Weather and Climate Extremes最新文献_第7页

Projected impacts of climate and land use changes on streamflow extremes in the upper awash Basin, Ethiopia 气候和土地利用变化对埃塞俄比亚上冲盆地极端水流的预估影响

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

Weather and Climate Extremes

Pub Date : 2025-12-01 Epub Date: 2025-09-26 DOI: 10.1016/j.wace.2025.100806

Selamawit Haftu Gebresellase , Zhiyong Wu , Wada Idris Muhammad , Gebremedhin Gebremeskel Haile

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.

本研究探讨了气候、土地利用和土地覆盖（LULC）变化对埃塞俄比亚上阿瓦什盆地（UAB）极端流量的预测影响。利用SSP4.5和SSP8.5条件下的高性能CMIP6气候模型，以及2030年代和2060年代在常规商业模式（BAU）和政府模式（GOV）下的未来LULC情景，采用SWAT模型模拟水文响应。结果表明：气候变化显著影响极端流量，具有高流量指数；最大高流量（MHF）、高流量脉冲数（HPC）、高流量脉冲持续时间（HPD）明显增加，低流量指标；最小低流量（MLF）、低流量脉冲数（LPC）和低流量脉冲持续时间（LPD）均大幅下降。例如，20世纪60年代SSP8.5条件下，MHF、HPC和HPD分别增加了63.16%、26.85%和14.96%，而MLF、LPC和LPD分别减少了67.11%、34.40%和5.95%。相比之下，在所有情景和时期，LULC变化对高流量和低流量指数的影响在统计上都不显著。BAU情景预测了大量的城市和农田扩张，导致森林和灌木面积减少，而GOV情景强调可持续土地管理，控制城市蔓延和增加森林覆盖。尽管存在这些差异，与气候变化的压倒性影响相比，lulc引起的极端流量变化仍然很小。本研究强调气候变化是UAB地区未来水文极端事件的主要驱动因素，强调需要以气候为重点的适应战略，以减轻对该地区水资源和生计的不利影响。

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引用次数: 0

Changes in atmospheric circulation amplify extreme snowfall fueled by Arctic sea ice loss over high-latitude land 大气环流的变化放大了北极海冰在高纬度陆地上的消融所引发的极端降雪

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

Weather and Climate Extremes

Pub Date : 2025-12-01 Epub Date: 2025-09-05 DOI: 10.1016/j.wace.2025.100802

Yubo Liu , Qiuhong Tang , L. Ruby Leung , Deliang Chen , Jennifer A. Francis , Chi Zhang , Hans W. Chen , Steven C. Sherwood

Arctic sea-ice retreat has been linked to increased winter precipitation and heavy snowfall over land, likely due to a combination of enhanced evaporation from ice-free Arctic marginal seas (AMS) and changes in atmospheric circulation. However, their relative roles and contributions remain uncertain. Here, we show that a greater proportion of AMS evaporative moisture reached high-latitude land during the cold seasons from 1980–1989 to 2012–2021. Atmospheric circulation changes added an additional 13 % increase in the AMS moisture contribution, accounting for 11 % of the total increase in AMS-sourced land precipitation. Notably, 46 % of the increase in AMS-sourced extreme snowfall is attributed to circulation-driven landward moisture transport, representing an 84 % increase beyond the effect of enhanced AMS evaporation alone. Further analysis indicates that both the rise in Arctic moisture and the atmospheric circulation shifts are primarily driven by anthropogenic forcing. These findings highlight how atmospheric circulation changes amplify extreme snowfall fueled by AMS evaporation, underscoring the synergistic effects of Arctic sea ice loss and circulation change on high-latitude winter precipitation.

