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Impact of extremely high temperature on future photovoltaic power potential over East Asia 极高温对东亚未来光伏发电潜力的影响

IF 6.9 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2026-01-21 DOI: 10.1016/j.wace.2026.100859

Changyong Park , Ana Juzbašić , Dong-Hyun Cha , Seung-Ki Min , Joong-Bae Ahn , Eun-Chul Chang , Young-Hwa Byun , Youngeun Choi

As global warming intensifies, the frequency and intensity of extremely high temperatures are expected to increase. This will impact the production of photovoltaics (PVs), which are increasingly adopted as an effective alternative to replace fossil fuel–based energy sources and reduce CO₂ emissions. Furthermore, extremely high temperature days account for a considerable proportion of days with high PV power potential (PVpot). Therefore, this study investigates changes in PVpot on future extremely high temperature days over East Asia, a region with high greenhouse gas emissions and vulnerability to extreme climatic events. The East Asia–averaged PVpot for extremely high temperature days was estimated to decrease across all scenarios and future periods. The East Asia–averaged PVpot for extremely high temperature days was predicted to decrease more substantially toward the late 21st century, with a larger magnitude of decrease expected under the high–carbon emissions scenario compared to the low–carbon emissions scenario. By the mid–and late 21st century, PVpot for extremely high temperature days was projected to decrease in PV hotspot areas, particularly in the regions of northern China and southern Mongolia, by up to −7.2 %. The signs of PVpot projections vary across sub–regions under summer mean conditions, while on extremely high temperature days, PVpot is consistently expected to decrease in all regions. This suggests that extremely high temperatures further intensify the decrease in PVpot. Moreover, under extremely high-temperature conditions, near-surface air temperature has been identified as the primary driver of projected decreases in PVpot among the climate variables considered; its influence is expected to intensify over time, thereby accelerating PVpot decreases under the high–carbon emissions scenario. Based on the findings, this study is expected to provide new insights for the development of renewable energy policies in a future where extremely high temperatures are projected to increase.

随着全球变暖的加剧，极端高温的频率和强度预计会增加。这将影响光伏发电（pv）的生产，光伏发电越来越多地被采用为替代化石燃料能源和减少二氧化碳排放的有效替代品。此外，极高温日占高PV功率势（PVpot）日的相当大比例。因此，本研究探讨了东亚地区未来极高温日数的PVpot变化，东亚地区是温室气体排放高、易受极端气候事件影响的地区。在所有情景和未来时期，东亚平均极高温日的PVpot估计都在减少。东亚极高温日数的平均PVpot在21世纪后期的下降幅度更大，且高碳排放情景下的下降幅度大于低碳排放情景。到21世纪中后期，PV热点地区（特别是中国北部和蒙古南部地区）的极高温日PVpot预计将减少7.2%。在夏季平均条件下，各子区域的PVpot预估迹象有所不同，而在极端高温天气，预计所有区域的PVpot都会持续下降。这表明极端高温进一步加剧了PVpot的下降。此外，在极端高温条件下，在考虑的气候变量中，近地表气温已被确定为预估PVpot减少的主要驱动因素；预计其影响将随着时间的推移而增强，从而在高碳排放情景下加速PVpot的下降。基于这些发现，这项研究有望为未来可再生能源政策的发展提供新的见解，预计未来极端高温将会增加。

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引用次数: 0

Statistics of Cloud-to-Ground Lightning Activity over North China during 2009–2023 2009-2023年华北地区云对地闪电活动统计

IF 6.9 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2026-01-14 DOI: 10.1016/j.wace.2026.100856

Yueyao Li , Xiaopeng Cui , Yun Chen , Wen Bao , Qing Lin

This study analyzes the spatiotemporal distribution and peak current (PC) characteristics of cloud-to-ground lightning (CG) over North China (NC) from 2009 to 2023, based on observations from the Advanced Directional Thunderstorm Detector (ADTD) network. The results show that 4,294,310 CG flashes are detected over the 15-year period; approximately 87 % are negative CG flashes (NCG). Approximately 48 % of multi-stroke NCG contain at least one subsequent stroke with a PC exceeding that of the first stroke. The spatial distribution of CG in NC is influenced by local topography, with two density maxima located in the western mountains and the northeastern mountainous fringe. Positive CG flashes (PCG) generally concentrate along mountain–plain transition zones with steep terrain gradients in western and northern NC. CG activity exhibits pronounced interannual variability: NCG frequency decreases significantly from 2013 to 2020, which leads to a marked increase in the proportion of PCG (P_PCG). This interannual change may be largely attributed to the implementation of regional air pollution control measures that reduce aerosol concentrations; such reductions may alter cloud microphysics and thereby contribute to the observed CG trends. Monthly CG variability is strongly tied to monsoon activity: CG frequency peaks in the warm season, whereas P_PCG is higher in the cold season. More than half of thunderstorm days (TSD) in NC occur in summer. Thunderstorms typically initiate over mountains in the afternoon and propagate eastward onto the NC Plain.

