Research can increasingly determine the contribution of climate change to extreme events such as droughts

风险评估是气候变化研究领域的核心课题之一,减缓和适应战略的理论需求推动下发展出许多定量评估方法,完成了大量的评估工作。然而,已有研究在气候变化的风险构成上从不同的角度去认识,且评估方法论在整体上缺乏对致险因子与承险体的集成分类。基于此,本文明晰气候变化风险构成,包括致险因子的危险性、承险体的暴露度与脆弱度及其相互关系,明晰了风险产生与变化逻辑。融合致险因子与承险体特征,将气候变化风险定量评估方法归纳为突发事件和渐变事件两类,并分别进行了理论阐述和案例剖析。最后,根据气候变化风险的研究现状和评估需求,从温升目标、脆弱性曲线、适应措施等方面提出未来展望。

Risk assessment is a core area of climate change research. Quantitative assessment methods have been developed particularly due to the needs for theory of mitigation and adaptation strategies, and have been applied to a great number of specific assessments. However, there have been different viewpoints of the risk composition of climate change, and overall, integrated classification by coupling risk causing factors and risk bearing bodies is lacking. This article illuminates the risk composition of climate change, including the danger of risk causing factors, the exposure and vulnerability of risk bearing bodies, and their interrelations. The emergence and change of risk were clarified. Based on the integrated analysis of risk causing factors and risk bearing bodies, this study divided the climate change risk quantitative assessment methods into sudden onset hazard risk and slow onset hazard risk assessment methods, then the theoretical elaboration and case analysis were conducted for the two types of risks respectively. Finally, according to the current status and needs, this article proposes the future development directions of climate change risk research, including risk assessment under different warming amplitude, vulnerability curve construction, and adaptation.

Droughts and hot extremes may lead to tremendous impacts on the ecosystem and different sectors of the society. A variety of studies have been conducted on the variability of the individual drought or hot extreme in China. However, the evaluation of compound droughts and hot extremes, which may induce even larger impacts than the individual drought or hot extreme, is still lacking. The aim of this study is to investigate changes in the frequency and spatial extent of compound droughts and hot extremes during summer in China using monthly precipitation and daily temperature data from 1953 to 2012. Results show that a high frequency of compound droughts and hot extremes mostly occur in the regions stretching from northeast to southwest of China. There is an overall increase in the frequency of co-occurrence of droughts and hot extremes across most parts of China with distinct regional patterns. In addition, an increasing trend in the areas covered by compound extremes has been observed, especially after the 1990s. At regional scales, the increase of the frequency and spatial extent of compound extremes has been shown to be most profound in North China (NC), South China (SC), and Southwest China (SWC), while the decrease of compound extremes was found in Central China (CC). These results show the variability of compound droughts and hot extremes and could provide useful insights into the mitigation efforts of extreme events in China.

. The Mediterranean (MED) Basin is a climate change hotspot that has seen drying and a pronounced increase in heatwaves over the last century. At the same time, it is experiencing increased heavy precipitation during wintertime cold spells. Understanding and quantifying the risks from compound events over the MED is paramount for present and future disaster risk reduction measures. Here, we apply a novel method to study compound events based on dynamical systems theory and analyse compound temperature and precipitation events over the MED from 1979 to 2018. The dynamical systems analysis quantifies the strength of the coupling between different atmospheric variables over the MED. Further, we consider compound warm–dry anomalies in summer and cold–wet anomalies in winter. Our results show that these warm–dry and cold–wet compound days are associated with large values of the temperature–precipitation coupling parameter of the dynamical systems analysis. This indicates that there is a strong interaction between temperature and precipitation during compound events. In winter, we find no significant trend in the coupling between temperature and precipitation. However in summer, we find a significant upward trend which is likely driven by a stronger coupling during warm and dry days. Thermodynamic processes associated with long-term MED warming can best explain the trend, which intensifies compound warm–dry events.\n

