Weather and Climate Extremes最新文献_第9页

Human influence on the unprecedented 2022 extreme dragon boat water event in South China: Insights from historical and projected perspectives 人类对2022年中国南方前所未有的极端龙舟水事件的影响：从历史和预测的角度看

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

Weather and Climate Extremes

Pub Date : 2025-12-01 Epub Date: 2025-11-12 DOI: 10.1016/j.wace.2025.100830

Shen'ao Li, Hui Cai, Wenxuan Zhang, Wenjun Liang, Kaixi Wang, Dong Chen, Shaobo Qiao, Xian Zhu

During May–June 2022, South China encountered an unprecedented extreme dragon boat water event (2022 EDBWE), characterized by persistent heavy precipitation. The maximum 31-day cumulative precipitation (Rx31day) from May 21 to June 20, was anomalously 74 % higher than the historical average, breaking previous records and resulting in substantial socioeconomic damage and loss of life. Nevertheless, the extent to which human-induced climate change influenced the occurrence of the 2022 EDBWE, as well as its implications for the future likelihood of analogous events under different Shared Socioeconomic Pathway (SSP) scenarios, remains inadequately quantified. This study aims to address these uncertainties by employing data from the Detection and Attribution Model Intercomparison Project (DAMIP) and the Scenario Model Intercomparison Project (SIMIP) within the Coupled Model Intercomparison Project Phase 6 (CMIP6). We evaluate the effect of anthropogenic forcing on extreme precipitation similar to the 2022 EDBWE both in historical context and under future projections for South China. The results indicate that anthropogenic forcing has increased the probability of the event similar to the 2022 EDBWE by approximately 64 % (90 % confidence interval: 35 % to +90 %). Specifically, the greenhouse gas-only (GHG) forcing has raised the probability by +66 % (+10 % to +91 %), while aerosol-only (AER) forcing has reduced the probability by −28 % (−564 % to +71 %). Furthermore, under SSP scenarios—SSP1-2.6, SSP2-4.5, and SSP5-8.5—the likelihood of similar events rises significantly. By the end of the 21st century, the probability of an event akin to the 2022 EDBWE is projected to be about 11 times greater under the high-emission scenario (SSP5-8.5) compared to historical climate conditions. This study offers crucial insights for designing effective strategies to mitigate and adapt to climate change, especially in regions prone to extreme precipitation events.

2022年5 - 6月，华南地区遭遇了一次前所未有的极端龙舟水事件（2022 EDBWE），其特征是持续强降水。5月21日至6月20日的最大31天累积降水（rx31天）比历史平均水平异常高出74%，打破了以往的记录，造成了重大的社会经济损失和生命损失。然而，人类引起的气候变化对2022年EDBWE发生的影响程度，以及它对不同共享社会经济路径（SSP）情景下类似事件未来可能性的影响，仍然没有充分量化。本研究旨在利用耦合模式比对项目第6阶段（CMIP6）中的探测与归因模式比对项目（DAMIP）和情景模式比对项目（SIMIP）的数据来解决这些不确定性。在历史背景和未来预测下，我们评估了与2022年EDBWE相似的人为强迫对中国南方极端降水的影响。结果表明，人为强迫使类似2022年EDBWE事件的概率增加了约64%（90%置信区间：35%至+ 90%）。具体而言，仅温室气体（GHG）强迫将概率提高了66%(+ 10%至+ 91%)，而仅气溶胶（AER）强迫将概率降低了28%（- 564%至+ 71%）。此外，在SSP情景（ssp1 -2.6、SSP2-4.5和ssp5 -8.5）下，类似事件发生的可能性显著上升。到21世纪末，在高排放情景（SSP5-8.5）下，与历史气候条件相比，预计类似2022年EDBWE事件的概率将高出约11倍。这项研究为设计有效的策略来减缓和适应气候变化提供了重要的见解，特别是在容易发生极端降水事件的地区。

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引用次数: 0

Asymmetric heatwave intensification under divergent climate change mitigation pathways amplifies urban–rural exposure disparities 不同气候变化缓解路径下的不对称热浪加剧放大了城乡暴露差异

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

Weather and Climate Extremes

Pub Date : 2025-12-01 Epub Date: 2025-10-29 DOI: 10.1016/j.wace.2025.100821

Oluwafemi E. Adeyeri , Wen Zhou , Christopher E. Ndehedehe , Kazeem Abiodun Ishola , Akintomide A. Akinsanola , Naveed Ahmed , Xuan Wang

