Weather and Climate Extremes最新文献_第2页

Unravelling the complex interplay between daily and sub-daily rainfall extremes in different climates 揭示不同气候条件下每日和次每日极端降雨量之间复杂的相互作用

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

Weather and Climate Extremes

Pub Date : 2024-10-18 DOI: 10.1016/j.wace.2024.100735

Selma B. Guerreiro , Stephen Blenkinsop , Elizabeth Lewis , David Pritchard , Amy Green , Hayley J. Fowler

Understanding short-duration intense rainfall is crucial for mitigating flash floods, landslides, soil erosion, and pollution incidents. Yet, most observations from rain gauges are only available at the daily resolution. We use the new Global Sub Daily Rainfall dataset to explore extreme rainfall at both daily and sub-daily durations worldwide. Employing Single Gauge Analysis (SGA) and pioneering global-scale Regional Frequency Analysis (RFA), we reveal for the first time how Generalized Extreme Value Distribution (GEV) parameters change across climates and data durations (1h, 3h, 6h, 24h, and daily). This marks the first-ever near-global-scale RFA, made possible by the development of an algorithm that automates RFA on observed rainfall datasets. We compare our results with GEV applied to a gridded rainfall reanalysis (ERA5). Our key findings are that: 1) using ERA5, return levels are significantly underestimated across all climates for 1h rainfall and across all data durations for gauges in the tropical climate region. Even when accounting for differences between point and areal estimates, the median 1h return level estimates are approximately 40% lower compared to RFA. We therefore strongly advise against the use of reanalysis gridded rainfall for studying these extremes. 2) While most gauges show similar return levels with RFA or SGA, some differ significantly, and either method may yield the highest values. Thus, we strongly recommend using both SGA and RFA simultaneously to estimate return levels for a robust risk assessment in flood infrastructure design. 3) The interaction between daily and sub-daily GEV shape parameters varies across climate regions, rendering a universal method for inferring sub-daily rainfall extremes from daily extremes (e.g., using Intensity-Duration-Frequency curves) impractical. Our research provides innovative methodological insights that warrant consideration in future studies on rainfall extremes. Our results not only benefit local stakeholders globally but also serve as a crucial validation tool for the rising number of convection-permitting climate model experiments conducted worldwide.

了解短时强降雨对缓解山洪、山体滑坡、水土流失和污染事件至关重要。然而，大多数雨量计的观测数据只有日分辨率。我们利用新的全球亚日降雨量数据集来探索全球日降雨量和亚日降雨量的极端降雨情况。利用单雨量计分析（SGA）和开创性的全球尺度区域频率分析（RFA），我们首次揭示了广义极值分布（GEV）参数在不同气候和数据持续时间（1 小时、3 小时、6 小时、24 小时和每日）下的变化情况。这标志着有史以来第一次近乎全球范围的广义极值分布（RFA）成为可能，而这得益于对观测降雨数据集自动进行广义极值分布的算法的开发。我们将结果与应用于网格降雨再分析（ERA5）的 GEV 进行了比较。我们的主要发现有1) 使用ERA5，在热带气候区域的所有气候条件下，1小时降雨量和所有数据持续时间的回归水平都被明显低估。即使考虑到点估计值和区域估计值之间的差异，1 小时回归水平估计值的中位数也比 RFA 低约 40%。因此，我们强烈建议不要使用再分析网格降雨量来研究这些极端情况。2) 虽然大多数测站在使用 RFA 或 SGA 时显示出相似的回归水平，但有些测站的回归水平差异很大，而这两种方法都可能得出最高值。因此，我们强烈建议同时使用 SGA 和 RFA 估算回归水位，以便在洪水基础设施设计中进行可靠的风险评估。3) 日极端降雨量和次日极端降雨量形状参数之间的相互作用因气候区域而异，因此从日极端降雨量推断次日极端降雨量的通用方法（如使用强度-持续时间-频率曲线）不切实际。我们的研究提供了创新的方法论见解，值得在未来的极端降雨研究中加以考虑。我们的研究成果不仅有利于全球的地方利益相关者，而且也是全球范围内开展的对流允许气候模型实验数量不断增加的重要验证工具。