北极海冰的退缩与冬季降水的增加和陆地上的大雪有关，这可能是由于无冰的北极边缘海（AMS）的蒸发增强和大气环流变化的共同作用。然而，它们的相对作用和贡献仍然不确定。研究表明，在1980-1989年和2012-2021年的寒冷季节，AMS蒸发水分到达高纬度陆地的比例更大。大气环流变化使AMS水分贡献增加了13%，占AMS源陆地降水总增加量的11%。值得注意的是，由AMS引起的极端降雪增加的46%归因于环流驱动的向陆地输送水分，比AMS蒸发增强的影响增加了84%。进一步的分析表明，北极湿度的上升和大气环流的变化主要是由人为强迫驱动的。这些发现强调了大气环流变化如何放大由AMS蒸发引起的极端降雪，强调了北极海冰损失和环流变化对高纬度冬季降水的协同效应。

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引用次数: 0

Differential sensitivities of three types of compound drought and heatwave events to human-induced climate change across the globe 全球三种类型的复合干旱和热浪事件对人为气候变化的差异敏感性

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

Weather and Climate Extremes

Pub Date : 2025-12-01 Epub Date: 2025-11-19 DOI: 10.1016/j.wace.2025.100836

Shuzhe Huang , Siqi Wang , Chao Wang , Xiang Zhang , Jianya Gong , Nengcheng Chen

Compound drought and heatwave (CDHW) events threaten ecosystems, water security, and human health through mutually reinforcing thermal and hydrological stress. Using CMIP6 multi-model simulations, we quantify influences of human-induced climate change on three CDHW types (i.e., precipitation-based (CMDH), runoff-based (CHDH), and soil-moisture-based (CSDH)) by isolating greenhouse gas, aerosol, and natural forcings (1960–2014). Greenhouse gas forcing emerges as the dominant driver of global CDHW intensification, with CSDH showing the strongest and most coherent amplification of CDHW frequency and severity. Aerosols partially offset warming-induced increases, particularly in monsoon regions. Interpretable machine learning reveals temperature as the primary driver, with precipitation and vapor pressure deficit playing event-dependent roles. Future projections (2015–2100) under high-emission pathways indicate significant severity growth (6.8 %, 9.4 %, and 15.4 % for CMDH, CHDH, and CSDH on average) and sharply rising population exposure (with slope of 0.22, 0.23, and 0.65 for CMDH, CHDH, and CSDH) concentrated in tropical and temperate regions. These findings highlight the urgency of aggressive mitigation and adaptation strategies that address the compound nature of climate extremes and the spatial heterogeneity of anthropogenic impacts.

复合干旱和热浪（CDHW）事件通过相互加强的热和水文压力，威胁着生态系统、水安全和人类健康。利用CMIP6多模式模拟，通过隔离温室气体、气溶胶和自然强迫（1960-2014），量化了人类引起的气候变化对三种CDHW类型（即基于降水（CMDH）、基于径流（CHDH）和基于土壤湿度（CSDH））的影响。温室气体强迫是全球CDHW增强的主要驱动因素，CSDH对CDHW的频率和强度表现出最强和最一致的放大。气溶胶部分抵消了由变暖引起的增加，特别是在季风区。可解释的机器学习表明，温度是主要驱动因素，降水和蒸汽压赤字起着事件依赖的作用。在高排放路径下的未来预测（2015-2100年）表明，严重程度的显著增长（CMDH、CHDH和CSDH的平均增长分别为6.8%、9.4%和15.4%）和人口暴露量的急剧增加（CMDH、CHDH和CSDH的斜率分别为0.22、0.23和0.65）集中在热带和温带地区。这些发现突出表明，迫切需要采取积极的减缓和适应战略，解决极端气候的复合性质和人为影响的空间异质性。

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引用次数: 0

A novel hybrid framework of high-resolution flood susceptibility mapping in ungauged mountainous regions 未测量山区高分辨率洪水易感性制图的新型混合框架

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

Weather and Climate Extremes

Pub Date : 2025-12-01 Epub Date: 2025-11-01 DOI: 10.1016/j.wace.2025.100822

Kai Li, Linmao Guo, Genxu Wang, Jihui Gao, Jiapei Ma, Jinlong Li, Peng Huang, Biying Zhai, Xiangyang Sun