Unmitigated climate change poses threats to human and environmental well-being through increasingly intense and frequent heatwaves. However, the future impact of heatwaves on urban and rural populations remains uncertain. We project intensified heatwave characteristics and earlier onsets across numerous global regions using bias-corrected climate models. The projected impacts of limiting global warming to either regional-rivalry (SSP370) or fossil-fueled development (SSP585) pathways differ significantly, with SSP585 resulting in substantially more persistence and intensity than SSP370. Under SSP370, high heatwave frequency (HWF) correlates with low heatwave number (HWN) in most tropical regions, but the opposite is true in polar regions. Moreover, heatwave intensity is mostly governed by radiative and advective forcing, while persistence depends on large-scale flow stability. We further demonstrate that heatwave exposure varies considerably across different climate regions and population strata, with rural populations exhibiting exposure comparable to urban populations. Under SSP 370, the Tibetan region will witness rural population exposure to HWF totalling 15 million person-days, compared to 5 million person-days in urban population exposure. In East Asia, both the near and late-21st-century scenarios under SSP 370 show a dominant climate effect (at 90 %) governing the total changes to rural population exposure. In general, most regions are expected to witness the population effect dominance during SSP 370 in the mid-21st-century for rural populations, while the population effect dominance for urban populations varies by region. Our findings underscore the importance of developing customized adaptation plans to address the challenges of heatwaves in a changing climate.

无法缓解的气候变化通过日益强烈和频繁的热浪对人类和环境福祉构成威胁。然而，未来热浪对城市和农村人口的影响仍不确定。我们利用校正偏倚的气候模式预测了全球许多地区热浪特征的增强和发病时间的提前。限制全球变暖对区域竞争（SSP370）或化石燃料发展（SSP585）途径的预期影响存在显著差异，SSP585导致的持续时间和强度明显高于SSP370。在SSP370下，大多数热带地区的高热浪频率（HWF）与低热浪次数（HWN）相关，而极地地区则相反。此外，热浪强度主要受辐射和平流强迫的影响，而持续性则取决于大尺度流动的稳定性。我们进一步证明，热浪暴露在不同气候区域和人口阶层之间差异很大，农村人口的暴露程度与城市人口相当。在东亚，SSP 370下的21世纪中期和后期情景都表明，气候效应主导着农村人口暴露的总变化（占90%）。总体而言，大多数地区预计在21世纪中期的SSP 370期间，农村人口将见证人口效应的主导地位，而城市人口的人口效应主导地位因地区而异。我们的研究结果强调了制定定制适应计划以应对气候变化中热浪挑战的重要性。

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引用次数: 0

Distinguishing environmental controls on strong vs. extreme wind gusts 区分强风和极端阵风的环境控制

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

Weather and Climate Extremes

Pub Date : 2025-09-01 Epub Date: 2025-07-26 DOI: 10.1016/j.wace.2025.100788

Greeshma Surendran , Steven Sherwood , Jason Evans , Moutassem El Rafei , Andrew Dowdy , Fei Ji , Andrew Brown

Statistical and theoretical models of wind gusts may be dominated by more common strong events, rather than rare but damaging extreme ones. We address this by combining case studies of six extreme gust cases in New South Wales (NSW), Australia, with statistical and machine-learning (random forest) models to identify environmental factors distinguishing “strong” (

\geq 18 m/s

) vs. “extreme” (

\geq 25 m/s

) gust events in a 20-year dataset. The BARRA-SY high-resolution regional reanalysis is used to augment in-situ observations and provide a model gust speed diagnostic for evaluation, as well as environmental prediction metrics. All the extreme wind cases were linked to deep convection, often organized into linear systems. A random forest model achieved 89% accuracy for predicting strong winds generally, with the gust diagnostic and environmental background wind speeds as the top predictors. For distinguishing extreme from strong gusts, the model’s accuracy was 79%, but with a high false alarm rate. Both statistical and machine-learning analyses highlight convective instability metrics — Most Unstable Convective Available Potential Energy (MUCAPE), Derecho Composite Parameter (DCP), and k_index - as key predictors of extreme gusts. The BARRA-SY gust speed diagnostic thus informs about strong wind gusts, but not extremes, which depend on variables it ignores. Instability measures, however, are also imperfect predictors of extreme gusts because they fail to capture storm trigger conditions, seen in some of the case studies. These findings demonstrate that the factors driving extreme wind gusts differ substantially from those driving strong but less extreme gusts. Therefore, statistical analyses or predictive models that consider all strong gusts collectively will likely fail to uncover the environmental factors responsible for the most extreme events with greatest impact.