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引用次数: 0

How unusual was Australia's 2017–2019 Tinderbox Drought? 澳大利亚 2017-2019 年的 "火药桶干旱 "有多不寻常？

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

Weather and Climate Extremes

Pub Date : 2024-10-17 DOI: 10.1016/j.wace.2024.100734

Georgina Falster , Sloan Coats , Nerilie Abram

Australia's Murray-Darling Basin experienced three consecutive years of meteorological drought across 2017–2019, collectively named the ‘Tinderbox Drought’. Rainfall deficits during the three-year drought were most pronounced in the Australian cool season (April to September). Deficits in both the cool season and annual total rainfall were unprecedented in the instrumental record. However, the instrumental record provides just one of a range of equally plausible climate trajectories that could have occurred during this period. To determine if the Tinderbox Drought was outside this range, we used observational data from prior to the onset of the drought to construct Linear Inverse Models (LIMs) that emulate the stationary statistics of Australian rainfall and its connection to global sea surface temperature (SST) anomalies. Overall, we find that rainfall deficits were most unusual in the northern Murray-Darling Basin, and during the final year of the drought. The global SST anomalies observed during the first two years of the Tinderbox Drought, particularly the cool anomalies in the central tropical Pacific and western Indian Ocean, are not typically associated with low rainfall across the Murray-Darling Basin. In terms of single-year rainfall anomalies, the only aspect of the Tinderbox Drought that was beyond the range of the LIMs was annual-total rainfall over the northern Murray-Darling Basin during 2019. This coincided with an extreme positive Indian Ocean Dipole event that was also beyond the range of the LIMs. When considered in terms of basin-wide rainfall over the full three years, rainfall deficits during the Tinderbox Drought were beyond the LIM range in terms of both cool-season and annual-total rainfall. This suggests an anthropogenic contribution to the severity of the drought—likely exacerbated by the 2019 extreme positive Indian Ocean Dipole event.

2017-2019 年间，澳大利亚墨累-达令盆地连续三年遭遇气象干旱，被统称为 "火药桶干旱"。三年干旱期间，澳大利亚冷季（4 月至 9 月）的降雨量不足最为明显。冷季降雨量和全年总降雨量的不足在仪器记录中都是前所未有的。然而，仪器记录只是提供了这一时期可能出现的一系列同样合理的气候轨迹之一。为了确定 Tinderbox 旱灾是否超出了这一范围，我们利用旱灾发生前的观测数据构建了线性反演模型 (LIM)，模拟澳大利亚降雨量的静态统计及其与全球海面温度 (SST) 异常的联系。总体而言，我们发现在墨累-达令盆地北部以及干旱的最后一年，降雨量不足的情况最为异常。在 Tinderbox 旱灾的前两年观测到的全球 SST 异常，尤其是热带太平洋中部和印度洋西部的低温异常，通常与墨累-达令盆地的降雨量偏低无关。就单年降雨量异常而言，Tinderbox 旱灾中唯一超出 LIMs 范围的是 2019 年墨累-达令盆地北部的年总降雨量。这与印度洋偶极子极端正向事件相吻合，该事件也超出了 LIMs 的范围。从整个三年的全流域降雨量来看，Tinderbox 旱灾期间的冷季降雨量和年总降雨量都超出了 LIM 范围。这表明干旱的严重程度是人为因素造成的--2019 年印度洋偶极子极端事件可能加剧了干旱。

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引用次数: 0

Projected changes in mean climate and extremes from downscaled high-resolution CMIP6 simulations in Australia 澳大利亚降尺度高分辨率 CMIP6 模拟对平均气候和极端气候的预测变化

