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High temperatures and droughts are two natural disasters that cause forest fires. During climate change, the frequent occurrence of high temperatures, droughts, and their coupled effects significantly increase the forest fire risk. To reveal the seasonal and spatial differences in the coupled effects of high temperatures and droughts on forest fires, this study used the Copula method and proposed the compound extremely high-temperature and drought event index ( CTDI ). The results indicated that the study area was subject to frequent forest fires in spring (71.56%), and the burned areas were mainly located in forests (40.83%) and the transition zone between farmland and forests (36.91%). The probability of forest fires in summer increased with high temperatures and drought intensity, with high temperatures playing a dominant role. The highest forest fire hazard occurred in summer (>0.98). The probability of a forest fire occurring under extreme meteorological conditions in summer and fall was more than twice as high as that in the same zone under non-extreme conditions. Droughts play a significant role in the occurrence and spread of forest fires during fall. These results can provide decision-making support for forest fire warnings and fire fighting in the Northeast China forest zone. [ABSTRACT FROM AUTHOR]

Extreme heat events over both lands and oceans have increased in frequency and intensity, and exerted profound impacts on human and natural systems. More impactful is their concurrence, leading to larger losses in health, food, economy, and ecosystem, but receiving far less attention. Understanding the mechanism for such marine–terrestrial compound heatwaves is a prerequisite to prediction and disaster prevention. Based on air particle trajectory analysis, we identified 87 compound heatwaves in China and adjacent oceans in summers of 1982–2021, with the connection between marine and terrestrial heatwaves particularly prominent between the oceans to Northeast Philippines and the lands in South/Southeast China. Through composite and case analysis, it is found that the connection is established by simultaneous governance of (i) the western Pacific subtropical high (WPSH), (ii) a dipole circulation pattern constituted by the WPSH and weak tropical cyclones (TCs), or (iii) strong and closer-to-coast TCs, each of which causes anomalously strong descending motion, increased incoming solar radiation, and strengthened adiabatic heating on lands. The marine heatwaves act to supply more moisture through enhanced evaporation, and/or intensify TCs that pass the region. The air particle tracking shows that these moister air masses are then advected by the WPSH and/or TCs to South/Southeast China, converting the adiabatic heating-caused dry heatwaves there into humid ones and thus adding to the heat stress. These diagnoses provide new insight into the mechanistic understanding and forecast precursors for terrestrial heatwaves, through the lens of compound events. [ABSTRACT FROM AUTHOR]

Quantifying flood risk depends on accurate probability estimation, which is challenging due to non‐stationarity and the combined effects of multiple factors in a changing environment. The threat of compound flood risks may spread from coastal areas to inland basins, which have received less attention. In this study, a framework based on time‐varying copulas was introduced for the treatment of compound flood risk and bivariate design in non‐stationary environments. Archimedean copulas were developed to diagnose the non‐stationary trends of flood risk. Return periods, average annual reliabilities, and bivariate designs were estimated. Model uncertainty was analyzed by comparing the results for stationary and non‐stationary conditions. The case study investigated the extreme rainfall and water level series from the Qinhuai River Basin and the Yangtze River in China. The results showed that marginal distributions and correlations are non‐stationary in all bivariate combinations. Ignoring composite effects may lead to inappropriate quantification of flood risk. Excluding non‐stationarity may lead to risk over or underestimation. It showed the limitations of the 1‐day scale and quantified the uncertainty of non‐stationary models. This study provided a flood risk assessment framework in a changing environment and a risk‐based design technique, which is essential for climate change adaptation and water management. [ABSTRACT FROM AUTHOR]

Abstract A semiparametric copula joint framework was proposed to model wind gust speed (WGS) and maximum temperature (MT) in Canada, using Gaussian kernel density estimation (GKDE) with parametric copulas. Their joint probability estimates allow for a better understanding of the risk of power blackouts and the demand for air conditioning in the community. The bivariate framework used two extreme sample groups to define extreme pairs at different time lags, i.e., 0 to ± 3 days, annual maximum WGS (AMWGS) and corresponding MT and annual highest MT (AHMT) and corresponding WGS. A thorough model performance comparison indicated that GKDE outperformed the parametric models in defining the marginal distribution of selected univariate series. Significant positive correlations were observed among extreme pairs, except for Calgary and Halifax stations, with inconsistent correlation variations based on selected cities and lag time. Various parametric 2-D copulas were selected to model the dependence structure of bivariate pairs at different time lags for selected stations. AMWGS or AHMT events, when considered independently, would be stressful for all stations due to high estimated quantiles with low univariate RPs. The bivariate events exhibited lower AND-joint RPs with moderate to high design quantiles, indicating a higher risk of power blackouts and heightened air-conditioning demands, which varied inconsistently with time lags across the station. The bivariate AMWGS and corresponding MT events would be stressful in Regina, Quebec City, Ottawa, and Edmonton, while AHMT and corresponding WGS events in Toronto, Regina, and Montreal. Conversely, Vancouver poses a lower risk of joint action of pairs AHMT and corresponding WGS events. These hazard statistics can help in better planning for community well-being during extreme weather.

Global climate change increasingly impacts agroecosystems, particularly through high-temperature–drought and low-temperature–drought compound events. This study uses ground meteorological and remote sensing data and employs geostatistics, random forest models, and copula methods to analyze the spatial and temporal distribution of these events and their impact on winter wheat in the Huang-Huai-Hai Plain from 1982 to 2020. High-temperature–drought events increased in frequency and expanded from north to south, with about 40% of observation stations recording such events from 2001 to 2020. In contrast, low-temperature–drought events decreased in frequency, affecting up to 80% of stations, but with lower frequency than high-temperature–drought events. Sensitivity analyses show winter wheat is most responsive to maximum and minimum temperature changes, with significant correlations to drought and temperature extremes. Copula analysis indicates temperature extremes and drought severity are crucial in determining compound event probability and return periods. High-temperature–drought events are likely under high temperatures and mild drought, while low-temperature–drought events are more common under low temperatures and mild drought. These findings highlight the need for effective agricultural adaptation strategies to mitigate future climate change impacts. [ABSTRACT FROM AUTHOR]

Taklamakan Desert (TD) has been characterized by numerous heatwaves and dust storms, leading to negative effects on societies and ecosystems at regional and global scales. However, the association between heatwaves and dust storms is poorly known. In this study, we describe the association between heatwaves and dust events and propose a mechanism for such compound events in the TD. The results show that, from 1993 to 2022, the frequency and intensity of heatwaves in the TD have increased at a rate of 0.21 days year−1 and 0.02°C year−1, respectively. More than 40% of heatwaves existed with dust events, which significantly lagged behind heatwaves. Mechanically, the higher the air temperature, the hotter and drier the soil, leading to more dust emissions in the TD. In high-occurrence heatwave years, a large-scale wave train of "cyclone-anticyclone-cyclone" in the northwest-southeast direction was found, with the anticyclone of which hovered over the TD region. The anomalous anticyclones favored the formation and maintenance of heatwaves, and subsequent anomalous cyclones in the wave train triggered strong dust events followed by heatwaves. With climate warming, the compound events of heatwave and dust storm are becoming bigger hazards threatening the socioeconomic and ecological security in the TD, the profound study of which is critical to understanding regional extreme responses. [ABSTRACT FROM AUTHOR]