. Estimating the likelihood of compound climate extremes such as concurrent drought and heatwaves or compound precipitation and wind speed extremes is important for assessing climate risks. Typically, simulations from climate models are used to assess future risks, but it is largely unknown how well the current generation of models represents compound extremes. Here, we introduce a new metric that measures whether the tails of bivariate distributions show a similar dependence structure across different datasets. We analyse compound precipitation and wind extremes in reanalysis data and different high-resolution simulations for central Europe. A state-of-the-art reanalysis dataset (ERA5) is compared to simulations with a weather model (Weather Research and Forecasting – WRF) either driven by observation-based boundary conditions or a global circulation model (Community Earth System Model – CESM) under present-day and future conditions with strong greenhouse gas forcing (Representative Concentration Pathway 8.5 – RCP8.5).\nOver the historical period, the high-resolution WRF simulations capture precipitation and wind extremes as well as their response to orographic effects more realistically than ERA5. Thus, WRF simulations driven by observation-based boundary conditions are used as a benchmark for evaluating the dependence structure of wind and precipitation extremes.\nOverall, boundary conditions in WRF appear to be the key factor in explaining differences in the dependence behaviour between strong wind and heavy precipitation between simulations. In comparison, external forcings (RCP8.5) are of second order. Our approach offers new methodological tools to evaluate climate model simulations with respect to compound extremes.\n

. The interaction between storm surge and concurrent precipitation is poorly understood in many coastal regions. This paper investigates the potential compound effects from these two flooding drivers along the coast of China for the first time by using the most comprehensive records of storm surge and precipitation. Statistically significant dependence between flooding drivers exists at the majority of locations that are analysed, but the strength of the correlation varies spatially and temporally and depending on how extreme events are defined. In general, we find higher dependence at the south-eastern tide gauges (TGs) (latitude < 30∘ N) compared to the northern TGs. Seasonal variations in the dependence are also evident. Overall there are more sites with significant dependence in the tropical cyclone (TC) season, especially in the summer. Accounting for past sea level rise further increases the dependence between flooding drivers, and future sea level rise will hence likely lead to an increase in the frequency of compound events. We also find notable differences in the meteorological patterns associated with events where both drivers are extreme versus events where only one driver is extreme. Events with both extreme drivers at south-eastern TG sites are caused by low-pressure systems with similar characteristics across locations, including high precipitable water content (PWC) and strong winds that generate high storm surge. Based on historical disaster damages records of Hong Kong, events with both extreme drivers account for the vast majority of damages and casualties, compared to univariate flooding events, where only one flooding driver occurred. Given the large coastal population and low capacity of drainage systems in many Chinese urban coastal areas, these findings highlight the necessity to incorporate compound flooding and its potential changes in a warming climate into risk assessments, urban planning, and the design of coastal infrastructure and flood defences.

Wahl, Thomas; Meyers, Steven D.; Luther, Mark E. Univ S Florida, Coll Marine Sci, St Petersburg, FL 33701 USA. Wahl, Thomas; Bender, Jens Univ Siegen, Res Ctr Siegen, D-57076 Siegen, Germany. Jain, Shaleen Univ Maine, Climate Change Inst, Civil & Environm Engn, Orono, ME 04469 USA. Jain, Shaleen Univ Maine, Mitchell Ctr Sustainabil Solut, Orono, ME 04469 USA. Bender, Jens Univ Siegen, Res Inst Water & Environm, D-57076 Siegen, Germany.

Floods and debris flows pose a significant threat, especially when extreme rain falls over burned areas. This is an example of a compound event in which two concurrent or consecutive events lead to extreme societal impacts. Compound and cascading hazards are becoming increasingly important and have notable impacts on threatened communities across the world. Wildfire followed by an intense precipitation event can result in a large flood under which the combined impacts of hazard drivers are much more intense than those from individual drivers. Here, we first quantify the change in exposure of natural gas infrastructure to individual hazards, wildfire and floods in the future relative to past. We, then quantify the compound hazards as coincidence likelihood of intense rain over burned areas and analyze the spatial patterns across the State of California, USA. Our results show that not only the exposure of natural gas infrastructure to individual hazards would be higher, the likelihood of compound hazards is expected to increase substantially in a warming climate.

基于 1960—2018 年的逐日降水观测数据，采用日尺度旱涝急转指数（DWAAI）计算方法，以生态地理区为框架，识别并分析了西南地区旱涝急转事件的时空变化特征。结果表明：西南地区旱涝急转事件的发生次数在 1960—2010年有增加趋势，在 2011—2018 年快速减少；旱转涝事件多发生在春夏季（4~8 月），涝转旱事件则跨越了春、夏、秋季（5~11 月）；在云南高原常绿阔叶林、松林区（VA5），西双版纳山地季雨林、雨林区（VIIA3），闽粤桂低山平原常绿阔叶林、人工植被区（VIA2），旱涝急转事件主要发生在夏季，而在湘黔高原山地常绿阔叶林区（VA3）和四川盆地常绿阔叶林、人工植被区（VA4），旱涝急转事件主要发生在春季；旱涝急转事件发生次数的空间分布呈现东北多、西南少的格局；2000 年以来旱涝急转事件在滇中南亚高山谷地常绿阔叶林、松林区（VIA3）和闽粤桂低山平原常绿阔叶林、人工植被区（VIA2）发生次数减少，但有加重趋势，呈现极端化特征。

