard deviation under RCP4.5 scenarios increases by about 19 % and 17 % under RCP8.5 scenarios. One of the remarkable changes includes intensification of precipitation in the Eastern Alps and northern Apennin, while a decreasing trend is observed in Sicily, Sardinia, and generally along the Tyrrhenian coast during the Summer. The k-means clustering analysis highlights the variations in precipitation patterns across different regions of Italy, identifying areas most vulnerable to extreme daily events and linking them to potential large-scale changes associated with future shifts in atmospheric circulation patterns. The high-resolution data (2.2 km) enables the representation of mesoscale phenomena and regional variations, and the results provide data to support climate adaptation planning by mapping precipitation distribution changes under future climate scenarios (RCP4.5 and RCP8.5).</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"51 ","pages":"Article 100849"},"PeriodicalIF":6.9,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145845315","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}
Pub Date : 2025-12-16DOI: 10.1016/j.wace.2025.100848
Matthew L. Newell , Martin Drews , Andrea Böhnisch , Nanna Høgh Ravn , Morten Andreas Dahl Larsen
An increase in the frequency and severity of extreme weather events has been reported across the globe. These events threaten society through hazards like floods and droughts, underscoring the need to understand how such risks are evolving in a changing climate. Standardized methods have recently been introduced to assess the potential role of climate change for extreme events. The World Weather Attribution (WWA) offers a probabilistic framework to determine whether changes in the frequency and severity of extremes can be attributed to anthropogenic warming. Here we use this methodology to attribute an unprecedented rainfall event in Southern Denmark to anthropogenic climate change. On September 27, 2024, approx. 145 mm of rainfall fell over the city of Esbjerg, marking the highest daily rainfall on record for September. The event caused widespread flooding, disrupting transportation, damaging infrastructure, and affecting residential areas. This study draws on rainfall observations, reanalysis datasets, and climate model ensembles to assess the role of anthropogenic climate change. Notably, this is the first attribution study to apply ClimEx, a high-resolution, regional single-model initial-condition large ensemble (SMILE). The results of the analysis show that the rainfall event was 60 % (−20 %–540 %) more likely in the current climate compared to a pre-industrial climate, and that the intensity of the event increased by 10.2 % (−3.3 %–25.6 %) due to climate change. Our findings also indicate that the frequency and intensity of such events increase with further warming. Overall, this study highlights how hazards, exposure, and vulnerabilities contribute to risk in cities.
{"title":"Attribution of the 2024 record-breaking precipitation event in Southern Denmark to human-induced climate change","authors":"Matthew L. Newell , Martin Drews , Andrea Böhnisch , Nanna Høgh Ravn , Morten Andreas Dahl Larsen","doi":"10.1016/j.wace.2025.100848","DOIUrl":"10.1016/j.wace.2025.100848","url":null,"abstract":"<div><div>An increase in the frequency and severity of extreme weather events has been reported across the globe. These events threaten society through hazards like floods and droughts, underscoring the need to understand how such risks are evolving in a changing climate. Standardized methods have recently been introduced to assess the potential role of climate change for extreme events. The World Weather Attribution (WWA) offers a probabilistic framework to determine whether changes in the frequency and severity of extremes can be attributed to anthropogenic warming. Here we use this methodology to attribute an unprecedented rainfall event in Southern Denmark to anthropogenic climate change. On September 27, 2024, approx. 145 mm of rainfall fell over the city of Esbjerg, marking the highest daily rainfall on record for September. The event caused widespread flooding, disrupting transportation, damaging infrastructure, and affecting residential areas. This study draws on rainfall observations, reanalysis datasets, and climate model ensembles to assess the role of anthropogenic climate change. Notably, this is the first attribution study to apply ClimEx, a high-resolution, regional single-model initial-condition large ensemble (SMILE). The results of the analysis show that the rainfall event was 60 % (−20 %–540 %) more likely in the current climate compared to a pre-industrial climate, and that the intensity of the event increased by 10.2 % (−3.3 %–25.6 %) due to climate change. Our findings also indicate that the frequency and intensity of such events increase with further warming. Overall, this study highlights how hazards, exposure, and vulnerabilities contribute to risk in cities.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"51 ","pages":"Article 100848"},"PeriodicalIF":6.9,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785334","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}
Pub Date : 2025-12-16DOI: 10.1016/j.wace.2025.100847
Zikang Xing , Yunliang Li , Yufeng Dai , Jianhui Wei , Miaomiao Ma , Xuejun Zhang , Hui Gao , Harald Kunstmann