基于先进定向雷暴探测器（ADTD）网络观测资料，分析了2009 - 2023年华北地区云对地闪电（CG）的时空分布和峰值电流（PC）特征。结果表明，在15年的时间里，共检测到4294310次CG闪光；约87%为负CG闪烁（NCG）。大约48%的多冲程NCG包含至少一个后续冲程，其PC值超过第一个冲程。华北地区植被密度的空间分布受局地地形的影响，在西部山区和东北部山区边缘有两个密度最大值。正CG闪光（PCG）一般集中在西部和北部陡峭地形梯度的山地-平原过渡带。CG活动具有明显的年际变化特征：2013 - 2020年NCG频率显著降低，导致PCG （PPCG）比例显著增加。这种年际变化可能主要归因于区域空气污染控制措施的实施，这些措施降低了气溶胶浓度；这种减少可能改变云微物理，从而有助于观测到的CG趋势。月平均气压变化与季风活动密切相关：平均气压频率在暖季达到峰值，而平均气压频率在冷季较高。全国雷暴日数的一半以上发生在夏季。雷暴通常在下午从山区开始，向东传播到北卡平原。

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引用次数: 0

Tidal, hydrological and meteorological contributions to high-water level events in the Saint Lawrence River Estuary: Local responses to regional drivers 潮汐、水文和气象对圣劳伦斯河河口高水位事件的贡献：对区域驱动因素的局部响应

IF 6.9 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2026-01-13 DOI: 10.1016/j.wace.2026.100852

Silvia Innocenti , Marianne Fortier , Pascal Matte , Caroline Sevigny , Remi Gosselin , Olivier Champoux

Extreme water levels in estuaries exhibit considerable variability on multiple spatial and temporal scales, driven by complex responses to coastal, hydrological, meteorological, geological, and anthropogenic factors. These factors complicate the prediction of high-water level events and their characteristics. Although extensive literature exists on hydroclimatic and coastal extremes, few studies conduct comprehensive statistical analyses that jointly consider multiple drivers and the spatiotemporal variability of high-water-level events in estuaries. This study addresses these gaps by developing a robust statistical framework to identify, characterize and attribute local and regional high-water-level events in the St. Lawrence River Estuary (Canada) over the period 1980–2023. Building on existing approaches, a Generalized Additive Model (GAM) formulation of non-stationary harmonic regression is used to decompose the water level variability at 11 gauging stations, with automated selection of covariates and tidal constituents. This decomposition quantifies the relative contributions of the underlying processes, enabling event classification according to their dominant coastal, tidal, or fluvial drivers. Distinct spatial patterns of tidal and non-tidal processes are observed along the fluvial estuary, and a specific transition zone is identified between dominant tidal and fluvial influences. The results indicate that non-stationary dynamics are distinct in different tidal and non-tidal frequency bands. The resulting event classification also demonstrated a different landward shift from coastal to hydrological drivers for tidal and non-tidal non-stationarity. These findings guide the statistical analysis and configuration of the hydrodynamic models used in meteorological forecasting, climate projections, and other specific applications.

河口极端水位在沿海、水文、气象、地质和人为因素的复杂响应下，在多个时空尺度上表现出相当大的变动性。这些因素使高水位事件及其特征的预测复杂化。尽管有大量关于水文气候和海岸极端事件的文献，但很少有研究进行综合统计分析，共同考虑河口高水位事件的多个驱动因素和时空变异。本研究通过开发一个强大的统计框架来识别、表征和属性1980-2023年期间圣劳伦斯河河口（加拿大）本地和区域高水位事件，从而解决了这些差距。在现有方法的基础上，采用非平稳调和回归的广义加性模型（GAM）公式对11个测量站的水位变化进行分解，并自动选择协变量和潮汐成分。这种分解量化了潜在过程的相对贡献，使事件能够根据其主要的海岸、潮汐或河流驱动因素进行分类。在河流河口沿线，潮汐和非潮汐过程具有明显的空间格局，并在优势潮汐和河流影响之间确定了一个特定的过渡带。结果表明，在不同的潮汐和非潮汐频带上，非平稳动力是明显的。由此产生的事件分类也显示了潮汐和非潮汐非平稳性从沿海向水文驱动的不同陆地转移。这些发现指导了用于气象预报、气候预估和其他具体应用的水动力模式的统计分析和配置。