Flood susceptibility mapping in mountainous regions remains a critical tool for mitigating escalating flood risks in the context of climate change. However, its accuracy is constrained by data scarcity of flood inventory maps and uncertainties in flood susceptibility mapping. This study addresses these gaps by introducing a novel hybrid framework that integrates a physically based Topography-based Subsurface Storm Flow (Top-SSF) model, a terrain-processed Height Above Nearest Drainage (HAND) model, and Random Forest (RF) model to achieve high-resolution (15 m) flood susceptibility mapping. Trained and tested on data from 80 gauged catchments, the hybrid framework demonstrated excellent performance, with training and test AUC of 0.995 and 0.992, respectively. Its robustness and applicability were subsequently validated against two independent historical flood datasets spanning 2000–2024, yielding high AUC values of 0.895 and 0.969, respectively. Sensitivity analysis identified slope, Topographic Position Index (TPI), and Topographic Wetness Index (TWI) as key drivers, collectively contributing 80.46 % to flood susceptibility. Finally, we used the hybrid framework to produce the first high-resolution flood susceptibility map for the Southwest Mountainous Region of China, with potential to significantly enhance early warning systems and improve flood management effectiveness.

在气候变化的背景下，山区洪水易感性地图仍然是缓解不断升级的洪水风险的重要工具。但其精度受到洪水库存量图数据稀缺性和洪水易感度图不确定性的制约。本研究通过引入一种新的混合框架来解决这些差距，该框架集成了基于物理的基于地形的地下风暴流（Top-SSF）模型、地形处理的比最近排水高度（HAND）模型和随机森林（RF）模型，以实现高分辨率（15米）洪水易感性映射。对80个计量流域的数据进行训练和测试，混合框架表现出优异的性能，训练和测试AUC分别为0.995和0.992。随后，在2000-2024年两个独立的历史洪水数据集上验证了其鲁棒性和适用性，分别获得了0.895和0.969的高AUC值。敏感性分析表明，坡度、地形位置指数（TPI）和地形湿度指数（TWI）是主要驱动因素，对洪涝易感性的贡献率为80.46%。最后，我们利用混合框架绘制了中国西南山区的第一张高分辨率洪水易感性图，具有显著增强预警系统和提高洪水管理效率的潜力。

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引用次数: 0

Integrating non-stationarity and uncertainty in design life levels based on climatological time series 基于气候时间序列的设计寿命水平非平稳性和不确定性的综合

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

Weather and Climate Extremes

Pub Date : 2025-12-01 Epub Date: 2025-09-27 DOI: 10.1016/j.wace.2025.100807

Occitane Barbaux , Philippe Naveau , Nathalie Bertrand , Aurélien Ribes

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.

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.

这项工作的重点是推断非平稳条件下极端事件的设计寿命水平。它的目标是双重的。第一种方法是提供一个单一的指标，该指标总结了时间序列中大值的相关和可解释的信息，即使不能假设平稳性。经典的风险指标，如100年回报水平，在非平稳框架下变得难以解释。为了解决这个问题，我们利用了等效可靠性（ER）级别的现有概念。在平稳性条件下，ER水平与经典回归水平一致，反之则不同。更准确地说，ER水平确保在指定设计期间所有观测值低于ER水平的概率得到控制。这个定义确保了在安全或故障风险方面的可解释性。第二个目标是捕获随机和估计不确定性，这是任何风险分析中的一个关键方面，因为推理方案的不确定性可能会以极端强度增长。我们通过使用贝叶斯预测分布将两者结合起来。虽然在贝叶斯统计中很有名，但预测分布很少应用于气候时间序列风险分析。

{"title":"Integrating non-stationarity and uncertainty in design life levels based on climatological time series","authors":"Occitane Barbaux , Philippe Naveau , Nathalie Bertrand , 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":"2025-12-01","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}

引用次数: 0

Improving extreme precipitation forecasts in Catalonia (NE Iberian Peninsula) using analog methods: A comparison with the GFS model 利用模拟方法改进加泰罗尼亚（伊比利亚半岛东北部）极端降水预报：与GFS模式的比较