Lakes worldwide are experiencing intensifying extreme heat, with escalating ecological impacts. Despite lakes' role as thermal buffers to modulate air temperature is well-documented, the spatial propagation dynamics of lake effects remain poorly understood due to complex interactions of lake-atmosphere. This study proposes a synergistic WRF modeling and directional buffer analysis framework to investigate the spatial propagation dynamics and underlying physical mechanisms of lake-induced thermal regulation during extreme heat, focusing on Poyang Lake, China's largest freshwater lake. The results demonstrate a pronounced diurnal asymmetry in lake-induced thermal effects, with distinct spatial propagation characteristics between daytime and nighttime periods. Daytime cooling exhibits an intensity of −1.16 °C, with its influence confined within a 40 km radius, showing a relatively rapid attenuation rate of 0.28 °C per 10 km. In contrast, nighttime warming (+0.97 °C) propagates 1.75 times farther than its daytime counterpart, extending up to 70 km downwind while maintaining a slower attenuation rate of 0.13 °C per 10 km. Directional analysis reveals north-oriented propagation of lake thermal effects, influenced by prevailing southerly winds and lake-land breeze. Vertical profile analysis reveals distinct altitudinal penetration of lake-induced thermal effects, with daytime influences confined below 900 hPa while nighttime impacts extend up to 700 hPa. Daytime cooling extent is limited by turbulent mixing, whereas nighttime warming is enhanced by stable air conditioning and advective transport. The study underscores the role of lake-atmosphere interactions in mitigating regional climate extremes, providing critical insights for nature-based heat adaptation strategies in lake-rich regions. These findings advance the understanding of inland water bodies as active climate regulators under anthropogenic warming.
{"title":"Quantifying the spatial extent and attenuation of lake thermal regulation at diurnal scales under extreme heat","authors":"Zikang Xing , Yunliang Li , Yufeng Dai , Jianhui Wei , Miaomiao Ma , Xuejun Zhang , Hui Gao , Harald Kunstmann","doi":"10.1016/j.wace.2025.100847","DOIUrl":"10.1016/j.wace.2025.100847","url":null,"abstract":"<div><div>Lakes worldwide are experiencing intensifying extreme heat, with escalating ecological impacts. Despite lakes' role as thermal buffers to modulate air temperature is well-documented, the spatial propagation dynamics of lake effects remain poorly understood due to complex interactions of lake-atmosphere. This study proposes a synergistic WRF modeling and directional buffer analysis framework to investigate the spatial propagation dynamics and underlying physical mechanisms of lake-induced thermal regulation during extreme heat, focusing on Poyang Lake, China's largest freshwater lake. The results demonstrate a pronounced diurnal asymmetry in lake-induced thermal effects, with distinct spatial propagation characteristics between daytime and nighttime periods. Daytime cooling exhibits an intensity of −1.16 °C, with its influence confined within a 40 km radius, showing a relatively rapid attenuation rate of 0.28 °C per 10 km. In contrast, nighttime warming (+0.97 °C) propagates 1.75 times farther than its daytime counterpart, extending up to 70 km downwind while maintaining a slower attenuation rate of 0.13 °C per 10 km. Directional analysis reveals north-oriented propagation of lake thermal effects, influenced by prevailing southerly winds and lake-land breeze. Vertical profile analysis reveals distinct altitudinal penetration of lake-induced thermal effects, with daytime influences confined below 900 hPa while nighttime impacts extend up to 700 hPa. Daytime cooling extent is limited by turbulent mixing, whereas nighttime warming is enhanced by stable air conditioning and advective transport. The study underscores the role of lake-atmosphere interactions in mitigating regional climate extremes, providing critical insights for nature-based heat adaptation strategies in lake-rich regions. These findings advance the understanding of inland water bodies as active climate regulators under anthropogenic warming.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"51 ","pages":"Article 100847"},"PeriodicalIF":6.9,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785291","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}
Compound climate extremes have significant societal and ecological impacts, yet their drivers in tropical regions remain poorly understood. For example, although global evidence increasingly highlights interactions between heatwaves and precipitation, the specific mechanisms driving these compound events in Northern Australia remain poorly characterized, particularly the contrasting influence of atmospheric circulation and temperature-driven thermodynamic processes. Motivated by these gaps, this study investigates the interaction between heatwaves and precipitation bursts in Northern Australia during the pre- and post-monsoon seasons. We employ a vertically integrated moisture budget framework to systematically contrast precipitation bursts preceded by heatwaves with those occurring independently. Heatwave-associated bursts exhibit stronger and more prolonged convective activity, resulting in intensified peak precipitation and delayed maxima compared to independently occurring bursts. Vertical moisture advection is the dominant mechanism, accounting for over 70% of the variability in column-integrated moisture flux. A further decomposition reveals that the dynamic component of vertical advection — driven by circulation anomalies — plays a more substantial role than the thermodynamic component in driving these changes. These events coincide with anomalously low mean sea level pressure and enhanced cyclonic circulation, and are observed alongside sustained convective processes. Collectively, our findings highlight the role of atmospheric circulation in shaping these compounded heat and precipitation extremes in tropical Northern Australia.