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

Weather and Climate Extremes

Pub Date : 2024-10-16 DOI: 10.1016/j.wace.2024.100733

Sarah Chapman , Jozef Syktus , Ralph Trancoso , Nathan Toombs , Rohan Eccles

High-resolution climate change projections are required to evaluate local and regional climate change impacts. We used CCAM (Conformal Cubic Atmospheric Model) to dynamically downscale CMIP6 GCMs (Global Climate Models) over Australia under three emissions scenarios, producing a set of 60 simulations at a 10 km resolution. Previous work has evaluated the performance of the downscaled models in the historical period. Here, we evaluate the impact of end-of-century climate change in the downscaled CMIP6-CCAM models for mean and extreme climate under three Shared Socioeconomic Pathways (SSP126, 245 and 370). We find the changes in mean climate are in general similar in the host CMIP6 and downscaled models. For extreme temperature, we find that extreme maximum temperatures (TXx) increase by 3.4 °C, while extreme minimum temperatures (TNn) warm by 3.0 °C. Extreme precipitation generally increases in summer and decreases in winter; however, there is a large amount of inter-model variation in the location and magnitude of change. Consecutive dry days also decrease in most areas in Austral summer and increase in Austral winter. Heatwaves become more frequent and hotter by the end of the century. These results suggest a hotter, wetter Austral summer, with longer, more frequent and more intense heatwaves, and a hotter and drier Austral winter in most areas. This dataset provides useful new high-resolution information on how climate change is likely to impact Australia, which will be a valuable resource to underpin local adaptation responses to future impacts.

评估地方和区域气候变化影响需要高分辨率的气候变化预测。我们利用 CCAM（共形立方大气模型）对三种排放情景下澳大利亚的 CMIP6 GCM（全球气候模型）进行了动态降尺度，产生了一组分辨率为 10 千米的 60 个模拟结果。以前的工作评估了降尺度模型在历史时期的性能。在此，我们评估了在三种共享社会经济路径（SSP126、245 和 370）下，缩小尺度的 CMIP6-CCAM 模型对平均气候和极端气候的世纪末气候变化的影响。我们发现，在 CMIP6 主模式和降尺度模式中，平均气温的变化基本相似。在极端气温方面，我们发现极端最高气温（TXx）升高了 3.4 ℃，而极端最低气温（TNn）升高了 3.0 ℃。极端降水量一般在夏季增加，冬季减少；然而，在变化的位置和幅度上，模式间存在很大差异。澳大拉西亚夏季大部分地区的连续干旱日也会减少，而澳大拉西亚冬季则会增加。到本世纪末，热浪会变得更加频繁和炎热。这些结果表明，澳大拉西亚夏季更热、更湿，热浪更长、更频繁、更剧烈，大部分地区的澳大拉西亚冬季更热、更干燥。该数据集提供了关于气候变化可能如何影响澳大利亚的有用的新的高分辨率信息，将成为支持当地适应未来影响的宝贵资源。

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引用次数: 0

Forecasting the groundwater levels in the Baltic through standardized index analysis 通过标准化指数分析预测波罗的海地下水位

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

Weather and Climate Extremes

Pub Date : 2024-10-11 DOI: 10.1016/j.wace.2024.100728

Alise Babre , Konrāds Popovs , Andis Kalvāns , Marta Jemeļjanova , Aija Dēliņa

In regions where groundwater forms the primary source of drinking water, comprehending the prospective availability of subsurface water resources due to climate change is of paramount importance.

This study evaluates the impact of climate change on groundwater levels in the Baltic States until the end of this century. It employs link between surface and subsurface standardized indices. For forecast it uses various Representative Concentration Pathways (RCP) alongside different Regional Climate Models (RCM).

By linking historical groundwater drought episodes with calculated surface drought indices and accumulation periods observed during defined climate Normals, we project groundwater levels for the short, medium, and long-term future. The study incorporates 13 EURO-CORDEX RCMs under three RCP scenarios.

Our analysis reveals that, compared to the recent climate Normals, an overall increase in groundwater levels is expected at most study sites. However, lower groundwater levels are estimated in the near future. The projected impacts show no significant seasonal bias or spatial conformity. Although these findings are specific to the Baltic region, the methodologies described can be readily adapted for global application.