With the warming climate and enhancing human activities, the frequency and intensity of dry-wet abrupt alternation (DWAA) events have been increasing, largely affected on natural environment and social-economy development. Using observed daily precipitation from 1960 to 2018, this study analyzed the spatio-temporal variations of DWAA events in Southwest China by calculating Dry-Wet Abrupt Alternation Index (DWAAI) based on eco-geographical regions. The DWAA events in Southwest China exhibited an increasing trend before 2010 and decreased after 2011. The dry-to-wet events mainly concentrated in spring and summer (April to August). Meanwhile, the wet-to-dry events were primarily found in spring, summer and autumn (May to November). At seasonal scale, DWAA events mainly occurred in summer, distributed in the area of Yunnan Plateau evergreen broadleaved forest and pine forest region (VA5), Xishuangbanna mountains seasonal rainforest and rainforest region (VIIA3), and Fujian, Guangdong and Guangxi low mountain and plain evergreen broadleaved forest and cultivated vegetation region (VIA2). In the area of Hunan and Guizhou mountains evergreen broadleaved forest region (VA3), and Sichuan Basin evergreen broadleaved forest and cultivated vegetation region (VA4), the DWAA events were examined in spring. Spatially, majority of DWAA events existed in the northeast of Southwest China, and the less were found in the southwest. Although frequency of DWAA events declined since 2000, the intensity of DWAA was obviously enhanced, especially in Xishuangbanna mountains seasonal rainforest and rainforest region (VIIA3), and Fujian, Guangdong and Guangxi low mountain and plain evergreen broadleaved forest and cultivated vegetation region (VIA2).

In this paper, preliminary results are presented showing that the two record-setting extreme events during 2010 summer (i.e., the Russian heat wave–wildfires and Pakistan flood) were physically connected. It is found that the Russian heat wave was associated with the development of an extraordinarily strong and prolonged extratropical atmospheric blocking event in association with the excitation of a large-scale atmospheric Rossby wave train spanning western Russia, Kazakhstan, and the northwestern China–Tibetan Plateau region. The southward penetration of upper-level vorticity perturbations in the leading trough of the Rossby wave was instrumental in triggering anomalously heavy rain events over northern Pakistan and vicinity in mid- to late July. Also shown are evidences that the Russian heat wave was amplified by a positive feedback through changes in surface energy fluxes between the atmospheric blocking pattern and an underlying extensive land region with below-normal soil moisture. The Pakistan heavy rain events were amplified and sustained by strong anomalous southeasterly flow along the Himalayan foothills and abundant moisture transport from the Bay of Bengal in connection with the northward propagation of the monsoonal intraseasonal oscillation.

利用气象站观测资料和NCEP/NCAR再分析资料对河套气旋发展东移触发的北京2012年7月21日特大暴雨(下称"721"暴雨)天气过程进行了诊断分析, 结果表明: 河套气旋是北京"721"特大暴雨的主要影响系统, 内蒙中部较强的冷空气活动阻挡了河套气旋北上的常规路径, 迫使其东移直接影响河北、北京地区; 河套气旋在东移过程中, 由暖心正压气旋转变为斜压性气旋, 且强烈发展, 其水汽、热力、高低空急流耦合等条件随着河套气旋的东移明显好转, 是此次暴雨天气过程降水量自西向东不断增大的主要原因; 午后, 河套气旋东移暖锋触发不稳定能量释放, 在北京地区产生强对流系统, 形成中尺度对流辐合体后, 使得降水进一步加强, 是北京地区产生特大暴雨的主要原因; 东南气流中地形抬升作用对降水有增幅作用, 北京"721"特大暴雨是多种有利因素叠加所致。

The rainstorm process on 21 July 2012(hereafter ‘721’ process) in Beijing is analyzed produced by the Hetao cyclone shifting eastward. The results show that the Hetao cyclone moves eastward directly that leads to the ‘721’ process, because the path of Hetao cyclone shifting northward is blocked by the stronger cold air. The main reason that the precipitation increases from west to east is because of the increasing factors, for example, the vapor, heat and high-low level jet stream during the warm barotropic cyclone changes into baroclinic cyclone with the process of Hetao cyclone shifting eastward. Afternoon, the instability energy triggers and the strong convective system forms in Beijing, whenthe warm front moves eastward. The formation of mesoscale convective complex (MCC)thatmakes the precipitation strengthened further, which is the main reason of the heavy rainstormin Beijing. The topography acts as a stimulus to this precipitation and the ‘721’ process is formed under simultaneous multiple positive factors.