{"title":"Precipitation bursts in northern Australia with and without preceding heatwaves","authors":"Sarthak Mohanty , Nikhil Garg , Nandini Ramesh , Mahesh Prakash","doi":"10.1016/j.wace.2025.100845","DOIUrl":"10.1016/j.wace.2025.100845","url":null,"abstract":"<div><div>Compound climate extremes have significant societal and ecological impacts, yet their drivers in tropical regions remain poorly understood. For example, although global evidence increasingly highlights interactions between heatwaves and precipitation, the specific mechanisms driving these compound events in Northern Australia remain poorly characterized, particularly the contrasting influence of atmospheric circulation and temperature-driven thermodynamic processes. Motivated by these gaps, this study investigates the interaction between heatwaves and precipitation bursts in Northern Australia during the pre- and post-monsoon seasons. We employ a vertically integrated moisture budget framework to systematically contrast precipitation bursts preceded by heatwaves with those occurring independently. Heatwave-associated bursts exhibit stronger and more prolonged convective activity, resulting in intensified peak precipitation and delayed maxima compared to independently occurring bursts. Vertical moisture advection is the dominant mechanism, accounting for over 70% of the variability in column-integrated moisture flux. A further decomposition reveals that the dynamic component of vertical advection — driven by circulation anomalies — plays a more substantial role than the thermodynamic component in driving these changes. These events coincide with anomalously low mean sea level pressure and enhanced cyclonic circulation, and are observed alongside sustained convective processes. Collectively, our findings highlight the role of atmospheric circulation in shaping these compounded heat and precipitation extremes in tropical Northern Australia.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"51 ","pages":"Article 100845"},"PeriodicalIF":6.9,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145730861","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}
Pub Date : 2025-12-11DOI: 10.1016/j.wace.2025.100846
Paul A. Davies , David L.A. Flack , Jennifer S.R. Pirret , Hayley J. Fowler
This study investigates the environmental conditions that resulted in the extreme rainfall and flash floods in the United Arab Emirates and Oman: 14–16 April 2024. We use a combination of numerical weather prediction modelling and observational analysis to examine the dynamics and thermodynamics of the event. Moisture convergence in the lower troposphere and a cut-off low pressure vortex coupled with high pressure over the northern Arabian Sea funnelled warm, moist air towards the Arabian Gulf. These dynamics lead to an environment that is not particularly unstable, but it is saturated in depth, with moist absolute unstable layers (MAULs) in and around areas of extreme rainfall.
We apply the concept of normalized gross moist stability alongside a recently proposed four-stage conceptual model in a spatial context. We identify large-scale indicators useful for augmenting forecast models, finding an association between MAUL depth, saturation fraction, and total rainfall. The presence of deep MAULs and a saturation fraction close to one are prerequisites for heavy rainfall enhancement in the hours preceding and during the rainfall peak.
We propose a new method to predict the characteristics of an extreme rainfall event using both the presence of MAULs and saturation fraction as a proxy for extremes, as either one on their own is not as beneficial. We infer that together these predictors can be used to discriminate between embedded convection in fronts versus isolated convective events producing the extremes.