在地下水构成主要饮用水源的地区，了解气候变化对地下水资源的预期可用性至关重要。研究采用了地表和地下标准化指数之间的联系。通过将历史上的地下水干旱事件与计算出的地表干旱指数以及在确定的气候常态期间观测到的累积期联系起来，我们预测了未来短期、中期和长期的地下水位。我们的分析表明，与最近的气候正常值相比，大多数研究地点的地下水位预计会整体上升。然而，预计在不久的将来地下水位会降低。预测的影响没有显示出明显的季节偏差或空间一致性。虽然这些研究结果是波罗的海地区特有的，但所述方法可随时在全球范围内应用。

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引用次数: 0

Fast generation of high-dimensional spatial extremes 快速生成高维空间极值

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

Weather and Climate Extremes

Pub Date : 2024-10-09 DOI: 10.1016/j.wace.2024.100732

Hans Van de Vyver

Widespread extreme climate events cause many fatalities, economic losses and have a huge impact on critical infrastructure. It is therefore of utmost importance to estimate the frequency and associated consequences of spatially concurrent extremes. Impact studies of climate extremes are severely hampered by the lack of extreme observations, and even large ensembles of climate simulations often do not include enough extreme or record-breaking climate events for robust analysis. On the other hand, weather generators specifically fitted to extreme observations can quickly generate many physically or statistically plausible extreme events, even with intensities that have never been observed before. We propose a Fourier-based algorithm for generating high-resolution synthetic datasets of rare events, using essential concepts of classical modelling of (spatial) extremes. Here, the key feature is that the stochastically generated datasets have the same spatial dependence as the observed extreme events. Using high-resolution gridded precipitation and temperature datasets, we show that the new algorithm produces realistic spatial patterns, and is particularly attractive compared to other existing methods for spatial extremes. It is exceptionally fast, easy to implement, scalable to high dimensions and, in principle, applicable for any spatial resolution. We generated datasets with 10,000 gridpoints, a number that can be increased without difficulty. Since current impact models often require high-resolution climate inputs, the new algorithm is particularly useful for improved impact and vulnerability assessment.

大范围的极端气候事件会造成大量人员伤亡和经济损失，并对关键基础设施产生巨大影响。因此，估算空间上同时发生的极端事件的频率和相关后果至关重要。由于缺乏极端观测数据，对极端气候影响的研究受到严重阻碍，即使是大型气候模拟集合也往往没有足够的极端或破纪录气候事件来进行可靠的分析。另一方面，专门根据极端观测数据拟合的天气生成器可以快速生成许多物理上或统计上可信的极端事件，甚至是以前从未观测到的强度。我们提出了一种基于傅立叶的算法，利用（空间）极端事件经典建模的基本概念，生成高分辨率的罕见事件合成数据集。该算法的主要特点是随机生成的数据集与观测到的极端事件具有相同的空间依赖性。通过使用高分辨率网格降水和气温数据集，我们发现新算法能产生逼真的空间模式，与其他现有的空间极端事件方法相比，新算法尤其具有吸引力。该算法异常快速、易于实施、可扩展至高维度，原则上适用于任何空间分辨率。我们生成了包含 10,000 个网格点的数据集，这个数字可以毫无困难地增加。由于目前的影响模型通常需要高分辨率的气候输入，新算法对于改进影响和脆弱性评估特别有用。

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引用次数: 0

Anthropogenic influence on precipitation in Aotearoa New Zealand with differing circulation types 不同环流类型对新西兰奥特亚罗瓦降水的人为影响

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

Weather and Climate Extremes

Pub Date : 2024-10-05 DOI: 10.1016/j.wace.2024.100727

Anjali Thomas , Adrian McDonald , James Renwick , Suzanne Rosier , Jordis S. Tradowsky , Gregory E. Bodeker