Temperature extremes exert a significant influence on terrestrial ecosystems, but the precise levels at which these extremes trigger adverse shifts in vegetation productivity have remained elusive. In this study, we have derived two critical thresholds, using standard deviations (SDs) of growing‐season temperature and satellite‐based vegetation productivity as key indicators. Our findings reveal that, on average, vegetation productivity experiences rapid suppression when confronted with temperature anomalies exceeding 1.45 SD above the mean temperature during 2001–2018. Furthermore, at temperatures exceeding 2.98 SD above the mean, we observe the maximum level of suppression, particularly in response to the most extreme high‐temperature events. When Earth System Models are driven by a future medium emission scenario, they project that mean temperatures will routinely surpass both of these critical thresholds by approximately the years 2050 and 2070, respectively. However, it is important to note that the timing of these threshold crossings exhibits spatial variation and will appear much earlier in tropical regions. Our finding highlights that restricting global warming to just 1.5°C can increase safe areas for vegetation growth by 13% compared to allowing warming to reach 2°C above preindustrial levels. This mitigation strategy helps avoid exposure to detrimental extreme temperatures that breach these thresholds. Our study underscores the pivotal role of climate mitigation policies in fostering the sustainable development of terrestrial ecosystems in a warming world. [ABSTRACT FROM AUTHOR]

The compound drought‐extreme precipitation event (CDEP) is one of the most impactful successive compound events that shift from drought to extreme precipitation in the same location within a short period. Due to its dual characteristics of drought and flood, CDEP tends to be more destructive than the impact of individual drought or flood. Yet few studies have analyzed the likelihood of CDEP at different time intervals and their potential variations under global warming. In this study, we assessed the coincidence rate between droughts and extreme precipitation events at 1‐month (CDEP‐1), 2‐month (CDEP‐2), and 3‐month (CDEP‐3) intervals, as well as their potential changes in a 1.5 and 2°C warming world (under both SSP2‐4.5 and SSP5‐8.5 scenarios). Our results suggest that global droughts and extreme precipitation events have coincided more frequently at 1‐month interval than at 2‐ and 3‐month intervals during the period 1985–2014. The global average coincidence rates of CDEP‐1, CDEP‐2, and CDEP‐3 are 24%, 10%, and 7%, respectively. Notably, the coincidence rate of CDEP‐1 exceeded 40% in Eastern Asia, north‐eastern North America, and India, indicating that more than 40% of droughts have been followed by extreme precipitation events in the next month after drought termination. Under both SSP2‐4.5 and SSP5‐8.5 scenarios, climate warming will increase the coincidence rate of CDEP‐1, CDEP‐2, and CDEP‐3, especially will lead to higher values in the coincidence rate of CDEP‐1. This study contributes to a better understanding of the patterns of CDEP and helps to develop more targeted risk management strategies. Plain Language Summary: The compound drought‐extreme precipitation event (CDEP), a phenomenon in which droughts and extreme precipitation events occur consecutively, is highly destructive but has been understudied. We examined the coincidence rate of droughts and extreme precipitation events at different time intervals and their changes under global warming. Our findings show that CDEP is more likely to occur within 1 month (CDEP‐1), with a global average coincidence rate of 24%. The coincidence rate of CDEP‐1 exceeded 40% in Eastern Asia, north‐eastern North America, and India. Climate warming will increase the likelihood of CDEP, particularly CDEP‐1, with the highest increments projected in Central Africa and Southern Asia. This study enhances our understanding of CDEP patterns and supports the development of targeted risk management strategies. Key Points: We evaluated the coincidence rate between drought and extreme precipitation at 2‐(CDEP‐1), 2‐(CDEP‐2), and 3‐month (CDEP‐3) intervals1985–2014, global droughts and extreme precipitation events coincided more frequently at 1‐month intervals than at other intervalsGlobal warming will increase the coincidence rate of CDEP‐1, CDEP‐2, and CDEP‐3, especially will lead to higher values for CDEP‐1 [ABSTRACT FROM AUTHOR]

Extreme drought and flood events, as well as their combined events, pose significant challenges to global sustainable socio-economic development and ecological health. However, the impact of dry–wet combination events (DWCEs) on vegetation vulnerability remains to be investigated. The Loess Plateau (LP) was selected as the study area to explore the response time of vegetation to precipitation index changes by optimal correlation coefficient; then, the impact of different DWCEs on vegetation vulnerability under moderate and severe scenarios was analyzed; finally, a vegetation loss probability model was constructed based on the copula function and Bayesian framework, to quantify the vegetation loss probability under DWCEs stress. The results indicate that: (1) normalized difference vegetation index (NDVI) shows an upward trend in spring, summer, and autumn, with the proportion of areas are 90.5%, 86.2%, and 95.4%, respectively, and show an insignificant trend in winter; (2) the response time of vegetation to precipitation index changes tends to be one or two seasons; (3) moderate scenarios have more influence than severe scenarios, dry-to-wet events (DWEs), wet-to-dry events (WDE) and continuous dry events (CDE) in spring-summer have a significant impact on summer vegetation of Ningxia and Shanxi, and WDE and CDE have a higher impact on autumn vegetation. (4) in terms of the probability of vegetation loss, DWE, and CDE cause higher losses to summer vegetation, while WDE and CDE cause higher losses to autumn vegetation. This study quantifies the impact of adjacent seasonal DWCE stress on future vegetation vulnerability. [ABSTRACT FROM AUTHOR]

Heat stress and flood impacts have been extensively studied separately because of their significant societal and economic impacts, albeit apart from each other. Here we show that heat stress can trigger floods across large areas of North and South America, southern Africa, Asia and eastern Australia. We also show that the compounding of heat stress and floods is projected to worsen under climate change. This effect is magnified as we move from the Shared Socioeconomic Pathways (SSPs) 1–2.6 to 5–8.5. Moreover, in the future, the compounding between heat stress and floods is projected to extend to Europe and Russia, two areas where it has not been identified as relevant in the past. Moreover, by intersecting our results with future projections of the population of urban agglomerations, we find that heat stress/flood compound can pose a serious risk to a large portion of the world population. These results highlight the need towards improved preparation and mitigation measures that account for the compound nature of heat stress and flooding, and how the compounding is expected to be exacerbated because of climate change. [ABSTRACT FROM AUTHOR]

The abrupt alternation between hot and wet extremes can lead to more severe societal impacts than isolated extremes. However, despite an understanding of hot and wet extremes separately, their temporally compounding characteristics are not well examined yet. Our study presents a comprehensive assessment of successive heat-pluvial and pluvial-heat events globally. We find that these successive extremes within a week occur every 6–7 years on average within warm seasons during 1956–2015, about 15% more often than would be expected by chance, and that they have a significant increase in frequency of about 22% per decade due to warming. We further investigate the role of vapor pressure deficit (VPD) and find that heat-pluvial (pluvial-heat) events are linked to negative (positive) VPD anomalies. Our results are statistically significant based on moving-blocks bootstrap resampling and field significance tests, highlighting these methods' importance in robustly identifying compound events under autocorrelation and multiple-testing conditions.