{"title":"Application of the Davies four-stage conceptual model for life-threatening rainfall extremes on the April 2024 United Arab Emirates and Oman floods","authors":"Paul A. Davies , David L.A. Flack , Jennifer S.R. Pirret , Hayley J. Fowler","doi":"10.1016/j.wace.2025.100846","DOIUrl":"10.1016/j.wace.2025.100846","url":null,"abstract":"<div><div>This study investigates the environmental conditions that resulted in the extreme rainfall and flash floods in the United Arab Emirates and Oman: 14–16 April 2024. We use a combination of numerical weather prediction modelling and observational analysis to examine the dynamics and thermodynamics of the event. Moisture convergence in the lower troposphere and a cut-off low pressure vortex coupled with high pressure over the northern Arabian Sea funnelled warm, moist air towards the Arabian Gulf. These dynamics lead to an environment that is not particularly unstable, but it is saturated in depth, with moist absolute unstable layers (MAULs) in and around areas of extreme rainfall.</div><div>We apply the concept of normalized gross moist stability alongside a recently proposed four-stage conceptual model in a spatial context. We identify large-scale indicators useful for augmenting forecast models, finding an association between MAUL depth, saturation fraction, and total rainfall. The presence of deep MAULs and a saturation fraction close to one are prerequisites for heavy rainfall enhancement in the hours preceding and during the rainfall peak.</div><div>We propose a new method to predict the characteristics of an extreme rainfall event using both the presence of MAULs and saturation fraction as a proxy for extremes, as either one on their own is not as beneficial. We infer that together these predictors can be used to discriminate between embedded convection in fronts versus isolated convective events producing the extremes.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"51 ","pages":"Article 100846"},"PeriodicalIF":6.9,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145730868","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}
Pub Date : 2025-12-10DOI: 10.1016/j.wace.2025.100844
Ting Lv , Haiqing Yu , Hui Wang , Yingtao Zhu , Lv Lu
Accurate forecasting of typhoon-induced wave height (WH), which supports timely evacuation and informed emergency responses, is essential for the effectiveness of early warning systems. Despite recent advances in deep learning for WH forecasting, a critical gap persists: current models often fail to reliably predict rare but catastrophic extreme WH under typhoon conditions due to data scarcity. To address this challenge, we propose a physics-guided multi-scale attention framework, named the typhoon-induced wave height network (TWHN), which adopts a dual-branch architecture that separately captures wind sea and swell features. Unlike architectures that rely on initial WH inputs, TWHN forecasts WH directly from historical wind fields, thereby reducing error accumulation and supporting predictions at future time steps. To enhance the representation of extreme WH events, we introduce a tail-aware extreme value optimization (TEVO) strategy, which integrates a progressive training scheme to shift model focus from global patterns to tail data and a quantile-aware hybrid loss to penalize underestimation of high-magnitude waves. Additionally, a feature distribution smoothing mechanism is employed to stabilize training in data-sparse regimes by mitigating feature dominance from frequent samples. The model is trained, validated, and tested on WH records from 1982 to 2022, using a reanalysis dataset that includes 1 060 typhoons in the Northwest Pacific. Evaluation based on regional fields and nearshore station comparisons suggests that TWHN maintains strong potential for forecasting high-impact typhoon wave events. This work may provide implications for the advancement of operational wave forecasting and the support of risk decision-making in response to typhoon-induced marine hazards.