This study quantifies the influences of anthropogenic forcing to date on precipitation over Aotearoa New Zealand (ANZ). Large ensembles of simulations from the weather@home regional climate model experiments are analysed under two scenarios, a natural (NAT) or counter-factual scenario which excludes human-induced changes to the climate system and an anthropogenic (ANT) or factual scenario. The impacts of anthropogenic forcing on precipitation are analysed in the context of large-scale circulation types characterized using an existing Self Organizing Map classification. The combined effect of both thermodynamics and dynamics are compared with values expected from the Clausius–Clapeyron (C–C) relation. Changes in the precipitation intensity due to greenhouse gas-forced temperature rise are lower than the expected C–C value. However extreme precipitation changes approach the C–C value for some circulation types. Specifically westerly flows enhance precipitation change across ANZ relative to the C–C rate, particularly over the West Coast. Conversely, northwesterly flows reduce the change over the North Island relative to the C–C value. Moreover, the wet day frequency generally reduces in the ANT scenario relative to NAT, reductions are largest on the West Coast of the South Island for westerly flows. Additionally, the frequency of days with extreme precipitation rises over ANZ for most circulation patterns, except in Northland and for northwesterly flows. This underscores the combined influence of dynamics and thermodynamics in shaping both precipitation intensity and frequency patterns across ANZ.

本研究量化了迄今为止人类活动对新西兰奥特亚罗瓦降水量的影响。研究分析了 "天气@家"（weather@home）区域气候模式实验在两种情景下的大型模拟集合，一种是自然情景（NAT）或反事实情景，即排除人为因素对气候系统造成的变化；另一种是人为情景（ANT）或事实情景。人为强迫对降水的影响是在大尺度环流类型的背景下利用现有的自组织地图分类特征进行分析的。热力学和动力学的综合影响与克劳修斯-克拉皮隆（C-C）关系的预期值进行了比较。温室气体导致的温度上升引起的降水强度变化低于预期的 C-C 值。然而，某些环流类型的极端降水变化接近 C-C 值。具体来说，相对于 C-C 值，西风流增强了整个澳新地区的降水变化，尤其是在西海岸。相反，相对于 C-C 值，西北气流会减少北岛的降水变化。此外，相对于 NAT，ANT 情景下的湿润日频率普遍降低，在南岛西海岸，西风流的降低幅度最大。此外，除北岛和西北气流外，在大多数环流模式下，澳新地区的极端降水日频率都有所上升。这突出表明，动力学和热力学共同影响着整个澳新地区的降水强度和降水频率模式。

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引用次数: 0

The 2022 record-high heat waves over southwestern Europe and their underlying mechanism 2022 年欧洲西南部上空创纪录的高温热浪及其内在机制

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

Weather and Climate Extremes

Pub Date : 2024-10-01 DOI: 10.1016/j.wace.2024.100729

Jeong-Hun Kim , So-Hyun Nam , Maeng-Ki Kim , Roberto Serrano-Notivoli , Ernesto Tejedor

Recently, the intensity and frequency of heat waves (HWs) have been increased worldwide. Particularly in 2022, Europe was severely affected by unprecedented HWs, which caused approximately 61,672 deaths and 11,324 deaths in Europe and Spain, respectively. In this study, we investigate the mechanisms of the HWs in southwestern Europe (SWEU) to identify the differences between typical HWs and the extreme HWs that occurred in 2022. Our results showed that the SWEU events in 2022 were strongly related to robust heat domes that developed in the lower troposphere due to high-pressure anomalies especially during two periods (9–18 June and 8–19 July). Analyses of the energy budget and thermodynamic equation revealed the processes underlying the amplification of the heat domes over SWEU during both periods. We also discovered that abnormal atmospheric blocking in the upper troposphere was closely associated with the amplification of the Gulf Stream SST, which caused an atmospheric circulation pattern favorable for the 2022 SWEU-HWs. This was further confirmed by modeling experiments. Therefore, our results emphasize that a Gulf Stream SST amplification can trigger an atmospheric circulation pattern favorable for extreme HWs in SWEU, enhancing our understanding of the mechanism behind extreme HWs. Finally, our findings will help improving the forecasting of SWEU-HWs on a sub-seasonal time scale, as well as future projections in global climate models.