阵风的统计和理论模型可能被更常见的强事件所主导，而不是罕见但具有破坏性的极端事件。我们通过将澳大利亚新南威尔士州（NSW）的六个极端阵风案例研究与统计和机器学习（随机森林）模型相结合来解决这个问题，以确定在20年数据集中区分“强”（≥18m/s）和“极端”（≥25m/s）阵风事件的环境因素。BARRA-SY高分辨率区域再分析用于增强现场观测，并为评估提供模型阵风速度诊断，以及环境预测指标。所有极端风的情况都与深层对流有关，通常被组织成线性系统。随机森林模型预测强风的准确率达到89%，其中阵风诊断和环境背景风速是最高的预测指标。在区分极端阵风和强烈阵风方面，该模型的准确率为79%，但误报率很高。统计和机器学习分析都强调对流不稳定性指标——最不稳定对流可用势能（MUCAPE）、Derecho复合参数（DCP）和k_index——是极端阵风的关键预测指标。因此，BARRA-SY阵风速度诊断告知强风阵风，但不告知极端情况，这取决于它忽略的变量。然而，不稳定性测量也不能完美地预测极端阵风，因为它们无法捕捉到在一些案例研究中看到的风暴触发条件。这些发现表明，驱动极端阵风的因素与驱动强烈但不那么极端的阵风的因素有很大不同。因此，综合考虑所有强风的统计分析或预测模型很可能无法揭示造成影响最大的最极端事件的环境因素。

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引用次数: 0

Convection-permitting WRF simulation of extreme winds in Canada: Present and future scenarios 允许对流的WRF模拟加拿大极端风：现在和未来情景

IF 6.1 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2025-09-01 Epub Date: 2025-05-29 DOI: 10.1016/j.wace.2025.100777

Xiao Ma, Yanping Li, Fei Huo, Zhenhua Li

This study investigates extreme wind events across southern Canada using 4-km convection-permitting WRF simulations under present (CTRL) and future (PGW) climate scenarios. The high resolution allows explicit representation of convective processes and complex terrain, improving local-scale wind prediction. We analyze three distinct regions—the central Prairies, Rocky Mountains, and southern Ontario—and find strong spatial and seasonal contrasts. Under future conditions, summer wind extremes intensify notably in the Prairies and southern Ontario, while winter winds decrease in the Prairies but increase in Ontario, Quebec, and mountainous areas. A conditional probability analysis based on Convective Available Potential Energy (CAPE) reveals that the likelihood of destructive winds (>20 m/s) rises significantly in convectively unstable environments. In southern Ontario, the probability under strong instability (CAPE >2500 J/kg) increases from nearly zero to 0.4. We also apply the Peaks-over-Threshold (POT) method to estimate 50-year return period wind speeds, which show substantial future increases, up to 6 m/s in some areas during summer. These changes indicate a rising threat from convectively driven wind extremes. This study highlights the value of convection-permitting models in resolving local wind features and emphasizes the need for region-specific adaptation strategies. The findings critically impact wind hazard assessment, infrastructure design, and climate resilience planning across southern Canada.

本研究在当前（CTRL）和未来（PGW）气候情景下，使用允许对流的4公里WRF模拟调查了加拿大南部的极端风事件。高分辨率使得对流过程和复杂地形的清晰表示成为可能，从而改善局地尺度的风预报。我们分析了三个不同的地区——中部大草原、落基山脉和安大略省南部——并发现了强烈的空间和季节反差。在未来的条件下，夏季极端风在大草原和安大略省南部明显加剧，而冬季风在大草原减少，而在安大略省，魁北克省和山区增加。基于对流有效势能（CAPE）的条件概率分析表明，在对流不稳定环境中，破坏性风（> 20m /s）发生的可能性显著增加。在安大略省南部，处于强不稳定状态（CAPE >2500 J/kg）的概率从接近零增加到0.4。我们还应用峰值超过阈值（POT）方法来估计50年的回归期风速，该方法显示出未来的大幅增加，在夏季某些地区可达6米/秒。这些变化表明，对流驱动的极端风的威胁正在上升。该研究强调了对流允许模式在解决局部风特征方面的价值，并强调了特定区域适应策略的必要性。这些发现对加拿大南部的风害评估、基础设施设计和气候适应性规划产生了重大影响。