{"title":"A dual-branch typhoon-induced wave height forecasting network with tail-aware extreme value optimization","authors":"Ting Lv , Haiqing Yu , Hui Wang , Yingtao Zhu , Lv Lu","doi":"10.1016/j.wace.2025.100844","DOIUrl":"10.1016/j.wace.2025.100844","url":null,"abstract":"<div><div>Accurate forecasting of typhoon-induced wave height (WH), which supports timely evacuation and informed emergency responses, is essential for the effectiveness of early warning systems. Despite recent advances in deep learning for WH forecasting, a critical gap persists: current models often fail to reliably predict rare but catastrophic extreme WH under typhoon conditions due to data scarcity. To address this challenge, we propose a physics-guided multi-scale attention framework, named the typhoon-induced wave height network (TWHN), which adopts a dual-branch architecture that separately captures wind sea and swell features. Unlike architectures that rely on initial WH inputs, TWHN forecasts WH directly from historical wind fields, thereby reducing error accumulation and supporting predictions at future time steps. To enhance the representation of extreme WH events, we introduce a tail-aware extreme value optimization (TEVO) strategy, which integrates a progressive training scheme to shift model focus from global patterns to tail data and a quantile-aware hybrid loss to penalize underestimation of high-magnitude waves. Additionally, a feature distribution smoothing mechanism is employed to stabilize training in data-sparse regimes by mitigating feature dominance from frequent samples. The model is trained, validated, and tested on WH records from 1982 to 2022, using a reanalysis dataset that includes 1 060 typhoons in the Northwest Pacific. Evaluation based on regional fields and nearshore station comparisons suggests that TWHN maintains strong potential for forecasting high-impact typhoon wave events. This work may provide implications for the advancement of operational wave forecasting and the support of risk decision-making in response to typhoon-induced marine hazards.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"51 ","pages":"Article 100844"},"PeriodicalIF":6.9,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145730872","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}
Pub Date : 2025-12-06DOI: 10.1016/j.wace.2025.100843
Md. Babul Miah , Jong-Yeon Park , Min-Uk Lee , Woojin Jeon , Young-Hwa Byun , Hyun Min Sung , Jin Gi Hong , Md. Jalal Uddin , Sanjit Kumar Mondal
The Global Monsoon Areas (GMAs), home to over half of the world's population, face escalating socio-economic risks from extreme precipitation events intensified by rising atmospheric carbon dioxide (CO2). While previous studies have examined the irreversibility of the climate system following carbon neutrality, most have focused on single carbon neutrality scenarios with limited attention to these vulnerable areas. This study assesses the irreversibility of extreme precipitation intensity across seven GMA sub-regions under eight future scenarios, incorporating four carbon neutrality targets and two reduction rates, using simulations from a state-of-the-art climate model. Our results reveal that extreme precipitation intensity exhibits irreversible behavior in response to carbon neutrality forcing, failing to return to its initial level even when atmospheric CO2 is reduced. This irreversibility is particularly pronounced when carbon neutrality timing is delayed, and the emission reduction rate is slow. Moreover, the irreversible response is nonlinear to the magnitude of carbon forcing, leading to distinct regional vulnerabilities, with some areas experiencing sharp increases in irreversibility by even small delays in reaching carbon neutrality. This region-specific behavior is largely attributed to increases in mean and variability of precipitation linked to irreversible El Niño-like warming and interhemispheric differential warming. Moisture budget analysis further shows that the intensified precipitation arises from the relative influence of thermodynamic (moisture flux) and dynamic (wind) drivers across regions. These findings highlight the urgency of rapid policy implementation in vulnerable regions and can provide a scientific basis for developing regional adaptation strategies to mitigate growing extreme precipitation risks.
{"title":"Irreversibility of extreme precipitation intensity in global monsoon areas under multiple carbon neutrality scenarios","authors":"Md. Babul Miah , Jong-Yeon Park , Min-Uk Lee , Woojin Jeon , Young-Hwa Byun , Hyun Min Sung , Jin Gi Hong , Md. Jalal Uddin , Sanjit Kumar Mondal","doi":"10.1016/j.wace.2025.100843","DOIUrl":"10.1016/j.wace.2025.100843","url":null,"abstract":"<div><div>The Global Monsoon Areas (GMAs), home to over half of the world's population, face escalating socio-economic risks from extreme precipitation events intensified by rising atmospheric carbon dioxide (CO<sub>2</sub>). While previous studies have examined the irreversibility of the climate system following carbon neutrality, most have focused on single carbon neutrality scenarios with limited attention to these vulnerable areas. This study assesses the irreversibility of extreme precipitation intensity across seven GMA sub-regions under eight future scenarios, incorporating four carbon neutrality targets and two reduction rates, using simulations from a state-of-the-art climate model. Our results reveal that extreme precipitation intensity exhibits irreversible behavior in response to carbon neutrality forcing, failing to return to its initial level even when atmospheric CO<sub>2</sub> is