最近，全球热浪（HWs）的强度和频率都有所增加。特别是在 2022 年，欧洲受到了前所未有的热浪的严重影响，在欧洲和西班牙分别造成约 61 672 人和 11 324 人死亡。在这项研究中，我们调查了欧洲西南部（SWEU）HWs 的机制，以确定典型 HWs 与 2022 年发生的极端 HWs 之间的差异。我们的研究结果表明，2022 年的西南欧高温事件与对流层低层因高压异常而形成的强热穹丘密切相关，尤其是在两个时段（6 月 9 日至 18 日和 7 月 8 日至 19 日）。对能量预算和热力学方程的分析揭示了这两个时段西南太平洋大学上空热穹放大的基本过程。我们还发现，对流层上部的异常大气阻塞与湾流 SST 的放大密切相关，这导致了有利于 2022 年西南欧-HWs 的大气环流模式。模拟实验进一步证实了这一点。因此，我们的研究结果强调了湾流 SST 的放大可以引发有利于西南太平洋极端 HWs 的大气环流模式，从而加深了我们对极端 HWs 背后机理的理解。最后，我们的研究结果将有助于改进西南欧-HWs 在亚季节时间尺度上的预报，以及全球气候模式的未来预测。

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引用次数: 0

The flash droughts across the south-central United States in 2022: Drivers, predictability, and impacts 2022 年美国中南部的暴旱：驱动因素、可预测性和影响

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

Weather and Climate Extremes

Pub Date : 2024-10-01 DOI: 10.1016/j.wace.2024.100730

Jordan I. Christian , Taylor M. Grace , Benjamin J. Fellman , Daniel F. Mesheske , Stuart G. Edris , Henry O. Olayiwola , Jeffrey B. Basara , Brian A. Fuchs , Jason C. Furtado

A rare subseasonal-to-seasonal phenomenon – two consecutive flash drought events interrupted by a period of recovery – occurred across eastern Oklahoma, Arkansas, and southern Missouri, spanning the summer and early fall of 2022. These flash drought events (the first in June–July, the second in August–September) led to severe (D2) and extreme (D3) drought conditions via the United States Drought Monitor across much of the region following the first period of rapid drought intensification, and extreme (D3) and exceptional (D4) drought conditions by the end of the second event. A notable driver of both flash drought events included a persistent upper-level ridge either centered over or shifted west and upstream of the flash drought region, leading to broad-scale subsidence and reduced mid-level moisture which acted to limit precipitation development and increase evaporative demand. In addition, several heatwave events developed during the warm season in 2022 and either (1) acted to drive flash drought development via increased evaporative demand or (2) were enhanced by land surface desiccation and land-atmosphere feedbacks following rapid drought intensification. Furthermore, S2S composite forecasts predicted drought development for both events. However, only 20% of the ensembles predicted rapid drought development associated with flash drought for the first event and 16% of the ensembles predicted rapid drought development during the second event. This result highlights a key challenge in S2S prediction of rapidly developing drought conditions versus that of more conventional and slower drought development. The ensembles that did predict rapid drought intensification were associated with the forecasting of positive 500 hPa geopotential height anomalies over the south-central United States (first event) or an amplified wave pattern centered over the west-central United States (second event). Lastly, the compounding effects of two flash droughts in a single warm season led to substantial impacts on agricultural, environmental, and hydrologic sectors across the region.