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引用次数: 0

A new class of climate hazard metrics and its demonstration: revealing a ten-fold increase of extreme heat over Europe 一种新的气候危害指标及其论证：揭示了欧洲极端高温的十倍增长

IF 8 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2026-01-13 DOI: 10.1016/j.wace.2026.100855

Gottfried Kirchengast, Stephanie J. Haas, Jürgen Fuchsberger

引用次数: 0

Diurnal evolution of synergistic interactions between urban heat islands and heat waves: An extreme heat wave case study in Seoul, South Korea 城市热岛与热浪协同作用的日演化：以韩国首尔的极端热浪为例

IF 6.9 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2026-01-09 DOI: 10.1016/j.wace.2026.100854

Kyeongjoo Park, Jong-Jin Baik

The synergistic interactions between urban heat islands (UHIs) and heat waves (HWs) refer to a phenomenon that UHIs are intensified during HWs, resulting in a greater temperature increase due to HWs in urban areas than in rural areas. Despite significant variations of the UHI–HW synergies on a diurnal timescale, their key physical processes are still not clearly understood. This study examines the diurnal evolution of the UHI–HW synergies and its underlying physical processes. For this, we simulate an extreme HW event with strong UHI–HW synergies in Seoul, South Korea using the Weather Research and Forecasting (WRF) model. The UHI–HW synergies rapidly strengthen in early evening and diminish in early morning, similar to the diurnal pattern found in many large cities. In early evening, the rural diabatic cooling is greatly enhanced under clearer skies during HW while the increases in both urban stored heat release and urban turbulent mixing result in only a slight change in urban diabatic heating. These contrasting responses are primarily responsible for the strengthening of the UHI–HW synergies. In early morning, the warm air advection from the rural residual layer by subsidence significantly increases under HW while subsidence rarely occurs in the urban boundary layer. These different responses to HW are mainly responsible for the weakening of the UHI–HW synergies. This study underlines the importance of differing changes in urban and rural near-surface thermodynamic processes during HWs on the temporal evolution of the UHI–HW synergies.

城市热岛与热浪的协同作用是指热浪期间城市热岛的强度增强，导致城市热岛的增温幅度大于农村热岛。尽管高温-高温协同效应在昼夜时间尺度上存在显著变化，但其关键物理过程仍未被清楚地了解。本研究探讨了高强度-高强度协同作用的昼夜演变及其潜在的物理过程。为此，我们使用天气研究与预报（WRF）模型模拟了韩国首尔发生的具有强烈超高热和高温协同效应的极端热浪事件。超高热量-高热量协同效应在傍晚迅速增强，在清晨减弱，这与许多大城市的昼夜模式相似。傍晚时分，天气晴朗时，农村的非绝热冷却大大增强，而城市蓄热释放和城市湍流混合的增加导致城市非绝热加热变化不大。这些截然不同的应对措施是加强高保健和高保健协同作用的主要原因。清晨，HW下下沉的农村残余层暖空气平流明显增加，而城市边界层很少发生下沉。这些对高热量的不同反应是高热量-高热量协同效应减弱的主要原因。本研究强调了高温期间城市和农村近地表热力过程的不同变化对高温-高温协同作用时间演化的重要性。

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引用次数: 0

Mechanisms of two types of summer persistent extreme precipitation events in the northeastern Tibetan Plateau 青藏高原东北部两类夏季持续性极端降水事件的发生机制

IF 6.9 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2026-01-07 DOI: 10.1016/j.wace.2026.100853

Qiaohua Liu , Lun Li

The northeastern Tibetan Plateau (TP) features complex terrain, and persistent extreme precipitation events (PEPEs) are key factors inducing landslides and mudflows in the northeastern TP and its downstream regions. A comprehensive understanding of PEPEs mechanisms is crucial but remains insufficient. This study investigates PEPEs characteristics and underlying mechanisms over the northeastern TP from a synoptic perspective, by objectively classifying PEPEs into two distinct types. Type1 (thermally triggered) develops in anomalously warm and moist environments across the TP, accompanied by a localized quasi-stationary shallow trough over the northeastern TP. Convection is initiated by thermodynamic forcing, wherein latent heating dominantly increases the potential vorticity (PV) in the mid-lower troposphere, enhancing the trough and thereby precipitation. Type1 tends to develop more rapidly and persist longer compared with Type2. Type2 (dynamically forced) is closely associated with the quasi-barotropic cold trough in mid-high latitudes, developing in an overall anomalously cold and dry environment over the TP, with moisture concentrated merely in the northeast. Precipitation is triggered by intense dynamical forcing east of the trough. As the trough moves eastward, the intrusion of high-PV air from the upper troposphere enhances the cold trough through horizontal and vertical advection. The precipitation evolves along with the eastward movement of the deep trough, presenting steadier and temporally symmetrical variation relative to the peak time. The results provide knowledge about the evolution mechanisms of the two types of PEPEs in the northeastern TP triggered in different environments, favoring the PEPEs forecast and disaster prevention over the TP and downstream regions.