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

Weather and Climate Extremes

Pub Date : 2025-12-01 Epub Date: 2025-11-22 DOI: 10.1016/j.wace.2025.100839

Carlo Guzzon , Raül Marcos-Matamoros , Maria Carmen Llasat , Montserrat Llasat-Botija

Flood forecasting in the Mediterranean region remains particularly challenging due to the localized and convective nature of extreme precipitation events. This study evaluates the potential of analog-based methods (AMs) to enhance 24-hour precipitation forecasts for Catalonia (northeastern Iberian Peninsula), with the broader objective of supporting flood risk management and early warning systems. The tested AMs use geopotential height fields at 500 and 1000 hPa as predictors and differ in complexity, combining Weather-Type classification (WT), Seasonal Standardization (S), and the Perfect Prognosis (PP) framework, a novel configuration in analog-based forecasting. Model performance was assessed against operational Global Forecast System (GFS) forecasts using fifth-generation ECMWF Re-Analysis (ERA5) as reference, for both moderate and extreme precipitation events associated with historical floods. Results show that AMs integrating Seasonal Standardization and the Perfect Prognosis framework markedly improve 24-hour precipitation forecasts relative to GFS, particularly in reproducing the intensity and spatial distribution of extreme events. These findings highlight the operational potential of enhanced AMs as efficient, data-driven complements to numerical weather prediction models, offering improved skill for flash-flood forecasting and impact-based risk management.

由于极端降水事件的局域性和对流性，地中海地区的洪水预报仍然特别具有挑战性。本研究评估了基于模拟的方法（AMs）在加强加泰罗尼亚（伊比利亚半岛东北部）24小时降水预报方面的潜力，其更广泛的目标是支持洪水风险管理和早期预警系统。测试的人工智能系统使用500和1000 hPa的位势高度场作为预测因子，其复杂性不同，结合了天气类型分类（WT）、季节标准化(S)和完美预测（PP）框架，这是一种基于模拟预测的新配置。在与历史洪水相关的中度和极端降水事件中，利用第五代ECMWF Re-Analysis （ERA5）作为参考，根据全球预报系统（GFS）的预报评估了模式的性能。结果表明，与GFS相比，整合季节标准化和完美预测框架的AMs在24小时降水预报方面有显著提高，特别是在再现极端事件的强度和空间分布方面。这些发现突出了增强型人工智能作为数值天气预报模式的有效、数据驱动的补充的业务潜力，为山洪预报和基于影响的风险管理提供了改进的技能。

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引用次数: 0

Discernability of the vertical vortex structure of pre-existing disturbances and their implication for tropical cyclone formation 已存在扰动的垂直涡旋结构的可分辨性及其对热带气旋形成的意义

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

Weather and Climate Extremes

Pub Date : 2025-12-01 Epub Date: 2025-09-05 DOI: 10.1016/j.wace.2025.100804

Hung Ming Cheung , Jung-Eun Chu

The formation of a tropical cyclone (TC) is often rooted in a pre-existing disturbance, yet our understanding of their structural differences and evolution into TCs remains limited. To bridge the knowledge gap, we examine tropical disturbances and depressions in the western North Pacific during the period 2004–2021 from a best-track dataset. Here we show four discernible structures of pre-existing disturbances in terms of their vertical and radial extents: broad vortex dominated by lower-tropospheric vorticity (Cluster 1), narrow vortex with its vorticity maximum in the lower troposphere (Cluster 2), broad and deep vortex spanning most of the troposphere (Cluster 3), and narrow vortex dominated by upper-tropospheric vorticity (Cluster 4), by applying unsupervised machine learning techniques. Out of the 2014 samples analyzed, almost 80 % exhibit vorticity maximum in the lower troposphere, while the others peak aloft. While these different structures have varying implications for stratiform and convective precipitations, there is no clear preference for specific vortex structures in pre-existing disturbances for TC genesis in the next 6 h. On the other hand, the time it takes for TC genesis or the intensification rate is more closely related to the upper-level extent of relative vorticity rather than the local maximum magnitude or radial size of the vortices. Despite the uncertainty concerning the data during the earlier lifetime, the study introduces a systematic approach to categorizing the vortex structures of pre-existing disturbances which provides new insights into their role in TC formation.