Compound events (CEs) are weather and climate events that result from multiple hazards or drivers with the potential to cause severe socio-economic impacts. Compared with isolated hazards, the multiple hazards/drivers associated with CEs can lead to higher economic losses and death tolls. Here, we provide the first analysis of multiple multivariate CEs potentially causing high-impact floods, droughts, and fires. Using observations and reanalysis data during 1980-2014, we analyse 27 hazard pairs and provide the first spatial estimates of their occurrences on the global scale. We identify hotspots of multivariate CEs including many socio-economically important regions such as North America, Russia and western Europe. We analyse the relative importance of different multivariate CEs in six continental regions to highlight CEs posing the highest risk. Our results provide initial guidance to assess the regional risk of CE events and an observationally-based dataset to aid evaluation of climate models for simulating multivariate CEs.

Various methods have been developed over the past five decades for dependence modeling of multivariate variables in hydrology and water resources, but there has been no overall review of techniques commonly used in the field. This paper, therefore, introduces several methods focusing on dependence structure modeling, including parametric distribution, entropy, copula, and nonparametric. Recent advances in modeling dependences mainly reside in nonlinear dependence modeling (including extreme dependence) with flexible marginal distributions, and in high-dimension dependence modeling via the vine copula construction with flexible dependence structures. Strengths and limitations of different methods and avenues for future research, such as dependence modeling in a changing climate, are discussed to aid water resource planners and managers in the selection and application of suitable techniques.

Traditional flood hazard analyses often rely on univariate probability distributions; however, in many coastal catchments, flooding is the result of complex hydrodynamic interactions between multiple drivers. For example, synoptic meteorological conditions can produce considerable rainfall-runoff, while also generating wind-driven elevated sea-levels. When these drivers interact in space and time, they can exacerbate flood impacts, a phenomenon known as compound flooding. In this paper, we build a Bayesian Network based on Gaussian copulas to generate the equivalent of 500 years of daily stochastic boundary conditions for a coastal watershed in Southeast Texas. In doing so, we overcome many of the limitations of conventional univariate approaches and are able to probabilistically represent compound floods caused by riverine and coastal interactions. We model the resulting water levels using a one-dimensional (1D) steady-state hydraulic model and find that flood stages in the catchment are strongly affected by backwater effects from tributary inflows and downstream water levels. By comparing our results against a bathtub modeling approach, we show that simplifying the multivariate dependence between flood drivers can lead to an underestimation of flood impacts, highlighting that accounting for multivariate dependence is critical for the accurate representation of flood risk in coastal catchments prone to compound events.

基于中国0.5°×0.5°逐日气温和降水格网数据,利用复杂网络分析方法,对2008年南方低温雨雪冰冻灾害综合致灾过程进行再认识,综合分析低温雨雪冰冻灾害在时空维度的网络特性。结果表明：2008年南方低温雨雪冰冻灾害是典型的多灾种叠加事件,低温与雨雪灾害叠加放大了致灾因子的危险性;基础设施设防水平低与春运高峰叠加增大了承灾体的脆弱性;低山丘陵区与人口聚集区叠加降低了孕灾环境的稳定性。低温冰冻雨雪灾害具有小世界特征和核心—边缘结构,具体表现为：在空间打击上具有集聚性,影响区域相对集中;在时间打击上具有连续性,间隔1天事件相对较少。在研究方法上,复杂网络是一种有效分析多灾种叠加的方法,可以进一步挖掘自然灾害的时空演化信息。