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引用次数: 0

A hybrid statistical-dynamical method to translate past extreme temperature days into the future climate 一种将过去极端温度日转化为未来气候的混合统计-动力方法

IF 6.1 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2025-09-01 Epub Date: 2025-06-18 DOI: 10.1016/j.wace.2025.100785

Julien Boé, Margot Bador, Laurent Terray

This study presents a novel hybrid statistical-dynamical method intended to translate past observed weather events into the future climate, and applies it to warm and cold extreme temperature days over western Europe. The method estimates the temperature anomalies that would result if an observed event of the 1940–2023 period, defined in terms of atmospheric circulation, were to occur at the end of the 21st century, under new climatological conditions. In practice, constructed analogues of observed extreme events are built using data from regional climate projections. Three regional climate projections under the RCP8.5 emissions pathway are used in order to assess the role of model uncertainties in this context. The same approach is also used beforehand to assess the role of large-scale circulation in the observed extreme temperature days, and the ability of regional climate models to capture it is evaluated. The study finds significant variability in the role of atmospheric dynamics in extreme temperature days, contributing 35–80 % of the temperature anomaly for warm days and 20–90 % for cold days, with other factors such as land-atmosphere interactions playing an amplifying role. Regional climate models generally capture the dynamical part of temperature anomalies quite correctly. Not surprisingly extreme temperature days become more intense in the future climate, but a large inter-event spread exists. Some of the events could become much warmer, while others would not change much. Moreover, this intensification varies widely between regional climate models, and not necessarily in line with the average warming.

本研究提出了一种新的混合统计动力学方法，旨在将过去观测到的天气事件转化为未来的气候，并将其应用于西欧的温暖和寒冷极端温度日。该方法估计了在新的气候条件下，如果观测到的1940-2023年期间的事件（根据大气环流定义）发生在21世纪末，将导致的温度异常。在实践中，利用区域气候预估的数据构建观测到的极端事件的类似物。利用RCP8.5排放路径下的三个区域气候预估来评估模式不确定性在这一背景下的作用。同样的方法也预先用于评估大尺度环流在观测到的极端温度日数中的作用，并评估了区域气候模式捕捉大尺度环流的能力。研究发现，大气动力在极端温度日中的作用具有显著的变异性，对温暖日和寒冷日温度异常的贡献率分别为35 - 80%和20 - 90%，而陆-气相互作用等其他因子则起着放大作用。区域气候模式通常能相当准确地捕捉温度异常的动力部分。在未来的气候中，极端温度的天气会变得更加强烈，这并不奇怪，但存在一个大的事件间传播。有些事件可能会变得更加温暖，而其他事件则不会发生太大变化。此外，在不同的区域气候模式之间，这种强度差异很大，不一定与平均变暖一致。

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引用次数: 0

Downscaled CMIP6 future climate projections for New Zealand: climatology and extremes 缩小版CMIP6对新西兰未来气候的预估：气候学和极端事件

IF 6.1 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2025-09-01 Epub Date: 2025-05-29 DOI: 10.1016/j.wace.2025.100784

Peter B. Gibson , Ashley M. Broadbent , Stephen J. Stuart , Hamish Lewis , Isaac Campbell , Neelesh Rampal , Luke J. Harrington , Jonny Williams

Downscaled climate projections provide regionally relevant information for climate adaptation and planning purposes. Updated climate projections (∼12-km) are presented here for the New Zealand region, downscaling 6 global climate models (GCMs) from the Coupled Model Intercomparison Project (CMIP6) under a high emissions scenario (SSP3-7.0). Three regional climate models (RCMs) are used to explore differences when downscaling select GCMs. For end of century projections (relative to 1986–2005), the national multi-model annual mean warming is 3.1°C (model range 2.0–3.8°C) across downscaled simulations. Downscaling generally enhances warming over New Zealand relative to the GCMs, with the largest increases across high-elevation regions. There can be important differences in the projections across RCMs, including at national scales for temperature and across local-to-regional scales for precipitation. Averaged across models, annual extreme heatwaves become 3–5°C hotter for most regions. More frequent, intense, and longer duration meteorological drought is projected across northern and eastern regions of both islands. In terms of model uncertainty based on sign agreement, while summer mean precipitation projections carry the largest uncertainty, projections of summer meteorological drought and precipitation extremes can be made with greater confidence. These results provide a foundation for further targeted regional climate change impact and adaptation studies.