2022 年夏季和初秋期间，俄克拉荷马州东部、阿肯色州和密苏里州南部出现了罕见的亚季节到季节现象--连续两次闪电干旱事件被一段恢复期打断。这些山洪暴发的干旱事件（第一次在 6-7 月，第二次在 8-9 月）在第一个快速干旱加剧期结束后，通过美国干旱监测，该地区大部分地区出现了严重（D2）和极端（D3）干旱状况，而在第二个干旱事件结束时，出现了极端（D3）和特殊（D4）干旱状况。这两次暴旱事件的一个显著驱动因素是持续的高空海脊，要么位于暴旱区域的中心，要么向西和上游移动，导致大范围下沉和中层水汽减少，从而限制了降水的发展并增加了蒸发需求。此外，2022 年暖季期间还出现了几次热浪事件，这些热浪事件（1）通过增加蒸发需求推动了闪旱的发展，或（2）在干旱迅速加剧后，陆地表面干燥和陆地-大气反馈作用增强了闪旱的发展。此外，S2S 综合预报预测了这两种事件的干旱发展。然而，只有 20% 的集合预测了第一次事件中与闪旱相关的快速干旱发展，16% 的集合预测了第二次事件中的快速干旱发展。这一结果凸显了 S2S 预测快速发展的干旱状况与预测更传统、更缓慢的干旱发展的关键挑战。预测到干旱迅速加剧的集合与预测到美国中南部上空出现正的 500 hPa 位势高度异常（第一次事件）或以美国中西部为中心的波浪模式扩大（第二次事件）有关。最后，在一个暖季发生两次暴旱的复合效应对整个地区的农业、环境和水文部门造成了巨大影响。

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引用次数: 0

Future changes of socioeconomic exposure to potential landslide hazards over mainland China 中国大陆潜在滑坡灾害对社会经济影响的未来变化

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

Weather and Climate Extremes

Pub Date : 2024-10-01 DOI: 10.1016/j.wace.2024.100731

Donghuan Li , Youcun Qi , Tianjun Zhou , Wenxia Zhang

Landslides are among the most destructive natural disasters, having huge socioeconomic impacts. Here, we investigate future changes in potential rainfall-induced landslide activities and their socioeconomic consequences in mainland China using CMIP6 simulations under five combined scenarios of the Shared Socioeconomic Pathways and the Representative Concentration Pathways (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5). The potential landslide activities over mainland China are projected to increase over the 21st century. The regional mean increases over mainland China under the SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, at the end of the 21st century, are approximately 20.6%, 24.8%, 27.2%, 33.1%, and 46.5%, respectively, compared to present day. Population exposure to potential landslide hazards is projected to increase under SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, but decline under SSP1-1.9 and SSP1-2.6 scenarios due to population reduction. Meanwhile, economic exposure is expected to rise substantially across mainland China due to the greatly increased GDP. In general, the most populous and economically developed southern China will experience the largest socioeconomic exposure percentage increase among the subregions due to the joint influence of climate change and socioeconomic change. Compared with SSP1-1.9 scenario, the higher emission levels of SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 will result in 20.4%, 32.0%, 60.6%, and 125.8% more increases in potential landslide days and 16.2%, 42.9%, 80.3%, and 4.6% less increases in anti-risk capacity (ability to resist landslide risk) in mainland China, respectively, at the end of the 21st century. The southern Tibetan Plateau is projected to experience greater increases in landslide days and decreases in anti-risk capacity than other subregions, if high emission scenarios are selected over SSP1-1.9.

滑坡是最具破坏性的自然灾害之一，对社会经济影响巨大。在此，我们利用 CMIP6 模拟，在 "共享社会经济路径 "和 "代表性浓度路径"（SSP1-1.9、SSP1-2.6、SSP2-4.5、SSP3-7.0 和 SSP5-8.5）的五种组合情景下，研究了中国大陆未来由降雨引发的潜在滑坡活动的变化及其社会经济后果。预计 21 世纪中国大陆上空潜在的滑坡活动将会增加。在 SSP1-1.9、SSP1-2.6、SSP2-4.5、SSP3-7.0 和 SSP5-8.5 情景下，21 世纪末中国大陆的区域平均值与现在相比分别增加了约 20.6%、24.8%、27.2%、33.1% 和 46.5%。预计在 SSP2-4.5、SSP3-7.0 和 SSP5-8.5 情景下，潜在滑坡灾害对人口的影响将增加，但在 SSP1-1.9 和 SSP1-2.6 情景下，由于人口减少，潜在滑坡灾害对人口的影响将下降。同时，由于 GDP 大幅增加，预计中国大陆各地的经济风险将大幅上升。总体而言，在气候变化和社会经济变化的共同影响下，人口最多、经济最发达的华南将是各分区域中社会经济风险增加比例最大的地区。与 SSP1-1.9 情景相比，SSP1-2.6、SSP2-4.5、SSP3-7.0 和 SSP5-8.5 的较高排放水平将导致 21 世纪末中国大陆潜在滑坡日分别增加 20.4%、32.0%、60.6% 和 125.8%，抗风险能力（抵抗滑坡风险的能力）分别减少 16.2%、42.9%、80.3% 和 4.6%。如果在 SSP1-1.9 的基础上选择高排放情景，预计青藏高原南部的滑坡日数将比其他次区域增加更多，抗风险能力将下降更多。