Terrestrial vegetation plays a vital role in global carbon recycling, but it is also affected by compound events (CEs); however, little is known about the impacts of these CEs on vegetation in terms of their occurrence and magnitude. Using meteorological observations and vegetation indices (leaf area index (LAI), gross primary productivity (GPP), and net primary productivity (NPP)) from 1981 to 2020, we explored the occurrence of 13 CEs types and identified the dominant CEs types across different eco-geographical regions of China, and quantified the response of various vegetation types to dominant CEs. We found that CEs of extreme hot-dry, extreme hot-dry-high fire weather, dry-high fire weather, and high fire weather-strong wind were the dominant types of compound events during the growing season in China, and their hazards increased at a rate of >0.1HI/10a during 1981–2020. We further detected that more than 60% of the total vegetation areas showed a strong negative correlation with compound extreme hot-dry-high fire weather-strong wind events, which was relatively higher than compound extreme hot-dry events. The response of vegetation to compound events varied at the national scale, which was related to the vegetation type, dominant compound event type, and local natural conditions. This study highlights the benefits of a multivariate perspective on compound events and reveals the regional differences in the response of vegetation to compound events, which can provide initial guidance to assess the regional compound event risk of vegetation against the background of carbon neutrality by 2060.

Angola is exceptionally vulnerable to climate change, and sectors such as health, agricultural, water resources and ecosystems may endure severe impacts. Here, an extensive analysis of the signal of climate change on temperature, precipitation, extremes and compound events, for the end of the 21st century, is presented. The analysis is based on a CORDEX-Africa multi-model ensemble at 0.44° resolution built with 19 individual simulations, which allows a robust study of climate change future projections and depict model's uncertainty. For the RCP8.5, the end of the century future warming can reach maxima values ∼ 7 °C for maximum temperature in south-eastern Angola, and 6 °C for minimum temperature. The extreme temperatures (90th percentile) is projected to rise more than 7 °C in southern areas. In general, projections display a rainfall reduction in the drier seasons and a rise in the wet seasons, leading to sharper annual cycles; it is also projected a growth on extreme precipitation (95th percentile), as much as plus ∼ 50 % in some coastal regions. Angola is projected to endure in the future more frequent and longer heatwaves and droughts. In agreement with the RCP8.5, up to 10 heatwaves and more 4 moderate droughts will occur, respectively in coastal and interior areas. Finally, the number of days when a compound of heatwave and moderate drought occurs is projected to growth immensely, around +30 % for many regions, which corresponds to multiply by 10 these events in the future. For the RCP4.5, changes are projected to be smaller but significant in what regards especially extremes and compound events. The magnitude of the projected changes for vulnerable countries as Angola constitute an urgent call for global mitigation and national to regional adaptation strategies, and ultimately to a constant effort of updating and deepen the quality of climate information produced.

Abstract Quantifying flood risk depends on accurate probability estimation, which is challenging due to non‐stationarity and the combined effects of multiple factors in a changing environment. The threat of compound flood risks may spread from coastal areas to inland basins, which have received less attention. In this study, a framework based on time‐varying copulas was introduced for the treatment of compound flood risk and bivariate design in non‐stationary environments. Archimedean copulas were developed to diagnose the non‐stationary trends of flood risk. Return periods, average annual reliabilities, and bivariate designs were estimated. Model uncertainty was analyzed by comparing the results for stationary and non‐stationary conditions. The case study investigated the extreme rainfall and water level series from the Qinhuai River Basin and the Yangtze River in China. The results showed that marginal distributions and correlations are non‐stationary in all bivariate combinations. Ignoring composite effects may lead to inappropriate quantification of flood risk. Excluding non‐stationarity may lead to risk over or underestimation. It showed the limitations of the 1‐day scale and quantified the uncertainty of non‐stationary models. This study provided a flood risk assessment framework in a changing environment and a risk‐based design technique, which is essential for climate change adaptation and water management.

Increasing wildfire and declining snowpacks in mountain regions threaten water availability. We combine satellite-based fire detections with snow seasonality classifications to examine fire activity in California's seasonal and ephemeral snow zones. We find a nearly tenfold increase in fire activity during 2020–2021 versus 2001–2019. Accumulation season broadband snow albedo declined 25%–71% at two burned sites (2021 and 2022) according to in-situ data relative to un-burned conditions, with greater declines associated with increased burn severity. By enhancing snowpack susceptibility to melt, both decreased snow albedo and canopy drove midwinter melt during a multi-week dry spell in 2022. Despite similar meteorological conditions in December–February 2013 and 2022–linked to persistent high pressure weather regimes–minimal melt occurred in 2013. Post-fire snowpack differences are confirmed with satellite measurements. With growing geographical overlap between wildfire and snow, our findings suggest California's snowpack is increasingly vulnerable to the compounding effects of dry spells and wildfire.

Introduction: Crops are vulnerable to precipitation and heat extremes during late spring through summer. Methods: We analyzed for a north-central U.S. region short-term drought and agricultural heat stress during April-May-June-July. We used the 4-km Parameter Elevation Regression on Independent Slopes Model (PRISM) for observations, aggregated to a 25-km grid, and two 25-km Regional Climate Model version 4 (RegCM4) simulns used either GFDL- or MPI-GCM boundary conditions. We chose 1981-2000 as our contemporary time period, and 2041-2060 as our scenario time period, which used the Representative Concentration Pathway 8.5 emissions scenario. We used object-oriented analysis to identify events of interest in observations and simulations by identifying objects in a space-time domain that meet specified criteria, such as exceeding a heat-stress temperature threshold. The event diagnosis allowed analysis of compound events, occurring when temperature and drought objects overlap. Results: Identified objects yielded events that can undermine agricultural productivity and which are thus relevant to decision makers, making them building blocks for possible climate storylines. The observations and simulations showed similar spatial distributions of event frequencies across the analysis region. However, the simulations attained this distribution by having fewer events that tend to cover larger areas compared to observed events, suggesting that the effective resolution of the simulations was coarser than their 25-km grids. Short-term drought frequency increased and heat-stress frequency decreased in transitioning to the scenario climate. When compounding occurred heat-stress events generally preceded the short-term drought events. The overlapping, compound events tended to be more extreme compared to non-overlapping events of either type. Discussion: The information yielded projected changes in these agriculturally motivated events. One prominent conditional behavior emerging from the work was that a heat-stress event should be a warning to watch for potential drought, as both could compound each other to more intense levels. [ABSTRACT FROM AUTHOR]

The synoptic cold surge is a weather event that frequently occurs in the Northern Hemisphere, often causing severe damage accompanied with intense winds and precipitation. It is reported that the Arctic Oscillation and the North Atlantic Oscillation can affect the cold surge. However, on interacting with tropical circulation, the cold surge potentially links to the Antarctic sea‐ice loss with influence extending to Tropics. Therefore, this research aims to investigate the potential link between Antarctic sea‐ice loss and Northern Hemisphere cold surges and corresponding wind–precipitation compound events. To study this link, twin numerical experiments using a physically based atmosphere model with a prescribed 30% Antarctic sea‐ice loss scenario were used. The results show that the cold surge occurs more frequently in most regions of the world, except for central North America and central Eurasia. In Europe, the cold surges occur closer to the lower latitudes in the Antarctic sea‐ice loss scenario. Additionally, the Antarctic sea‐ice loss can result in intensified wind and precipitation extremes within compound events. The intensified precipitation extremes are caused by increased moisture transportation by tropical easterlies and higher local temperature after the cold surge occurrence, providing more moisture available for precipitation in East Asia and East North America, respectively. Overall, the results of the numerical experiments provide evidence that Antarctic sea‐ice loss influences cold surges in Northern Hemisphere through atmospheric teleconnections. It is important to continue investigating the link between Antarctic sea‐ice loss and weather events like cold surges, as this research can help improve our understanding of the impacts of polar climate change on lower latitudes. [ABSTRACT FROM AUTHOR]