青藏高原东北部地形复杂，持续极端降水事件（PEPEs）是诱发青藏高原东北部及其下游地区滑坡和泥石流的关键因素。对PEPEs机制的全面了解至关重要，但仍然不够。本文从天气学的角度，客观地将青藏高原东北部的pepe分为两种类型，探讨了pepe的特征及其形成机制。第1型（热触发型）在整个青藏高原异常温暖潮湿的环境中发展，并伴随着青藏高原东北部的局部准静止浅槽。对流是由热力强迫引发的，其中潜热主要增加对流层中下层的位涡量（PV），从而增强槽，从而增强降水。与2型相比，1型往往发展得更快，持续时间更长。第2型（动力强迫）与中高纬准正压冷槽密切相关，在青藏高原上空整体异常寒冷干燥的环境中发展，水汽仅集中在东北。降水是由低压槽以东强烈的动力强迫触发的。随着槽向东移动，来自对流层上层的高pv气流通过水平和垂直平流增强了冷槽。降水随深槽东移而演变，相对于峰值时间呈现更为稳定和时间对称的变化。研究结果揭示了青藏高原东北部不同环境下两类pepe的演化机制，有利于青藏高原及其下游地区pepe的预报和防灾。

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引用次数: 0

Learning the hard way: Applying a climate literacy approach to extreme weather experience — Evidence from Poland 以艰难的方式学习：将气候素养方法应用于极端天气体验——来自波兰的证据

IF 6.9 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2026-01-07 DOI: 10.1016/j.wace.2026.100851

Łukasz Kurowski, Tomasz Wites

Climate literacy is essential for empowering societies to respond effectively to the challenges of climate change. However, individuals often struggle to address climate issues because of their abstract nature and perceived psychological distance. This study investigates whether direct personal experiences of extreme weather events are associated with higher scores on the climate literacy measures among Polish citizens. We developed and validated, through an expert-based process, the “Big Three Climate Literacy Questions” - a concise instrument designed to capture key components of climate literacy across knowledge, skills and attitudes - and administered them in a survey of 1001 residents from regions in Poland historically affected by floods and storms. Regression analyses reveal that the mere occurrence of an extreme weather event does not significantly influence scores on the climate literacy measures. However, when such events result in severe financial or psychological consequences, they are associated with higher literacy scores (for all three dimensions of climate literacy), suggesting that the intensity of the experience can act as a catalyst for deeper cognitive and emotional engagement. We also find that individuals employed in high-emission sectors tend to overestimate their climate knowledge; nonetheless, their personal experiences with extreme weather events are still associated with higher scores on the climate literacy measures. These findings support the hypothesis that intense climate-related experiences can serve as “teachable moments", enhancing receptiveness to climate information and fostering the development of more accurate and informed climate-related beliefs—even among groups that might otherwise exhibit resistance to such messages.

气候知识对于增强社会权能、有效应对气候变化挑战至关重要。然而，由于气候问题的抽象性质和感知到的心理距离，个人往往难以解决气候问题。本研究调查了极端天气事件的直接个人经历是否与波兰公民的气候素养措施得分较高有关。通过以专家为基础的流程，我们开发并验证了“三大气候素养问题”，这是一个简明的工具，旨在捕捉气候素养的关键组成部分，包括知识、技能和态度，并在对波兰历史上受洪水和风暴影响地区的1001名居民的调查中进行了管理。回归分析表明，极端天气事件的发生并不显著影响气候素养措施的得分。然而，当这些事件导致严重的经济或心理后果时，它们与更高的识字分数（对于气候素养的所有三个维度）有关，这表明体验的强度可以作为更深层次认知和情感参与的催化剂。我们还发现，受雇于高排放行业的个人往往高估了他们的气候知识；尽管如此，他们与极端天气事件的个人经历仍然与气候素养措施的高分有关。这些发现支持了这样一种假设，即强烈的气候相关经历可以作为“教育时刻”，增强对气候信息的接受能力，促进更准确、更明智的气候相关信念的发展——即使在那些可能对这些信息表现出抵制的群体中也是如此。

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引用次数: 0

Assessing livelihood vulnerability in flood-prone communities through systems thinking and the sustainable livelihood framework: A case study of Rajanpur district, Pakistan 通过系统思维和可持续生计框架评估易发洪灾社区的生计脆弱性：以巴基斯坦Rajanpur地区为例

IF 6.9 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2026-01-02 DOI: 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.