缩小尺度的气候预估为气候适应和规划目的提供区域相关信息。本文介绍了在高排放情景（SSP3-7.0）下，耦合模式比对项目（CMIP6）的6种全球气候模式（GCMs）对新西兰地区的最新气候预估（~ 12公里）。使用三种区域气候模式（rcm）来探讨选择gcm降尺度时的差异。对于世纪末预估（相对于1986-2005年），在缩小规模的模拟中，全国多模式年平均变暖为3.1°C（模式范围2.0-3.8°C）。相对于gcm，降尺度通常会增强新西兰的变暖，高海拔地区的增温幅度最大。跨rcm的预估可能存在重大差异，包括在国家尺度上的温度预估和在局地尺度上的降水预估。各模式的平均值显示，大多数地区的年极端热浪温度升高3-5°C。预计这两个岛屿的北部和东部地区将出现更频繁、更强烈和持续时间更长的气象干旱。在模式不确定性方面，夏季平均降水预估的不确定性最大，而夏季气象干旱和极端降水预估的置信度更高。这些结果为进一步开展有针对性的区域气候变化影响与适应研究奠定了基础。

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引用次数: 0

High-latitude lake influence on highly concentrated precipitation from cold-season storms in western Canada 高纬度湖泊对加拿大西部冷季风暴高度集中降水的影响

IF 6.1 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2025-09-01 Epub Date: 2025-05-10 DOI: 10.1016/j.wace.2025.100778

Fei Huo, Yanping Li, Zhenhua Li

Cold-season (October–March) storms, particularly severe snowstorms, are responsible for significant economic losses and have crucial impacts on freshwater availability and ecosystems in high-latitude North America. These snowstorms also contribute to destructive floods during rapid snowmelt. Thus, ecosystems and water infrastructure in Canada are highly sensitive to changes in cold-season storms under global warming. This study employs an object-based approach, specifically utilizing a storm-tracking algorithm, to investigate how cold-season storm precipitation in western Canada responds to climate change under a worst-case warming scenario. In the entire study area, peak daily precipitation greater than 50 mm day⁻¹ within storms significantly increases in both warm and cold seasons. The most extreme storms with highly concentrated precipitation (that is, storms with the precipitation intensity 5 times greater at the storm center compared to the area-averaged intensity), are expected to become more frequent in the future, particularly in the coastal regions and inland lake regions. More importantly, by analyzing the top 20 storms with the highest peak daily precipitation, we found that in the future, lakes will contribute more moisture to the atmosphere through increased evaporation, thereby intensifying the moisture supply and enhancing storm precipitation. Additionally, our findings indicate that future cold-season storms with highly concentrated precipitation may not increase evenly across each month. Warmer lakes in autumn, due to their high thermal inertia, will continue to provide significant local moisture to the atmosphere, which is crucial for the formation of highly concentrated precipitation. These findings suggest significant implications for understanding and predicting the impacts of climate change on storm dynamics and precipitation patterns over inland lakes.

寒冷季节（10月至3月）的风暴，特别是严重的暴风雪，造成了重大的经济损失，并对北美高纬度地区的淡水供应和生态系统产生了重大影响。在快速融雪期间，这些暴风雪也会造成破坏性的洪水。因此，在全球变暖的情况下，加拿大的生态系统和水利基础设施对寒冷季节风暴的变化高度敏感。本研究采用基于对象的方法，特别是利用风暴跟踪算法，调查在最坏的变暖情景下，加拿大西部冷季风暴降水如何响应气候变化。在整个研究区，风暴内大于50 mm day - 1的峰值日降水量在暖季和寒季均显著增加。降水高度集中的最极端风暴（即风暴中心降水强度比区域平均强度大5倍的风暴）预计将在未来变得更加频繁，特别是在沿海地区和内陆湖地区。更重要的是，通过对日降水量最高的前20次风暴的分析，我们发现在未来，湖泊将通过增加蒸发向大气贡献更多的水分，从而加强水分供应，增强风暴降水。此外，我们的研究结果表明，未来具有高度集中降水的冷季风暴可能不会在每个月均匀增加。由于较高的热惯性，秋季较暖的湖泊将继续为大气提供大量的局部水分，这对形成高度集中的降水至关重要。这些发现对理解和预测气候变化对内陆湖泊风暴动力学和降水模式的影响具有重要意义。