Seasonal climate variability is a major source of crop production risk. The expected increase in climate variability and frequency of extreme events in the coming years and decades due to climate change will bring additional challenges for most commodities and geographies. In recent years, climatic anomalies and extreme weather events have impacted the major global breadbaskets. In many instances, the impact of these events could be unanticipated until a later time during the growing season or even until harvest, challenging existing crop yield forecasting programs and posing a significant threat to global food security. The Climate Information for Agriculture (CIFA) system was developed to identify, measure, and monitor the occurrence of climate anomalies and extreme weather events with the potential to affect crop production during the growing season in the continental USA. CIFA provides near real-time information during the growing season and facilitates the detection of compounded events, thus resulting in more informed decisions by stakeholders. Its capability to alert for the occurrence of extreme weather events was demonstrated in 2019, when a historical delay in planting activities impeded over 7 million hectares intended to be planted across the major U.S. cropping areas and again in 2020, when several abnormal events occurred in areas affected by unusual dryness and above-average temperatures in the U.S. Corn-Belt. CIFA not only contributes to enhancing crop forecasting systems but also serves as a valuable resource for academics and experts providing more reliable and accurate data for developing effective adaptation strategies.

Abstract The compound drought‐extreme precipitation event (CDEP) is one of the most impactful successive compound events that shift from drought to extreme precipitation in the same location within a short period. Due to its dual characteristics of drought and flood, CDEP tends to be more destructive than the impact of individual drought or flood. Yet few studies have analyzed the likelihood of CDEP at different time intervals and their potential variations under global warming. In this study, we assessed the coincidence rate between droughts and extreme precipitation events at 1‐month (CDEP‐1), 2‐month (CDEP‐2), and 3‐month (CDEP‐3) intervals, as well as their potential changes in a 1.5 and 2°C warming world (under both SSP2‐4.5 and SSP5‐8.5 scenarios). Our results suggest that global droughts and extreme precipitation events have coincided more frequently at 1‐month interval than at 2‐ and 3‐month intervals during the period 1985–2014. The global average coincidence rates of CDEP‐1, CDEP‐2, and CDEP‐3 are 24%, 10%, and 7%, respectively. Notably, the coincidence rate of CDEP‐1 exceeded 40% in Eastern Asia, north‐eastern North America, and India, indicating that more than 40% of droughts have been followed by extreme precipitation events in the next month after drought termination. Under both SSP2‐4.5 and SSP5‐8.5 scenarios, climate warming will increase the coincidence rate of CDEP‐1, CDEP‐2, and CDEP‐3, especially will lead to higher values in the coincidence rate of CDEP‐1. This study contributes to a better understanding of the patterns of CDEP and helps to develop more targeted risk management strategies.

Study region: Southwestern China of Hubei, Hunan, Guangxi, Guangdong, Yunnan, Guizhou, Sichuan, and Chongqing. Study focus: Compound hot-dry extreme events (CHDEs) are escalating disproportionately worldwide, posing significant challenges across various sectors. Yet, their driving mechanisms and characteristics at a regional scale remain largely uncertain. This study used a copula-based approach to construct the daily Standardized Compound Hot-Dry Index (SCHDI) to discern the intensifying trends of hot-dry extremes from 1963 to 2022, especially under different karst landscapes in Southwestern China. New hydrological insights for the region: SCHDI variations show an escalation of hot-dry conditions across most areas, with a notable increase in extreme hot, dry, and hot-dry events. There was a consistent increase in the frequency, duration, severity, and intensity of CHDEs, with larger magnitudes observed in non-karst areas. However, karst regions exhibited a higher escalation rate in intensity, especially over the most recent three decades. Land areas affected by less severe CHDEs (e.g., abnormal: −0.31%/year) show decreasing trends over 1993–2022, while the most extreme category (e.g., extreme: 0.34%/year) has increased. The areas affected by CHDEs showed a greater increase in trend slope compared to hot or dry events alone. Additionally, these trends are further influenced by large-scale circulation patterns. Our study highlights the role of karst landscapes in escalating hot-dry extremes in Southwestern China Karst.

The co-occurrence of wind and rainfall extremes can yield larger impacts than when either hazard occurs in isolation. This study assesses compound extremes produced by Extra-tropical cyclones (ETCs) during winter from two perspectives. Firstly, we assess ETCs with extreme footprints of wind and rainfall; footprint severity is measured using the wind severity index (WSI) and rain severity index (RSI) which account for the intensity, duration, and area of either hazard. Secondly, we assess local co-occurrences of 6-hourly wind and rainfall extremes within ETCs. We quantify the likelihood of compound extremes in these two perspectives and characterise a number of their drivers (jet stream, cyclone tracks, and fronts) in control (1981–2000) and future (2060–2081, RCP8.5) climate simulations from a 12-member ensemble of local convection-permitting 2.2 km climate projections over the UK and Ireland. Simulations indicate an increased probability of ETCs producing extremely severe WSI and RSI in the same storm in the future, occurring 3.6 times more frequently (every 5 years compared to every 18 years in the control). This frequency increase is mainly driven by increased rainfall intensities, pointing to a predominantly thermodynamic driver. However, future winds also increase alongside a strengthened jet stream, while a southward displaced jet and cyclone track in these events leads to a dynamically-enhanced increase in temperature. This intensifies rainfall in line with Clausius-Clapeyron, and potentially wind speeds due to additional latent heat energy. Future simulations also indicate an increase in the land area experiencing locally co-occurring wind and rainfall extremes; largely explained by increased rainfall within warm and cold fronts, although the relative increase is highest near cold fronts suggesting increased convective activity. These locally co-occurring extremes are more likely in storms with severe WSI and RSI, but not exclusively so as local co-occurrence requires the coincidence of separate drivers within ETCs. Overall, our results reveal many contributing factors to compound wind and rainfall extremes and their future changes. Further work is needed to understand the uncertainty in the future response by sampling additional climate models.

High temperatures and droughts are two natural disasters that cause forest fires. During climate change, the frequent occurrence of high temperatures, droughts, and their coupled effects significantly increase the forest fire risk. To reveal the seasonal and spatial differences in the coupled effects of high temperatures and droughts on forest fires, this study used the Copula method and proposed the compound extremely high-temperature and drought event index (CTDI). The results indicated that the study area was subject to frequent forest fires in spring (71.56%), and the burned areas were mainly located in forests (40.83%) and the transition zone between farmland and forests (36.91%). The probability of forest fires in summer increased with high temperatures and drought intensity, with high temperatures playing a dominant role. The highest forest fire hazard occurred in summer (>0.98). The probability of a forest fire occurring under extreme meteorological conditions in summer and fall was more than twice as high as that in the same zone under non-extreme conditions. Droughts play a significant role in the occurrence and spread of forest fires during fall. These results can provide decision-making support for forest fire warnings and fire fighting in the Northeast China forest zone.