In recent years, some new areas of development have been proposed for natural disaster science. It is suggested that the discipline should try to attach more importance to recognizing disaster loss accumulation and amplification trends, re-evaluate the mechanisms of major natural disasters, and facilitate interdisciplinary research between natural disaster and complexity science. The 2008 Chinese ice storm struck the most populated and economically developed region of China, and direct economic losses exceeded $22.3 billion (indirect losses may have been even greater). Recognition of the formation mechanism of the 2008 Chinese ice storm will be very important for developing integrated disaster risk reduction strategies. This study employed daily temperature and precipitation data from a 0.5°×0.5° gridded dataset released by China's National Meteorological Information Center to evaluate the synthetic hazard process of the severe cold surge, ice-snow events, and corresponding frozen disasters in southern China in 2008. More specifically, we analyzed the spatial-temporal structure and complexity of the catastrophes by using bipartite networks. Results indicated that the large freezing rain and snow disaster was a typical multi-disaster overlaying event. The overlaying of freezing rain and snow amplified the risks of other hazards such as critical infrastructure failures. Moreover, the timing of the event, which occurred during the Chinese New Year, increased the vulnerability of people to exposures (i.e., they were more likely to be traveling). Low mountain-hilly terrain and high population density reduced the stability of the fostering environment. The freezing rain and snow catastrophes in 2008 showed the mathematical characteristics of small-world features. In terms of spatial data, the occurrence of hazards was clustered when the unprecedented ice struck the region; in terms of temporal data, the intervals between successive waves were too short for ice to melt or be broken, thus disaster losses were accumulated and amplified through the small-world features of the hazards. Networks of freezing rain and snow catastrophes in 2008 had a typical core-periphery structure. The spatial core nodes were Sichuan, Guizhou, Chongqing, Anhui, Hubei, Shaanxi, and Hunan (provincial units); the temporal core nodes were 1.13, 1.15, 1.17-1.22, and 1.25-2.4. Overall, these results highlight that complex network theory can be used advantageously in the analysis of the loss accumulation and amplification trends associated with multi-disaster events. Such techniques can also be used effectively to describe the spatial and temporal evolution of multi-disaster events and support the understanding of disaster dynamics.

干旱和热浪耦合是典型的多灾种事件,全球气候变暖增加了干旱和热浪耦合的风险。选取京津冀地区作为研究对象,以复杂网络理论为基础,构建干旱热浪时空耦合网络模型,拓展派系模型时空聚类方法,分析年代尺度上干旱和热浪时空聚类特征。结果表明：近55年京津冀地区干旱热浪耦合存在空间差异性,形成4个规律相异的时空耦合形态,即密集分布型（张家口—怀来—遵化,石家庄—邢台）、前期集中型（北部燕山地区）、后期集中型（太行山地区）、稀疏分布型（东部沿海区）。同时,干旱热浪空间耦合中心具有明显的迁移规律,以20世纪80年代为界,前期耦合中心分布偏北,位于北部燕山地区,后期则向南迁移,分布于南部太行山区。以时空数据为基础,提出面向非过程的多灾种时空网络构建方法,不仅是多灾种研究方法的探索,也是地理时空数据一体化研究的尝试,以期为多灾种时空耦合方法体系完善提供新的思路。

Concurrent occurrence of heat waves and droughts is a typical multi-hazard event. Global warming is leading to an increased risk of concurrent and compound extremes. In this study, we evaluated the changes in the pattern of concurrent drought and heat wave events in the Beijing-Tianjin-Hebei metropolitan region, China from 1960 to 2014. In addition, we used spatial-temporal data as a breakthrough point to examine the spatiotemporal clustering in concurrent heat wave and drought events by using bipartite networks. According to our results, based on the variations in heat waves and droughts trends, three distinct phases were identified: the first phase (1960s-1970s), a relatively wet phase when heat waves continually decreased; the second phase (1980s-1990s), when the climate conditions changed from a drought like period to a pluvial period, and the heat waves increased; the third phase (1999-2014), when little precipitation was observed and the heat waves showed a decreasing trend. The correlation between heat waves and droughts was found to increase substantially between 1960 and 2014. Moreover, the concurrence of heat waves and droughts showed a significant pattern of spatiotemporal variation; before 1984, the concurrence of heat waves and droughts increased in the surrounding regions and the north of Yanshan Mountains; after 1984, high concurrence between heat waves and droughts was mainly observed in the south of Taihang Mountains. The research methodology used in this study can not only serve as the basis for research on multi-hazards, but also contribute to geographic spatiotemporal data modeling. Most importantly, the method based on the spatiotemporal network for multi-hazards makes up for the deficiencies of traditional methods in terms of utilization of spatiotemporal data.