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引用次数: 0

Understanding drought onset: What makes flash droughts different from conventional droughts? 了解干旱的发生：是什么使突发性干旱与常规干旱不同？

IF 6.1 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2025-09-01 Epub Date: 2025-06-07 DOI: 10.1016/j.wace.2025.100782

Pallavi Goswami , Ailie J.E. Gallant

This study examines the timescales of drought onset to understand the differences between rapid onset droughts, called flash droughts, and the more conventional slow-onset droughts. Using a soil moisture-based drought identification approach, we show that soil moisture across most of Australia can transition from near-normal to drought conditions within one month’s time. The median duration for non-rapid drought onset, here called a conventional drought, is 30 days, while the rapid onset drought, here called a flash drought, takes around 15 days, indicating that the difference in onset timescales of the two drought types is relatively small. Further, our findings reveal that changes to precipitation and evaporative conditions during a flash drought onset are not very different from those that cause a conventional drought onset. However, flash drought development is associated with larger magnitude of anomalies of those variables leading to drought conditions. These larger anomalies during flash droughts reduce soil moisture rapidly, with a potential to cause damage to vegetation health without sufficient early warning. Although there is a diversity in the mechanisms causing flash droughts, we show here that the majority of the flash droughts are primarily related to the joint influence of abnormally low precipitation and heightened incoming solar radiation (low cloud cover) and large vapour pressure deficits (low relative humidity). The results emphasise the need to update existing drought monitoring systems to account for more realistic timescales of drought onsets for better early warning and preparedness.

本研究考察了干旱发生的时间尺度，以了解快速发生的干旱（称为骤发干旱）和更常规的缓慢发生的干旱之间的差异。使用基于土壤湿度的干旱识别方法，我们表明澳大利亚大部分地区的土壤湿度可以在一个月内从接近正常的状态过渡到干旱状态。非快速干旱（这里称为常规干旱）的中位持续时间为30天，而快速干旱（这里称为突发性干旱）的中位持续时间约为15天，这表明两种干旱类型的发生时间尺度差异相对较小。此外，我们的研究结果表明，在突发性干旱发生期间，降水和蒸发条件的变化与导致常规干旱发生的变化没有太大不同。然而，突发性干旱的发展与导致干旱条件的这些变量的较大程度的异常有关。在突然性干旱期间，这些较大的异常会迅速降低土壤湿度，如果没有足够的早期预警，可能会对植被健康造成损害。虽然造成暴发性干旱的机制多种多样，但我们在这里表明，大多数暴发性干旱主要与异常低降水、入射太阳辐射增强（低云量）和大蒸汽压差（低相对湿度）的共同影响有关。这些结果强调需要更新现有的干旱监测系统，以便考虑到更现实的干旱发生时间尺度，从而更好地进行早期预警和准备。

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引用次数: 0

The contribution of climate drivers to compound drought and extreme temperature events increased in recent decades 近几十年来，气候驱动因素对复合干旱和极端温度事件的贡献有所增加

IF 6.1 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2025-09-01 Epub Date: 2025-07-05 DOI: 10.1016/j.wace.2025.100793

Siyi Li , Bin Wang , De Li Liu , Chao Chen , Puyu Feng , Alfredo Huete , Keyu Xiang , Qiang Yu

Compound climate extremes severely impact crops more than individual events. Understanding historical changes in compound extreme events and their drivers is crucial for managing climate risks and protecting crop survival. Using a hybrid biophysical-statistical modeling approach, we investigated the connections between large-scale climate drivers of El Niño Southern Oscillation (ENSO)/Indian Ocean Dipole (IOD) and compound drought and extreme temperature (DET) across Australia's wheat belt from 1900 to 2020. DET in eastern Australia's wheat belt was more responsive to ENSO/IOD compared to the west. El Niño and positive IOD phases intensified DET and increased the probability of high-intensity DET, whereas La Niña and negative IOD reduced them. Probabilities of high-intensity DET have exhibited a temporal increase, during the strong El Niño phase and the positive IOD phase. Our findings highlight the need to assess the spatial-temporal response of compound events to climate drivers for effective early warning and mitigation.