In this study, a comprehensive multiscale analysis of compounding drought-heat events in the Pantanal region is presented. The goal is to assess the multiscale nature of drought and determine whether the combined effects of drought and heatwaves, as driving factors, are more relevant than the effects of each event separately. The study describes a persistent interannual extreme event characterized by drought and heatwaves in the Pantanal, lasting from 2019 to 2021. The extreme event involved a prolonged dry season, a shortened and delayed rainy season, and persistent heatwaves, resulting in the emergence of drought-heat compound events. Despite experiencing consecutive months of increasing drought hazards and a delayed rainy season in late 2020 to 2021, the northern Pantanal region was unable to recover from the water deficit accumulated due to water stress in the previous year. This emphasizes the long-lasting impacts of compound events on water availability and ecosystem health. Furthermore, the study suggests that interannual water stress played a crucial role in explaining the context that led to record-breaking daily maximum temperatures during the austral spring of 2020. The regions most at risk for such compound extreme events are the northern and central Pantanal. Looking at longer timescales, the analysis of compound drought-heat events can provide insights essential for understanding and preventing their impacts, particularly those that could trigger fire outbreaks. [ABSTRACT FROM AUTHOR]

This study used the "Daily meteorological dataset of basic meteorological elements of China National Surface Weather Station (V3.0)" and applied the absolute threshold method and standardized precipitation evapotranspiration index to identify heatwave events and drought events. This study analyzed the spatiotemporal evolution patterns of three types of summer disaster events, namely, heatwave events, drought events, and compound drought and heatwave events, in Jiangsu Province from 1960 to 2018. Additionally, it investigated and verified the concurrent historical data of the identified years with the most severe occurrence of compound drought and heatwave events and calculated the monthly drought centers and summer accumulations of the standardized precipitation evapotranspiration index (SPEI-3). The results indicate that over the 59 years analyzed, the number of days with a threshold of 35 °C, which were considered hot days, was 503.2, accounting for 9.27% of the total summer days in Jiangsu Province. Both the number of hot days and the frequency of heatwave events showed a clear increasing trend from the northeastern coastal areas to the southwestern regions of Jiangsu Province. The total frequency of drought events at different stations in Jiangsu Province from 1960 to 2018 fell within the range of 50–64. The fitted slope of the frequency of compound drought and heatwave events in Jiangsu Province was −0.021 for the period 1960 to 1989, and 0.079 for the period 1990 to 2018, indicating a higher frequency compared with the preceding 30 years. This trend aligned with the rise in heatwave events experienced in Jiangsu Province in recent years. The frequency and duration of compound drought and heatwave events in Jiangsu Province exhibited an increasing spatial pattern from the southwestern parts to the northeastern parts. This study's verification established that the identification of compound drought and heatwave events was relatively accurate. [ABSTRACT FROM AUTHOR]

Extreme dry and wet events can result in significant crop yield losses. However, the impact of consecutive occurrence of dry and wet extremes on crop yield remains unclear. Here, we investigate the hotspots of compound dry and wet (CDW) extremes across global rice croplands and their impacts on rice yield. We identify a significant increasing trend in the frequency of CDW extremes during 1981–2016. The risk of yield loss caused by CDW extremes can be twice as high as the risk from individual wet and dry extremes. Furthermore, we find that global rice croplands face a 43% higher risk of rice yield loss due to dry‐to‐wet extremes compared to wet‐to‐dry extremes. Our findings provide new insights into the sustainability of global rice production and food security in the face of compound hydrological extremes. Plain Language Summary: It is widely recognized that compound events may exert larger impacts on crop production compared to individual extremes. Here, we investigate the consecutive occurrence of dry and wet (CDW) extremes during the rice‐growing season and estimate their impacts on rice yield. We observe a significant increase in the frequency of CDW extremes across global rice croplands during the rice‐growing season from 1981 to 2016. The CDW extremes exert a larger impact on rice yield loss compared to individual wet and dry extremes. The CDW extremes, characterized by longer durations of both dry and wet extremes and faster transitions between them, have an even more adverse influence on rice yield. The risk of yield loss caused by CDW extremes is 200% higher than the risk from individual wet and dry extremes. Furthermore, global rice croplands face a 43% higher risk of yield loss due to dry‐to‐wet extremes than wet‐to‐dry extremes. Key Points: A significant increasing trend in the frequency of compound dry and wet (CDW) extremes was observed across global rice croplandsThe risk of rice yield loss caused by CDW extremes can be twice as high as the risk from individual wet and dry extremesGlobal rice croplands face a 43% higher risk of rice yield loss caused by dry‐to‐wet extremes compared to wet‐to‐dry extremes [ABSTRACT FROM AUTHOR]

When multiple atmospheric rivers (ARs) occur in rapid succession, the combined effect on the hydrologic system can lead to more flooding and damage than would be expected from the individual events. This temporally compounding risk is a source of growing concern for water managers in California. We present a novel moving average‐based definition of AR "sequences" that identifies the time periods of elevated hydrologic hazard that occur during and after consecutive AR events. This marks the first quantitative evaluation of when temporal compounding is contributing to AR flood risk. We also assess projected changes in sequence frequency, intensity, and duration in California using the Geophysical Fluid Dynamics Laboratory Seamless System for Prediction and EArth system Research (GFDL SPEAR) global coupled model. Sequence frequency increases over time and is fairly uniform across the state under both intermediate (SSP2–4.5) and very high (SSP5–8.5) emissions scenarios, with the largest changes occurring by the end of the century (+0.72 sequences/year in SSP2–4.5, +1.13 sequences/year in SSP5–8.5). Sequence intensity and duration both see increases in the medians and extreme values of their respective distributions relative to the historical baselines. In particular, "super‐sequence" events longer than 60 days are projected to occur 2–3x more frequently and to emerge in places that have never seen them in the historical record. In a world where California precipitation is becoming more variable, our definition of sequences will help identify when and where hydrologic impacts will be most extreme, which can in turn support better management of the state's highly variable water resources and inform future flood mitigation strategies. Plain Language Summary: Atmospheric rivers (ARs) are a type of storm that are vital to water resources in the western United States, but can also cause significant flooding and damage. Back‐to‐back AR events have historically been a source of concern for water managers because the compound effect of multiple events together can increase the probability of damaging floods. We present a definition of AR "sequences" that identifies periods of time where the likelihood of compound effects is increased. We look at the relationship between sequences, runoff, and soil moisture in California and show that sequences are in fact aligning with time windows of elevated hydrologic hazard in the historical record. We then look at sequences in two future climate projections and find that sequence frequency, intensity, and duration are all projected to increase with increasing emissions levels. In particular, "super‐sequences" more than 60 days long are projected to become two to three times more frequent across all of California. Our definition of sequences captures and communicates new information about the risk associated with temporally compounding hydrologic events in present and future climates. Key Points: We introduce atmospheric river (AR) sequences as a way to measure the hydrologic hazard from temporally compounding (back‐to‐back) ARsAR sequences in Geophysical Fluid Dynamics Laboratory Seamless System for Prediction and EArth system Research (GFDL SPEAR) model projections increase in frequency, intensity, and duration in California by the end of the century"Super‐sequences" over 60 days long drive the projected increase in frequency and present a growing water management threat in California [ABSTRACT FROM AUTHOR]