热带气旋（TC）的形成通常植根于预先存在的扰动，但我们对它们的结构差异和向TC演变的理解仍然有限。为了弥补知识差距，我们从最佳跟踪数据集中研究了2004-2021年期间北太平洋西部的热带扰动和低气压。通过应用无监督机器学习技术，我们展示了四种可识别的已存在扰动结构：由对流层低层涡度主导的宽涡（簇1），涡度最大的对流层低层涡（簇2），跨越大部分对流层的宽深涡（簇3），以及由对流层上层涡度主导的窄涡（簇4）。在分析的2014个样本中，几乎80%的涡度在对流层下层达到最大值，而其他的则在高空达到峰值。虽然这些不同的结构对层状降水和对流降水有不同的影响，但在接下来的6小时内，对已有扰动中的特定涡结构的TC形成没有明显的偏好。另一方面，TC形成所需的时间或增强速率与上层相对涡度的程度更密切相关，而不是与当地最大涡的大小或径向大小密切相关。尽管早期的数据存在不确定性，但该研究引入了一种系统的方法来对预先存在的扰动的涡结构进行分类，这为它们在TC形成中的作用提供了新的见解。

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引用次数: 0

Increased precipitation variability at multi-timescales in China since the 1960s 20世纪60年代以来中国多时间尺度降水变率的增加

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

Weather and Climate Extremes

Pub Date : 2025-12-01 Epub Date: 2025-09-18 DOI: 10.1016/j.wace.2025.100808

Xuyang Mo , Wenxia Zhang , Tianjun Zhou

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.

中国降水的频率和强度发生了显著变化。一个相关的行为是降水的变率，它描述了降水事件的时间波动。然而，目前尚不清楚中国不同时间尺度的降水变异性是如何变化的。在这项研究中，我们发现自20世纪60年代以来，中国的降水变率显著增加，平均每十年增加2.3%。这种增加在天气到季节内的时间尺度上都存在。各季节降水变率的增加都很明显，冬季的百分比增加幅度最大，约为夏季的3倍。从区域上看，中国西北部、东北部和东南部降水变率显著上升，而沿华北至西南的干湿过渡带降水变率下降不显著。与平均和极端降水趋势相比，降水变率的增加范围更广，幅度更大。前10%极端降水事件的变化贡献了全国降水变率放大的约75%。除了长期趋势外，中国东部夏季降水变率还受到太平洋年代际涛动的调制。研究表明，自20世纪60年代以来，中国不同时间尺度、季节和地区的降水变率显著增加，对干旱、洪水和水资源管理产生了深远的影响。

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引用次数: 0

The impact of aerosol forcing on the statistical attribution of heatwaves 气溶胶强迫对热浪统计归因的影响

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

Weather and Climate Extremes

Pub Date : 2025-12-01 Epub Date: 2025-09-12 DOI: 10.1016/j.wace.2025.100803

Florian Kraulich, Peter Pfleiderer, Sebastian Sippel

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.

由于人为气候变化，热浪正变得越来越频繁和强烈。准确地确定其发生概率和强度的变化对有效的气候变化适应战略至关重要。在观测中计算热浪重现期的一种常见做法依赖于极值统计，其中广义极值分布（GEV）随全球平均温度（GMT）的协变量线性移动，以捕获气候变化的全球强迫响应（“标准方法”，从现在开始）。虽然这种方法通常是有效的，但它没有明确地包括区域气溶胶趋势，而气溶胶趋势通过反射太阳辐射和改变云的性质而强烈地影响当地的极端高温。根据地区的不同，气溶胶强迫趋势可以放大或抵消温室气体引起的变暖。本文利用社区地球系统模式2 （CESM2）大集合和单一强迫大集合的气候模式模拟，评估了区域气溶胶趋势对热浪统计极端事件归因的影响。为了检验气溶胶对极端事件趋势的影响，我们在GEV模型中引入气溶胶光学深度（AOD）作为一个额外的协变量，并将这种方法与“标准方法”进行比较。我们的结果表明，在气溶胶变化强烈的地区和时期，特别是在北美、中欧和东欧以及东亚的工业区，“标准方法”存在很大的偏差。包括AOD作为协变量显著减少了这些偏差，并改善了回报期估计。这项研究强调了将区域气溶胶趋势纳入统计归因框架的重要性，以改进对回归期的估计，从而改进归因陈述。