This paper reviews the historical and potential future trends of extratropical cyclones (ECs) along the United States (US) East Coast and western Atlantic, as well as potential changes in coastal flooding, heavy precipitation, and damaging winds. Most models project a steady decrease in the number of ECs for the US East Coast and western Atlantic region by the middle to later twenty-first century, while there is an increase in more intense (<980 hPa) cyclones and heavy precipitation; however, there is also been large interdecadal and interannual variability. Potential biases may exist in the models because of difficulty capturing: (a) the Atlantic storm track sensitivity to the Gulf Stream SST gradient, (b) latent heating within these storms, and (c) dynamical interactions at jet level. More work is needed to determine future changes in hybrid storms (e.g., Sandy 2012) and diagnostics to better understand the future cyclone changes in the models.© The Author(s) 2015.

Phenomena such as cyclones, fronts and thunderstorms can cause extreme weather in various regions throughout the world. Although these phenomena have been examined in numerous studies, they have not all been systematically examined in combination with each other, including in relation to extreme precipitation and extreme winds throughout the world. Consequently, the combined influence of these phenomena represents a substantial gap in the current understanding of the causes of extreme weather events. Here we present a systematic analysis of cyclones, fronts and thunderstorms in combination with each other, as represented by seven different types of storm combinations. Our results highlight the storm combinations that most frequently cause extreme weather in various regions of the world. The highest risk of extreme precipitation and extreme wind speeds is found to be associated with a triple storm type characterized by concurrent cyclone, front and thunderstorm occurrences. Our findings reveal new insight on the relationships between cyclones, fronts and thunderstorms and clearly demonstrate the importance of concurrent phenomena in causing extreme weather.

Atmospheric rivers-long, narrow filaments of large integrated water vapour transport-are associated with weather and water extremes, such as precipitation extremes and flooding in western North America and northern Europe. Here we apply a global detection algorithm for atmospheric rivers to reanalysis data during 1997-2014 to investigate the impact of atmospheric rivers on wind extremes as well as precipitation extremes. We find that atmospheric rivers are associated with up to half of the extreme events in the top 2% of the precipitation and wind distribution, across most mid-latitude regions globally. Landfalling atmospheric rivers are associated with about 40-75% of extreme wind and precipitation events over 40% of the world's coastlines. Atmospheric rivers are associated with a doubling or more of the typical wind speed compared to all storm conditions, and a 50-100% increase in the wind and precipitation values for extreme events. We also find that the majority of extreme wind events catalogued between 1997 and 2013 over Europe with billion US dollar losses were associated with atmospheric rivers. We conclude that landfalling atmospheric rivers can represent a significant hazard around the globe, because of their association with not only extreme precipitation, but also extreme winds.

The western Pacific subtropical high (WPSH) is regarded as the key circulation system that dominates the summer heat waves over eastern China, but whether the WPSH-summer heat wave connection changes with time remains unknown. In this study, decadal variations in the WPSH-heat wave connection were examined for the period 1959-2016 using daily maximum temperature data from 654 observational stations across China and global reanalysis datasets. The results show that the correlation coefficient between the WPSH intensity (WPSHI) and the number of heat-wave days (NHD) was 0.65 (>99% confidence level) during positive phases of the Pacific decadal oscillation (PDO), whereas that during negative phases of the PDO was only 0.12 (<80% confidence level). The remarkable difference in correlations is due to the more westward extension of a stronger WPSH in El Nino decaying summers during the positive phases of PDO. The stronger Indian Ocean warming in El Nino decaying-year summers for PDO positive phases in comparison to PDO negative phases is associated with enhanced convection and heating, which further drive a stronger anticyclone over the northwestern Pacific, leading to a stronger and more westward-extending WPSH, which is favorable for more heat waves over eastern China.

Droughts and heatwaves cause agricultural loss, forest mortality, and drinking water scarcity, especially when they occur simultaneously as combined events. Their predicted increase in recurrence and intensity poses serious threats to future food security. Still today, the knowledge of how droughts and heatwaves start and evolve remains limited, and so does our understanding of how climate change may affect them. Droughts and heatwaves have been suggested to intensify and propagate via land-atmosphere feedbacks. However, a global capacity to observe these processes is still lacking, and climate and forecast models are immature when it comes to representing the influences of land on temperature and rainfall. Key open questions remain in our goal to uncover the real importance of these feedbacks: What is the impact of the extreme meteorological conditions on ecosystem evaporation? How do these anomalies regulate the atmospheric boundary layer state (event self-intensification) and contribute to the inflow of heat and moisture to other regions (event self-propagation)? Can this knowledge on the role of land feedbacks, when available, be exploited to develop geo-engineering mitigation strategies that prevent these events from aggravating during their early stages? The goal of our perspective is not to present a convincing answer to these questions, but to assess the scientific progress to date, while highlighting new and innovative avenues to keep advancing our understanding in the future.© 2018 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of The New York Academy of Sciences.