The impacts of climate change on rural cultures and livelihoods depend on how the resulting complex biophysical processes may transform people’s land use practices. We argue that research can incorporate local concerns of compound hazards through deterministic rather than probabilistic approaches to better understand the multiple causations involved in such climate change impacts. We apply mixed methods within a storyline approach to examine how a forest reindeer herding community in Northern Sweden copes with and experiences basal ice formation on their winter pasturelands under the influence of climatic and environmental change. Our results show that the detrimental impact of basal ice formation on the availability of winter forage for reindeer is amplified by the directional effects of climate change and encroachments, especially particular forestry practices and their surrounding infrastructure. On the one hand, we show that policy action can address local concerns through ecological interventions that improve the amount and distribution of ground and pendulous lichens at the pastoral landscape scale. On the other hand, we show that policy inaction can threaten the community’s desired experience of human-animal relations in their landscape, which was inextricably connected to ecological conditions for natural pasture-based reindeer pastoralism. [ABSTRACT FROM AUTHOR]

IntroductionCrops are vulnerable to precipitation and heat extremes during late spring through summer.MethodsWe analyzed for a north-central U.S. region short-term drought and agricultural heat stress during April-May-June-July. We used the 4-km Parameter Elevation Regression on Independent Slopes Model (PRISM) for observations, aggregated to a 25-km grid, and two 25-km Regional Climate Model version 4 (RegCM4) simulns used either GFDL- or MPI-GCM boundary conditions. We chose 1981-2000 as our contemporary time period, and 2041-2060 as our scenario time period, which used the Representative Concentration Pathway 8.5 emissions scenario. We used object-oriented analysis to identify events of interest in observations and simulations by identifying objects in a space-time domain that meet specified criteria, such as exceeding a heat-stress temperature threshold. The event diagnosis allowed analysis of compound events, occurring when temperature and drought objects overlap.ResultsIdentified objects yielded events that can undermine agricultural productivity and which are thus relevant to decision makers, making them building blocks for possible climate storylines. The observations and simulations showed similar spatial distributions of event frequencies across the analysis region. However, the simulations attained this distribution by having fewer events that tend to cover larger areas compared to observed events, suggesting that the effective resolution of the simulations was coarser than their 25-km grids. Short-term drought frequency increased and heat-stress frequency decreased in transitioning to the scenario climate. When compounding occurred heat-stress events generally preceded the short-term drought events. The overlapping, compound events tended to be more extreme compared to non-overlapping events of either type.DiscussionThe information yielded projected changes in these agriculturally motivated events. One prominent conditional behavior emerging from the work was that a heat-stress event should be a warning to watch for potential drought, as both could compound each other to more intense levels.

Disaster risk in the 21st century differs from the experience of past generations and is defined by its evolving systemic nature. The increased role of technological networks, societal interdependencies and climate change dynamics make crises more complex and unpredictable. Cascading and compounding dynamics are becoming the new “business as usual”, challenging emergency management to maintain operations in face of complex disruptions while requiring the development of good practices and strategy for facilitate the recovery process. Our special issue aimed to support the development of a paradigm shift in the understanding of complex events, utilizing a network-based, cross-disciplinary approach to resilience. This editorial introduces and summarizes 18 papers across four thematic areas: 1) Resilience Challenges; 2) Area Studies and the Sendai Framework for Disaster Risk Reduction; 3) Community and Health; 4) Enhancing New Methodologies. The conclusions highlight open research challenges for future exploration.

Co-design processes involving the scientific community, practitioners, end users and stakeholders can efficiently characterize harmful weather events during the growing season that potentially result in losses of crop yield and quality. This study builds on the experience of the EU Horizon 2020 project MED-GOLD for grape and olive. The identified agro-climate indicators are extended from the MED-GOLD regions to the entire ones where grape and olive are currently grown in Europe and Turkey, and used to assess climate change impacts with intrinsic adaptation relevance stemming from the co-design process. Before 2000, only a low fraction of the European grape and olive growing areas was exposed to extreme weather events as revealed by the agro-climate indicators, but this has changed rapidly afterward. Projections show increasingly widespread extreme high temperature events from 2020 to 2080. Approximately one-third of grapevine regions and over half of olive cultivation areas are expected to experience extreme drought conditions. Additionally, the frequency of compound extreme events will increase in the future, especially in the Mediterranean region and under the high-end emission scenario RCP8.5. This outcome calls for a new decision-making mindset that embeds expected levels of climate variability and extremes as the “new normal” for grape and olive in Europe. This will facilitate deployment of the required biophysical, economic and policy adaptation tools.

Global climate change increasingly impacts agroecosystems, particularly through high-temperature–drought and low-temperature–drought compound events. This study uses ground meteorological and remote sensing data and employs geostatistics, random forest models, and copula methods to analyze the spatial and temporal distribution of these events and their impact on winter wheat in the Huang-Huai-Hai Plain from 1982 to 2020. High-temperature–drought events increased in frequency and expanded from north to south, with about 40% of observation stations recording such events from 2001 to 2020. In contrast, low-temperature–drought events decreased in frequency, affecting up to 80% of stations, but with lower frequency than high-temperature–drought events. Sensitivity analyses show winter wheat is most responsive to maximum and minimum temperature changes, with significant correlations to drought and temperature extremes. Copula analysis indicates temperature extremes and drought severity are crucial in determining compound event probability and return periods. High-temperature–drought events are likely under high temperatures and mild drought, while low-temperature–drought events are more common under low temperatures and mild drought. These findings highlight the need for effective agricultural adaptation strategies to mitigate future climate change impacts.

Globally, forests are net carbon sinks that partly mitigates anthropogenic climate change. However, there is evidence of increasing weather-induced tree mortality, which needs to be better understood to improve forest management under future climate conditions. Disentangling drivers of tree mortality is challenging because of their interacting behavior over multiple temporal scales. In this study, we take a data-driven approach to the problem. We generate hourly temperate weather data using a stochastic weather generator to simulate 160,000 years of beech, pine, and spruce forest dynamics with a forest gap model. These data are used to train a generative deep learning model (a modified variational autoencoder) to learn representations of three-year-long monthly weather conditions (precipitation, temperature, and solar radiation) in an unsupervised way. We then associate these weather representations with years of high biomass loss in the forests and derive weather prototypes associated with such years. The identified prototype weather conditions are associated with 5–22% higher median biomass loss compared to the median of all samples, depending on the forest type and the prototype. When prototype weather conditions co-occur, these numbers increase to 10–25%. Our research illustrates how generative deep learning can discover compounding weather patterns associated with extreme impacts.