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引用次数: 0

Downscaling, bias correction, and spatial adjustment of extreme tropical cyclone rainfall in ERA5 using deep learning 利用深度学习对ERA5中的极端热带气旋降雨量进行降尺度、纠偏和空间调整

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

Weather and Climate Extremes

Pub Date : 2024-09-30 DOI: 10.1016/j.wace.2024.100724

Guido Ascenso , Andrea Ficchì , Matteo Giuliani , Enrico Scoccimarro , Andrea Castelletti

Hydrological models that are used to analyse flood risk induced by tropical cyclones often input ERA5 reanalysis data. However, ERA5 precipitation has large systematic biases, especially over heavy precipitation events like Tropical Cyclones, compromising its usefulness in such scenarios. Few studies to date have performed bias correction of ERA5 precipitation and none of them for extreme rainfall induced by tropical cyclones. Additionally, most existing works on bias adjustment focus on adjusting pixel-wise metrics of bias, such as the Mean Squared Error (MSE). However, it is equally important to ensure that the rainfall peaks are correctly located within the rainfall maps, especially if these maps are then used as input to hydrological models. In this paper, we describe a novel machine learning model that addresses both gaps, RA-U

_{c m p d}

, based on the popular U-Net model. The key novelty of RA-U

_{c m p d}

is its loss function, the compound loss, which optimizes both a pixel-wise bias metric (the MSE) and a spatial verification metric (a modified version of the Fractions Skill Score). Our results show how RA-U

_{c m p d}

improves ERA5 in almost all metrics by 3-28%—more than the other models we used for comparison which actually worsen the total rainfall bias of ERA5—at the cost of a slightly increased (3%) error on the magnitude of the peak. We analyse the behaviour of RA-U

_{c m p d}

by visualizing accumulated maps of four particularly wet tropical cyclones and by dividing our data according to the Saffir-Simpson scale and to whether they made landfall, and we perform an error analysis to understand under what conditions our model performs best.

用于分析热带气旋引发的洪水风险的水文模型通常输入ERA5再分析数据。然而，ERA5 降水量存在较大的系统偏差，尤其是在热带气旋等强降水事件中，这影响了其在此类情景中的实用性。迄今为止，对ERA5 降水量进行偏差修正的研究很少，而且没有一项研究是针对热带气旋引起的极端降雨的。此外，大多数现有的偏差调整工作都侧重于调整像素偏差指标，如平均平方误差（MSE）。然而，确保降雨峰值在降雨地图中的正确定位同样重要，尤其是当这些地图被用作水文模型的输入时。在本文中，我们介绍了一种新型机器学习模型 RA-Ucmpd，该模型基于流行的 U-Net 模型，可同时解决这两个问题。RA-Ucmpd 的主要创新点在于其损失函数--复合损失，它同时优化了像素偏差指标（MSE）和空间验证指标（分数技能得分的改进版）。我们的结果表明 RA-Ucmpd 在几乎所有指标上都比 ERA5 提高了 3-28%，超过了我们用于比较的其他模型，后者实际上恶化了 ERA5 的总降雨量偏差，但代价是峰值大小误差略有增加（3%）。我们分析了 RA-Ucmpd 的行为，方法是直观显示四个特别潮湿的热带气旋的累积图，并根据萨菲尔-辛普森尺度和是否登陆对数据进行划分，我们还进行了误差分析，以了解我们的模型在什么条件下表现最佳。

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引用次数: 0