Dependence between extreme rainfall and storm surge can have significant implications for coastal floods, which are often caused by joint occurrence of these flood drivers (through pluvial or fluvial processes). The effect of multiple drivers leading to a compound flood event poses higher risk than those caused by a single flood-driving process. There is strong evidence that compound floods caused by joint occurrence of extreme storm surge and heavy rainfall are related to meteorological forcing (e.g. large scale pressure systems and wind) and climate phenomena (e.g. the El Niño Southern Oscillation or ENSO). Therefore, understanding how climate phenomena affect the co-occurrence of coastal flood drivers is an important step towards understanding future coastal flood risk under climate change. Here we examine the impact of one of the most important climate phenomena—ENSO—on dependence between storm surge and rainfall in Australia, using both observed surge and modelled surge from a linked ocean-climate model—the Regional Ocean Modeling System. Our results show that ENSO has a significant impact on the dependence between extreme rainfall and storm surge, thus flood risk resulted from these drivers. The overall dependence is largely driven by La Niña in Australia, with increased dependence observed during La Niña along most of the Australian coastline. However, there can be increased dependence during El Niño in some locations. The results demonstrate dependence is contributed by unequally-weighted mechanisms due to the interaction between climate phenomena and local features, indicating the need for greater understanding of composition of compound flood risk. Where climate phenomena are anticipated to change into the future, it is possible to use integrated process-driven models to establish a better understanding of whether extremes are more likely to co-occur and exacerbate compound flood risk.

Sea level rise (SLR), a well-documented and urgent aspect of anthropogenic global warming, threatens population and assets located in low-lying coastal regions all around the world. Common flood hazard assessment practices typically account for one driver at a time (e.g., either fluvial flooding only or ocean flooding only), whereas coastal cities vulnerable to SLR are at risk for flooding from multiple drivers (e.g., extreme coastal high tide, storm surge, and river flow). Here, we propose a bivariate flood hazard assessment approach that accounts for compound flooding from river flow and coastal water level, and we show that a univariate approach may not appropriately characterize the flood hazard if there are compounding effects. Using copulas and bivariate dependence analysis, we also quantify the increases in failure probabilities for 2030 and 2050 caused by SLR under representative concentration pathways 4.5 and 8.5. Additionally, the increase in failure probability is shown to be strongly affected by compounding effects. The proposed failure probability method offers an innovative tool for assessing compounding flood hazards in a warming climate.

基于Gumbel-Hougaard copula、Kendall和生存Kendall函数对比分析波高和周期联合分布的4种重现水平。以位于北卡罗来纳州Duck的美国陆军工程师团FRF (Field Research Facility)实验场观测的波高与周期样本为例, 计算二者联合分布的&#x0201c;或&#x0201d;重现期、&#x0201c;且&#x0201d;重现期、Kendall重现期和生存Kendall重现期及其联合设计值。主要结论如下: 对比设定重现期, 相对于&#x0201c;或&#x0201d;联合重现期, Kendall重现期可更准确地反映波高周期联合分布的风险率; 相对于&#x0201c;且&#x0201d;联合重现期, 生存Kendall重现期可更准确地反映波高周期同时超值情况下的风险率。按目前有关规范设计要求的单变量波高设计值基本达到设计标准, 按两变量&#x0201c;或&#x0201d;重现期和波高周期两变量同频率设计值推算的设计值偏高, 以最大可能概率推算的两变量的Kendall重现期和生存Kendall重现期设计值可为海岸海洋工程安全与风险管理提供新的选择。