reduced. This irreversibility is particularly pronounced when carbon neutrality timing is delayed, and the emission reduction rate is slow. Moreover, the irreversible response is nonlinear to the magnitude of carbon forcing, leading to distinct regional vulnerabilities, with some areas experiencing sharp increases in irreversibility by even small delays in reaching carbon neutrality. This region-specific behavior is largely attributed to increases in mean and variability of precipitation linked to irreversible El Niño-like warming and interhemispheric differential warming. Moisture budget analysis further shows that the intensified precipitation arises from the relative influence of thermodynamic (moisture flux) and dynamic (wind) drivers across regions. These findings highlight the urgency of rapid policy implementation in vulnerable regions and can provide a scientific basis for developing regional adaptation strategies to mitigate growing extreme precipitation risks.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"51 ","pages":"Article 100843"},"PeriodicalIF":6.9,"publicationDate":"2025-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145689977","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}
Pub Date : 2025-12-04DOI: 10.1016/j.wace.2025.100842
Hannah R. Bourbon , Francine Machin , Pandora Hope , Brenda Mackie , Eric Lede
There is a proliferation of Extreme Event Attribution (EEA) science studies that quantify to what extent anthropogenic climate change influences extreme events. To date, no evidence explores how EEA may be used in decision-making contexts, across jurisdictions and governments, within Australia. Understanding this will allow targeted capability development, to ensure EEA supports effective climate risk decision-making. This study closes this knowledge gap and contributes to a novel understanding of EEA use and needs in a decision-making context within Australia, aligned with objectives: (1) Identifying decision-maker familiarity and use of EEA for extreme heat and rainfall events and (2) Understanding how decision-making needs for EEA vary across geographies, climates and jurisdictions. Forty-three diverse decision-makers were interviewed in Temperate South-Eastern and Tropical Northern regions of Australia, and at the federal level. Five key areas to improve EEA communication and increase uptake in decision-making contexts were identified under the categories: Language, Methodology, Impact Linkages, Action-Oriented Communication and Scientific Comprehension. Results demonstrate varied EEA needs across regions and scales, and reveal that despite high familiarity with EEA, it is not widely used for decision-making. Challenges preventing regional decision-maker use of EEA included few local level EEA studies, none available in Northern Australia and the need for improved EEA communication in this region. EEA is being used to increase climate risk understanding, but Action-Oriented Communication could allow EEA to also drive adaptation and mitigation decisions. Recognising and addressing the identified areas for improvement will strengthen EEA delivery to support diverse climate risk decision-making contexts.
{"title":"Understanding decision-maker needs for extreme event attribution science","authors":"Hannah R. Bourbon , Francine Machin , Pandora Hope , Brenda Mackie , Eric Lede","doi":"10.1016/j.wace.2025.100842","DOIUrl":"10.1016/j.wace.2025.100842","url":null,"abstract":"<div><div>There is a proliferation of Extreme Event Attribution (EEA) science studies that quantify to what extent anthropogenic climate change influences extreme events. To date, no evidence explores how EEA may be used in decision-making contexts, across jurisdictions and governments, within Australia. Understanding this will allow targeted capability development, to ensure EEA supports effective climate risk decision-making. This study closes this knowledge gap and contributes to a novel understanding of EEA use and needs in a decision-making context within Australia, aligned with objectives: (1) Identifying decision-maker familiarity and use of EEA for extreme heat and rainfall events and (2) Understanding how decision-making needs for EEA vary across geographies, climates and jurisdictions. Forty-three diverse decision-makers were interviewed in Temperate South-Eastern and Tropical Northern regions of Australia, and at the federal level. Five key areas to improve EEA communication and increase uptake in decision-making contexts were identified under the categories: Language, Methodology, Impact Linkages, Action-Oriented Communication and Scientific Comprehension. Results demonstrate varied EEA needs across regions and scales, and reveal that despite high familiarity with EEA, it is not widely used for decision-making. Challenges preventing regional decision-maker use of EEA included few local level EEA studies, none available in Northern Australia and the need for improved EEA communication in this region. EEA is being used to increase climate risk understanding, but Action-Oriented Communication could allow EEA to also drive adaptation and mitigation decisions. Recognising and addressing the identified areas for improvement will strengthen EEA delivery to support diverse climate risk decision-making contexts.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"51 ","pages":"Article 100842"},"PeriodicalIF":6.9,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145690053","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}
Pub Date : 2025-12-01DOI: 10.1016/j.wace.2025.100838
Leibin Wang , Robert V. Rohli , Qigen Lin , Yanzhao Zhou , Siyan Dong , Shikai Song , Qiang Liu , Xiaodong Yan