Abstract Extreme dry and wet events can result in significant crop yield losses. However, the impact of consecutive occurrence of dry and wet extremes on crop yield remains unclear. Here, we investigate the hotspots of compound dry and wet (CDW) extremes across global rice croplands and their impacts on rice yield. We identify a significant increasing trend in the frequency of CDW extremes during 1981–2016. The risk of yield loss caused by CDW extremes can be twice as high as the risk from individual wet and dry extremes. Furthermore, we find that global rice croplands face a 43% higher risk of rice yield loss due to dry‐to‐wet extremes compared to wet‐to‐dry extremes. Our findings provide new insights into the sustainability of global rice production and food security in the face of compound hydrological extremes.

Abstract When multiple atmospheric rivers (ARs) occur in rapid succession, the combined effect on the hydrologic system can lead to more flooding and damage than would be expected from the individual events. This temporally compounding risk is a source of growing concern for water managers in California. We present a novel moving average‐based definition of AR “sequences” that identifies the time periods of elevated hydrologic hazard that occur during and after consecutive AR events. This marks the first quantitative evaluation of when temporal compounding is contributing to AR flood risk. We also assess projected changes in sequence frequency, intensity, and duration in California using the Geophysical Fluid Dynamics Laboratory Seamless System for Prediction and EArth system Research (GFDL SPEAR) global coupled model. Sequence frequency increases over time and is fairly uniform across the state under both intermediate (SSP2–4.5) and very high (SSP5–8.5) emissions scenarios, with the largest changes occurring by the end of the century (+0.72 sequences/year in SSP2–4.5, +1.13 sequences/year in SSP5–8.5). Sequence intensity and duration both see increases in the medians and extreme values of their respective distributions relative to the historical baselines. In particular, “super‐sequence” events longer than 60 days are projected to occur 2–3x more frequently and to emerge in places that have never seen them in the historical record. In a world where California precipitation is becoming more variable, our definition of sequences will help identify when and where hydrologic impacts will be most extreme, which can in turn support better management of the state's highly variable water resources and inform future flood mitigation strategies.

Climate change is exacerbating the occurrence of compound droughts and heatwaves (CDHWs), which pose a serious threat to human health and socio-economic development. Using daily maximum temperature (Tmax) and monthly self-calibrating Palmer drought severity index (sc-PDSI) dataset, the evolution patterns of CDHWs and compound wet-heatwave events, the dominant drivers and the relative contributions of droughts and heatwaves in the drylands and humid areas from 1961 to 2020 were compared and analyzed. The results show that the CDHWs are stronger in drylands than in humid areas, the growth rate of CDHWs in drylands was almost twice that of the humid areas, the CDHWs are greater than the multi-year average intensity of compound wet-heatwave events by up to 2.4 times. Moreover, CDHWs has increased significantly from the past period (1961–1990) to the recent warm period (1991–2020), and the heatwave threshold has increased by about 5 °C. In most drylands, the contribution of heatwaves to CDHWs dominates, whereas in humid areas, the droughts contribution to CDHWs does. The compounding effects of droughts and heatwaves may exacerbate the severity of CDHWs regionally and are most pronounced in drylands, taking into account optimal lags. The study findings could provide scientific and technological support to actively address global climate change risks.

Owing to their potentially amplified impacts, compound dry‐hot events (CDHEs) can pose serious risk to human life and ecosystems. However, studies have mainly assessed the risk related to CDHEs from the hazard or exposure perspective, while a system risk assessment incorporating the hazard, exposure and vulnerability at the global scale is lacking. This study assessed the risk from CDHEs based on model simulations from Coupled Model Intercomparison Project 6 (CMIP6) models for different future periods, including near term (2021–2040), mid‐term (2041–2060) and long term (2081–2100) periods, under two different Shared Socioeconomic Pathways (SSPs) scenarios. Using cropland and population as exposure indicators, the risk from CDHEs to human and agricultural systems was investigated by combing the hazard (the frequency or duration of CDHEs) and vulnerability indicators (GDP and irrigation fraction). Results showed a widespread increase in the risk to human and agricultural systems (represented by the populations and cropland) under the two scenarios (SSP2‐4.5 and SSP5‐8.5) across the globe, particularly in North America, Europe, Africa and Oceania for population and northern South America, large parts of Europe, and southeast China for cropland. The median values of relative changes in risk to human (cropland) systems were 136%, 213% and 207% (102%, 161% and 225%) for the near term, mid‐term and long term, respectively. The increase in hazards was shown to primarily contribute to the increased population risk. This study may provide useful insights for future risk management of compound extremes in human and agricultural systems. [ABSTRACT FROM AUTHOR]

Heatwaves have been shown to increase the likelihood and intensity of extreme rainfall occurring immediately afterward, potentially leading to increased flood risk. However, the exact mechanisms connecting heatwaves to extreme rainfall remain poorly understood. In this study, we use weather type data sets for Australia and Europe to identify weather patterns, including fronts, cyclones, and thunderstorm conditions, associated with heatwave terminations and following extreme rainfall events. We further analyze, using reanalysis data, how atmospheric instability and moisture availability change before and after the heatwave termination depending on whether the heatwave is followed by extreme rainfall, as well as the location of the heatwave. We find that most heatwaves terminate during thunderstorm and/or frontal conditions. Additionally, atmospheric instability and moisture availability increase several days before the heatwave termination; but only if heatwaves are followed by extreme rainfall. We also find that atmospheric instability and moisture after a heatwave are significantly higher than expected from climatology for the same time of the year, and that highest values of instability and moisture are associated with highest post‐heatwave rainfall intensities. We conclude that the joint presence of high atmospheric instability, moisture, as well as frontal systems are likely to explain why rainfall is generally more extreme and likely after heatwaves, as well as why this compound hazard is mainly found in the non‐arid mid and high latitudes. An improved understanding of the drivers of these compound events will help assess potential changing impacts in the future. Plain Language Summary: Extreme rainfall which can lead to flash floods is more likely to occur if it is preceded by a heatwave. The exact reasons behind this connection, however, are not fully clear. In this study we investigate the mechanistic drivers connecting heatwaves to extreme rainfall in Europe and Australia by analyzing which types of weather (e.g., fronts, cyclones, thunderstorms) are present during the transition from heatwaves to extreme rainfall. We also analyze how atmospheric characteristics associated with extreme rainfall during thunderstorms change depending on if a heatwave is followed by extreme rainfall or not. We find that heatwaves are usually followed by extreme rainfall when there are thunderstorm conditions and/or when there is the presence of a front. Further, we find that high amounts of moisture are present if heatwaves are followed by extreme rainfall and that atmospheric conditions favorable for thunderstorms, including high amounts of moisture are generally increased after heatwaves. These findings help understand how heatwaves are connected to extreme rainfall and can help assess how the risk from these events might change in the future. Key Points: The transition from heatwaves to extreme rainfall is usually associated with fronts and/or thunderstorm conditionsAtmospheric instability and moisture are larger than during non‐heatwave conditions and increase over several days before the terminationAvailability of moisture is important for producing extreme rainfall after heatwaves and explains the spatial variability for this event [ABSTRACT FROM AUTHOR]