. Compound events (CEs) are multivariate extreme events in which the individual contributing variables may not be extreme themselves, but their joint – dependent – occurrence causes an extreme impact. Conventional univariate statistical analysis cannot give accurate information regarding the multivariate nature of these events. We develop a conceptual model, implemented via pair-copula constructions, which allows for the quantification of the risk associated with compound events in present-day and future climate, as well as the uncertainty estimates around such risk. The model includes predictors, which could represent for instance meteorological processes that provide insight into both the involved physical mechanisms and the temporal variability of compound events. Moreover, this model enables multivariate statistical downscaling of compound events. Downscaling is required to extend the compound events' risk assessment to the past or future climate, where climate models either do not simulate realistic values of the local variables driving the events or do not simulate them at all. Based on the developed model, we study compound floods, i.e. joint storm surge and high river runoff, in Ravenna (Italy). To explicitly quantify the risk, we define the impact of compound floods as a function of sea and river levels. We use meteorological predictors to extend the analysis to the past, and get a more robust risk analysis. We quantify the uncertainties of the risk analysis, observing that they are very large due to the shortness of the available data, though this may also be the case in other studies where they have not been estimated. Ignoring the dependence between sea and river levels would result in an underestimation of risk; in particular, the expected return period of the highest compound flood observed increases from about 20 to 32 years when switching from the dependent to the independent case.\n

Multivariate hydrologic design under stationary conditions is traditionally performed through the use of the design criterion of the return period, which is theoretically equal to the average inter-arrival time of flood events divided by the exceedance probability of the design flood event. Under nonstationary conditions, the exceedance probability of a given multivariate flood event varies over time. This suggests that the traditional return-period concept cannot apply to engineering practice under nonstationary conditions, since by such a definition, a given multivariate flood event would correspond to a time-varying return period. In this paper, average annual reliability (AAR) was employed as the criterion for multivariate design rather than the return period to ensure that a given multivariate flood event corresponded to a unique design level under nonstationary conditions. The multivariate hydrologic design conditioned on the given AAR was estimated from the nonstationary multivariate flood distribution constructed by a dynamic C-vine copula, allowing for time-varying marginal distributions and a time-varying dependence structure. Both the most-likely design event and confidence interval for the multivariate hydrologic design conditioned on the given AAR were identified to provide supporting information for designers. The multivariate flood series from the Xijiang River, China, were chosen as a case study. The results indicated that both the marginal distributions and dependence structure of the multivariate flood series were nonstationary due to the driving forces of urbanization and reservoir regulation. The nonstationarities of both the marginal distributions and dependence structure were found to affect the outcome of the multivariate hydrologic design.

. In low-lying coastal regions, flooding arises from oceanographic (storm\nsurges plus tides and/or waves), fluvial (increased river discharge), and/or\npluvial (direct surface run-off) sources. The adverse consequences of a flood\ncan be disproportionately large when these different sources occur\nconcurrently or in close succession, a phenomenon that is known as\n“compound flooding”. In this paper, we assess the potential for compound\nflooding arising from the joint occurrence of high storm surge and high\nriver discharge around the coast of the UK. We hypothesise that there will be\nspatial variation in compound flood frequency, with some coastal regions\nexperiencing a greater dependency between the two flooding sources than\nothers. We map the dependence between high skew surges and high river\ndischarge, considering 326 river stations linked to 33 tide gauge sites. We\nfind that the joint occurrence of high skew surges and high river discharge\noccurs more frequently during the study period (15–50 years) at sites on the\nsouth-western and western coasts of the UK (between three and six joint events per\ndecade) compared to sites along the eastern coast (between zero and one joint\nevents per decade). Second, we investigate the meteorological conditions\nthat drive compound and non-compound events across the UK. We show, for the\nfirst time, that spatial variability in the dependence and number of joint\noccurrences of high skew surges and high river discharge is driven by\nmeteorological differences in storm characteristics. On the western coast of\nthe UK, the storms that generate high skew surges and high river discharge\nare typically similar in characteristics and track across the UK on\ncomparable pathways. In contrast, on the eastern coast, the storms that\ntypically generate high skew surges are mostly distinct from the types of\nstorms that tend to generate high river discharge. Third, we briefly examine\nhow the phase and strength of dependence between high skew surge and high\nriver discharge is influenced by the characteristics (i.e. flashiness, size,\nand elevation gradient) of the corresponding river catchments. We find that high\nskew surges tend to occur more frequently with high river discharge at\ncatchments with a lower base flow index, smaller catchment area, and steeper\nelevation gradient. In catchments with a high base flow index, large\ncatchment area, and shallow elevation gradient, the peak river flow tends to\noccur several days after the high skew surge. The previous lack of\nconsideration of compound flooding means that flood risk has likely been\nunderestimated around UK coasts, particularly along the south-western and western\ncoasts. It is crucial that this be addressed in future assessments of flood\nrisk and flood management approaches.\n

In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.