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引用次数: 0

Attributing a deadly landslide disaster in Southeastern Brazil to human-induced climate change 将巴西东南部致命的山体滑坡灾害归咎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 : 2025-12-01 Epub Date: 2025-10-11 DOI: 10.1016/j.wace.2025.100811

Maria Lucia Ferreira Barbosa , Rafaela Quintella Veiga , Renata Pacheco Quevedo , Débora Joana Dutra , Ana Carolina Moreira Pessôa , Thaís Pereira de Medeiros , Chantelle Burton , Yuexiao Liu , Nubia Beray Armond , Rafael C. de Abreu , Sihan Li , Fraser C. Lott , Cassiano Antonio Bortolozo , Sarah Sparrow , Liana Oighenstein Anderson

Petrópolis was hit by a devastating disaster in February 2022, when it rained 252.8 mm within 3 h, leading to 200 lost lives and hundreds of people being displaced. Here, we aimed to attribute the extreme rainfall event that led to several landslides in Petrópolis, assess how Land Use and Land Cover changes (LUCC) from 1985 to 2021 contributed to it, and quantify their socioeconomic impacts. For this, we compared natural-only forcing (NAT) and natural and anthropogenic forcing combined (ALL) scenarios of the HadGEM3 ensemble models with observation data. We computed the trends in LUCC and quantified the landslide's socioeconomic impacts from official datasets. Human-induced climate change made this extreme event 45 % and 71 % more likely in short and long-term rainfall, respectively. Recurrence period dropped from 2.36 years (NAT) to 1.63 years (ALL) in the short-term and from 5.66 years (NAT) to 3.31 years (ALL) in the long-term. Landscape trends show an increase in forest formations, but unprotected hilltops that collapsed presented more than 40 % of their area as farming. The total economic loss was more than USD 22 million, with 1 078 people directly affected. The study's findings are valuable in understanding how changes in extreme weather events and land use are affecting our society. We highlight the need for adaptation measures and for more research addressing the attribution of extreme events, especially those associated with disastrous landslides.

2022年2月，Petrópolis遭受了一场毁灭性的灾难，当时3小时内降雨量达到252.8毫米，导致200人丧生，数百人流离失所。在这里，我们的目的是归因导致Petrópolis几次山体滑坡的极端降雨事件，评估1985年至2021年土地利用和土地覆盖变化（LUCC）是如何促成它的，并量化其社会经济影响。为此，我们将HadGEM3整体模式的自然强迫（NAT）和自然与人为强迫组合（ALL）情景与观测数据进行了比较。我们计算了LUCC的趋势，并从官方数据集中量化了滑坡的社会经济影响。人为引起的气候变化使这种极端事件在短期和长期降雨方面的可能性分别增加了45%和71%。短期复发期由2.36 a （NAT）降至1.63 a (ALL)，长期复发期由5.66 a （NAT）降至3.31 a （ALL）。景观趋势表明，森林的形成有所增加，但未受保护的山顶坍塌，其面积的40%以上为农业。经济损失总额超过2200万美元，直接受灾人数达1078人。这项研究的发现对于理解极端天气事件和土地利用的变化如何影响我们的社会是有价值的。我们强调需要采取适应措施，并开展更多研究，解决极端事件的归因问题，特别是与灾难性山体滑坡有关的事件。

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