Exposure to record-breaking heatwaves represents a significant and growing challenge for human health and societal well-being in a changing climate. Comprehending the risks of future exposure to record-breaking heatwaves is vital for devising effective mitigation strategies. However, population data, a key determinant in projecting future exposure risks, has rarely been scrutinized for the uncertainty it introduces into these projections. This study investigates population exposure risks to record-breaking heatwaves from 2020 to 2 100 using four population datasets (ECNU, Lund, NASA SEDAC, and Tsinghua) under various IPCC AR6 shared socioeconomic pathways (SSPs: 1–2.6, 2–4.5, 3–7.0, and 5–8.5). Results indicate that by the 2090s, approximately 0.9 billion, 2 billion, 4.8 billion, and 4 billion people per year will be exposed to record-breaking heatwaves under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, accounting for about 10 %, 21 %, 42 %, and 50 % of the total population, respectively. Key risk areas include East Asia, South Asia, Western and Central Europe, the Mediterranean coast, West and East Africa, and the Northeastern United States. Our results also demonstrate good consistency in global population estimates across the datasets under different SSPs, except for Lund, which tends to predict a higher global population than the other datasets by about 8 % in SSP2 and SSP3. The Kappa test results reveal that, in the context of global population distribution, while the datasets of ECNU and Tsinghua, as well as Lund and Tsinghua, display a strong degree of spatial consistency, other dataset combinations show only a moderate level of agreement. Notably, at the subcontinental level, significant disparities emerge in the projected population sizes and distributions across different population projections, and over time, this gap is widening. This will have a significant impact on the estimation of future population exposure. For example, in the Northern Hemisphere mid-to-high latitudes and the Australian region, the ECNU dataset forecasts a higher population growth rate than the other datasets. Subsequently, a similar trend is observed in the projections of population exposure to record-breaking heatwaves. These findings highlight the variability in regional risk projections across different population datasets, providing valuable insights for future population-related risk assessments and informing targeted mitigation efforts.
{"title":"Dissimilar global record-breaking heatwave exposure driven by divergent population projections within shared socioeconomic pathways","authors":"Leibin Wang , Robert V. Rohli , Qigen Lin , Yanzhao Zhou , Siyan Dong , Shikai Song , Qiang Liu , Xiaodong Yan","doi":"10.1016/j.wace.2025.100838","DOIUrl":"10.1016/j.wace.2025.100838","url":null,"abstract":"<div><div>Exposure to record-breaking heatwaves represents a significant and growing challenge for human health and societal well-being in a changing climate. Comprehending the risks of future exposure to record-breaking heatwaves is vital for devising effective mitigation strategies. However, population data, a key determinant in projecting future exposure risks, has rarely been scrutinized for the uncertainty it introduces into these projections. This study investigates population exposure risks to record-breaking heatwaves from 2020 to 2 100 using four population datasets (ECNU, Lund, NASA SEDAC, and Tsinghua) under various IPCC AR6 shared socioeconomic pathways (SSPs: 1–2.6, 2–4.5, 3–7.0, and 5–8.5). Results indicate that by the 2090s, approximately 0.9 billion, 2 billion, 4.8 billion, and 4 billion people per year will be exposed to record-breaking heatwaves under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, accounting for about 10 %, 21 %, 42 %, and 50 % of the total population, respectively. Key risk areas include East Asia, South Asia, Western and Central Europe, the Mediterranean coast, West and East Africa, and the Northeastern United States. Our results also demonstrate good consistency in global population estimates across the datasets under different SSPs, except for Lund, which tends to predict a higher global population than the other datasets by about 8 % in SSP2 and SSP3. The Kappa test results reveal that, in the context of global population distribution, while the datasets of ECNU and Tsinghua, as well as Lund and Tsinghua, display a strong degree of spatial consistency, other dataset combinations show only a moderate level of agreement. Notably, at the subcontinental level, significant disparities emerge in the projected population sizes and distributions across different population projections, and over time, this gap is widening. This will have a significant impact on the estimation of future population exposure. For example, in the Northern Hemisphere mid-to-high latitudes and the Australian region, the ECNU dataset forecasts a higher population growth rate than the other datasets. Subsequently, a similar trend is observed in the projections of population exposure to record-breaking heatwaves. These findings highlight the variability in regional risk projections across different population datasets, providing valuable insights for future population-related risk assessments and informing targeted mitigation efforts.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"50 ","pages":"Article 100838"},"PeriodicalIF":6.9,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145575309","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}
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