本文讨论了以动态方式评估发展中国家易受洪水影响的农村社区生计脆弱性的关键问题。主要目标是制定一个框架，以了解易受洪水影响的演变性质，并提出基于系统的干预策略，以加强社区的复原力。该研究将系统思维方法与可持续生计框架相结合，采用了巴基斯坦拉詹普尔地区的一个案例研究，该地区近几十年来经历了严重的洪灾。该研究提出了一个社区生计系统的概念模型及其相关的系统原型。概念模型强调了影响该地区生计脆弱性的潜在反馈结构。已确定的系统原型表明，目前的洪水适应政策由于其意想不到的后果而不适应，这些后果损害了干预措施的长期有效性和生计资源的可持续管理。为了避免适应不良和加强社区生计资本的利用，政策努力必须从短期修复转向设计和实施长期战略，以提高该地区的抗洪能力和加强生计资产。本研究为重塑巴基斯坦的适应政策提供了有价值的见解，并为面临类似气候相关挑战的其他地区的知识共享奠定了基础。

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引用次数: 0

Identifying recurring patterns of extreme daily precipitation using K-means algorithm: Uncovering spatial shift driven by climate change over the Italian Peninsula 利用K-means算法识别极端日降水的重复模式：揭示意大利半岛气候变化驱动的空间变化

IF 6.9 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2025-12-26 DOI: 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).

本研究旨在利用应用于高分辨率气候预测的k均值聚类分析，调查整个意大利半岛极端日降水事件的时空格局。研究分析了分辨率为2.2 km的VHR-PRO_IT数据集数据，并对RCP4.5和RCP8.5浓度情景下的历史期（1981-2005年）和未来期（2035-2065年）进行了分析。聚类方法确定了13种不同的降水模式，并说明了复杂地形、地理位置和海洋影响对形成极端降水制度的决定性影响。结果显示，降水模式有相当大的季节性波动，冬季观测到的强度最高，特别是在山区。未来的预估表明整个地区的降雨变率将增加，其中RCP4.5情景下的标准差将增加约19%，RCP8.5情景下的标准差将增加17%。其中一个显著的变化是，东阿尔卑斯和亚平宁北部的降水增加，而西西里岛、撒丁岛和第勒尼安沿岸的降水在夏季呈减少趋势。k均值聚类分析强调了意大利不同地区降水模式的变化，确定了最容易受到极端日常事件影响的地区，并将它们与未来大气环流模式变化相关的潜在大规模变化联系起来。高分辨率数据（2.2 km）能够表征中尺度现象和区域变化，并通过绘制未来气候情景（RCP4.5和RCP8.5）下的降水分布变化，为气候适应规划提供数据支持。

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引用次数: 0

Attribution of the 2024 record-breaking precipitation event in Southern Denmark to human-induced climate change 将2024年丹麦南部破纪录的降水事件归因于人为引起的气候变化

IF 6.9 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2025-12-16 DOI: 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.

据报道，全球极端天气事件的频率和严重程度都在增加。这些事件通过洪水和干旱等危害威胁着社会，强调有必要了解这些风险在不断变化的气候中是如何演变的。最近采用了标准化方法来评估气候变化对极端事件的潜在作用。世界天气归因（WWA）提供了一个概率框架，以确定极端事件发生频率和严重程度的变化是否可归因于人为变暖。在这里，我们使用这种方法将丹麦南部前所未有的降雨事件归因于人为气候变化。大约在2024年9月27日。埃斯比约市的降雨量为145毫米，创下9月份的最高日降雨量记录。这一事件造成了大范围的洪水，交通中断，基础设施受损，并影响到居民区。本研究利用降雨观测、再分析数据集和气候模式集来评估人为气候变化的作用。值得注意的是，这是首次应用高分辨率区域单模式初始条件大集合（SMILE） ClimEx归因研究。分析结果表明，与工业化前气候相比，当前气候下降雨事件发生的可能性增加了60%(- 20% - 540%)，事件强度因气候变化增加了10.2%（- 3.3% - 25.6%）。我们的发现还表明，这类事件的频率和强度随着进一步变暖而增加。总的来说，这项研究强调了危害、暴露和脆弱性如何导致城市风险。

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