复合极端气候对农作物的影响比个别事件更严重。了解复合极端事件的历史变化及其驱动因素对于管理气候风险和保护作物生存至关重要。采用混合生物物理-统计建模方法，研究了1900 - 2020年厄尔尼诺Niño南方涛动(ENSO)/印度洋偶极子（IOD）大尺度气候驱动因子与澳大利亚小麦带复合干旱和极端温度（DET）之间的关系。与西部相比，澳大利亚东部小麦带的DET对ENSO/IOD的响应更大。El Niño和IOD阳性期增强了DET，增加了高强度DET的概率，而La Niña和IOD阴性期则降低了DET的概率。在强El Niño期和正IOD期，高强度DET的概率在时间上有所增加。我们的研究结果强调需要评估复合事件对气候驱动因素的时空响应，以实现有效的早期预警和缓解。

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引用次数: 0

Influence of the East Asia‒Pacific and Eurasian teleconnection on the summer marine heatwaves in the Japan/East Sea 东亚-亚太和欧亚遥相关对日本/东海夏季海洋热浪的影响

IF 6.1 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Climate Extremes

Pub Date : 2025-09-01 Epub Date: 2025-05-29 DOI: 10.1016/j.wace.2025.100783

Kaidi Huang , Gang Zeng , Aminu Dalhatu Datti , Changming Dong

Marine heatwaves (MHWs) are an escalating global issue, posing significant threats to marine ecosystems and the fisheries economy worldwide, including in the Japan/East Sea (JES). However, the influence of atmospheric circulation modes on the occurrence of MHWs in this relatively enclosed sea area remains unclear. To address this issue, this study utilizes 1982–2023 high-resolution daily satellite sea surface temperature (SST) data and atmospheric reanalysis products to investigate the relationship between atmospheric circulation modes and MHWs in the JES. The results show that during 1982–2023, the JES experienced severe summer MHWs, primarily driven by intense shortwave radiation linked to atmospheric activities. The East Asia-Pacific (EAP) pattern was found to influence the MHWs in the JES. Notably, we identified an interdecadal change in the relationship between MHWs and EAP patterns around 2001. Before 2001, there was a strong correlation (r = 0.68, p < 0.01) between MHWs in the JES and the EAP, but this relationship weakened significantly in the following years. During the 1982–2000 period, MHWs in the JES were primarily influenced by tropical convection over the South China Sea and the Philippine region, which triggered poleward Rossby wave propagation. Furthermore, since 2001, MHWs have shown a strong correlation with the summer Eurasian (EU) teleconnection, a zonal wave train situated over Eurasia. The correlation between EU and MHWs has reached 0.6 (p < 0.01) during the period from 2001 to 2023, in contrast to a weak negative correlation observed in the preceding EAP dominated period. This EU type mode is linked to warm SST anomalies in the North Atlantic and cold SST anomalies in the north of Western Europe from April to August. The Linear Baroclinic Model (LBM) and NCAR CAM5.3 can effectively validate the conclusions of the observations.

海洋热浪（MHWs）是一个不断升级的全球问题，对包括日本/东海（JES）在内的全球海洋生态系统和渔业经济构成重大威胁。然而，在这一相对封闭的海域，大气环流模式对强震发生的影响尚不清楚。为了解决这一问题，本研究利用1982-2023年高分辨率卫星海表温度（SST）日数据和大气再分析产品，研究了JES大气环流模式与强震的关系。结果表明：1982—2023年，日本副热带地区经历了强烈的夏季强震，主要由与大气活动相关的强短波辐射驱动。发现东亚-亚太（EAP）模式影响了日本副热带的强震。值得注意的是，我们确定了2001年前后MHWs和EAP模式之间关系的年代际变化。在2001年之前，有很强的相关性(r = 0.68, p <；在JES和EAP的MHWs之间存在0.01)，但这种关系在随后的几年中显著减弱。1982-2000年期间，日本副热带强震主要受南海和菲律宾地区热带对流的影响，引发了Rossby波向极地的传播。此外，自2001年以来，mhw已显示出与夏季欧亚（EU）遥相关的强相关性，这是一种位于欧亚大陆上空的纬向波列。EU与MHWs的相关系数达到0.6 (p <；0.01)，而在此之前的EAP主导期则呈弱负相关。这种EU型模态与4 - 8月北大西洋海温偏暖和西欧北部海温偏冷有关。线性斜压模型（LBM）和NCAR CAM5.3可以有效地验证观测结果的结论。

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