The increase in record‐breaking extreme events caused by climate change poses a threat to human health and well‐being. Understanding the future impacts of such events on global populations can provide decision‐making support for policies aiming to mitigate climate change. Here, we investigated the population exposure to eight climate extreme indices and drivers of exposure trajectories based on National Aeronautics and Space Administration Earth Exchange Global Daily Downscaled Projections Coupled Model Intercomparison Project 6 and population projection data under four shared socioeconomic pathway scenarios at a spatial resolution of 0.25° × 0.25°. The results show that by the mid‐twenty‐first century, most regions worldwide, especially Africa and South America, will continue to experience record‐breaking temperatures and compound drought and heatwaves (CDHWs). Regarding population exposure, under SSP3‐7.0 in the late twenty‐first century, the mean value of the multimodel median expected annual exposure (EAE) of all extreme temperature indices and CDHW reaches 8.12 billion persons per year. Population exposure hotspots will be concentrated in Central Africa, South Asia, Southeast Asia, and East Asia, mostly in developing countries, where 55.01%–87.42% of the EAE is found. The drivers of exposure trajectories are spatially heterogeneous. The increase in record‐breaking probability contributes more than population growth to EAE growth in most regions of the world except Central Asia, the Middle East, and most of Africa. These findings reveal the future trajectories of record‐breaking probabilities and population exposures for climate extremes, which can inform understanding of the intersections between climate change and population change and future risk management. Plain Language Summary: Climate change causes rapid increases in extreme weather events that threaten human health and well‐being. Understanding the future impacts of climate change on the global population can inform policies aiming to mitigate climate change. Here, we investigated the spatiotemporal dynamics of future record‐breaking extreme temperature and precipitation events, sequential precipitation and heatwaves (hot extremes after heavy precipitation), and compound drought and heatwaves (cooccurring dry and hot extremes) (CDHWs) and analyzed how populations may be potentially affected by these events based on the latest available climate model data and future population projections. The results show that by the mid‐twenty‐first century, most regions worldwide, especially Africa and South America, will continue to experience record‐breaking temperatures and CDHWs. Regions where populations will be most affected include Central Africa, South Asia, Southeast Asia, and East Asia, mostly developing countries. This increase in the affected population is due to the growth of the population and the increase in record‐breaking extreme events; record‐breaking extreme event increases contribute more than population growth in most regions of the world except Central Asia, the Middle East, and most of Africa. Overall, this study projected the spatiotemporal patterns of unprecedented climate extremes and affected populations to inform risk management. Key Points: Africa and South America will experience successive record‐breaking extreme events and even compound droughts and heatwavesPopulation exposure will be highly uneven and largely concentrated in underdeveloped areasA record‐breaking increase in probability will be the major driver of the increase in population exposure in most regions of the world [ABSTRACT FROM AUTHOR]

The number of climate-related disasters has progressively increased in the last two decades and this trend will drastically exacerbate in the medium- and long-term horizons according to climate change projections. In this framework, through a multi-disciplinary team and a strong background acquired in recent projects, ICARIA aims to promote the use of asset-level modeling to achieve a better understanding of climate related tangible direct and indirect impacts on critical assets due to complex, cascading, and compound disasters. Furthermore, it takes into account the related risk reduction provided by suitable, sustainable, and cost-effective adaptation solutions. ICARIA focuses on both (i) critical assets and services that were not designed for potential climate change-related impacts that can increase the unplanned outages and failures, and (ii) on housing, natural areas, and population. Cutting edge methods regarding climate scenario building, asset-level-coupled models, and multi-risk assessment approaches will be implemented and replicated in three EU regions to understand how future climate scenarios might affect critical assets and to provide decision-making support tools to private and public risk owners to assess the costs and benefits of various adaptation solutions. [ABSTRACT FROM AUTHOR]

Compound extreme natural events cause a significantly larger impact than individual extreme events. Therefore, the urgency of exploring the climatology of compound events is growing. This paper is aimed to identify the current hotspots of compound heatwaves and droughts (CHD) and trends in their occurrence in southeast Australia. In this context, 61 weather stations were selected from the study area, and analyses were carried out over the extended summer season of the time period 1971–2021. The hotspots of CHDs in southeast Australia were identified considering both the total count of CHD days and 90th percentile of CHDs during the study period. The study period was divided into two periods 1971–2000 and 2001–2021, to assess the change in hotspots spatially and temporally. Four different attributes of CHDs based on the number, duration, severity and amplitude of CHDs were also calculated, and Mann–Kendall (MK) test followed by Sen's slope was adopted to detect the trends in all these four attributes of CHDs. Trends in CHD indices were also calculated for the two periods of 1971–2000 and 2001–2021. For calculating the CHD, excess heat factor (EHF) was used to identify the heatwaves. In the case of drought identification, SPEI and SPI drought indices were adopted with aggregation of 3 and 126 antecedent months, and three different threshold values were selected to consider three levels of dry conditions, e.g. 0, − 0.5 and − 1.0. It has been found that more CHDs occurred on the eastern side of NSW and Queensland states. Furthermore, the total count of CHD days increased notably during the last two decades. The trends in CHD indices were found to be significant in the recent period (2001–2021), and there was no trend in the earlier period (1971–2000). The findings of this study will help to plan heat and drought-related emergency management in the study area. [ABSTRACT FROM AUTHOR]

Significant increases in both heatwaves and heavy precipitation were reported under global warming, leading to detrimental social, economic, and environmental impacts. However, future variations of such compound heatwave and heavy precipitation events (CHWHPs) were barely analyzed in Guangdong. Therefore, a downscaled compound heatwave-precipitation analysis approach (DCHP) was developed to explore the spatio-temporal variations of CHWHPs in Guangdong under two shared socioeconomic pathways (i.e., SSPs). Potential changes in four parameters (i.e., the occurrence frequency, the average duration, the total intensity, and the longest duration) of projected CHWHPs for the future (i.e., 2025–2054 and 2066–2095) and historical (i.e., 1985–2014) periods were analyzed based on the multi-model ensemble of 15 global climate models (GCMs) from the Coupled Model Intercomparison Projected Phase 6 (CMIP6). Additionally, the effects of multiple impact factors (GCM, SSP, and their interactions) on the compound events were investigated through a multilevel factorial analysis approach. The results showed that the majority of Guangdong would undergo a significant increasing trend in the projected temperature and precipitation (e.g., 0.43–0.61 °C per decade and − 7.79 to 43.02 mm per decade under SSP5–8.5). Spatial changes and interannual trends suggested that Guangdong would suffer more CHWHP events in the future, especially for 2066–2095 under SSP5–8.5. The variations of four parameters are projected to increase by 13.86 events, 2.27 days per event, 55.32 °C, and 7.13 days during 2066–2095 under SSP5–8.5, respectively; the MK test of four parameters are statistically significant and the Sen's slopes are 0.0125%, 0.0027%, 0.1946%, and 0.0097% per decade, respectively. The higher increases in such parameters are expected to be concentrated in western, northwestern, and northeastern Guangdong. The factorial analysis results indicate that the GCM choice is a major impacting factor on the projected CHWHP parameters in two future periods; the contribution of such factor would decrease slightly from 2025–2054 to 2066–2095. The results can help support informed decision-making to mitigate and adapt to potential risks from compound events in multiple sectors under climate change, such as human health and agriculture. [ABSTRACT FROM AUTHOR]

Abstract The increase in record‐breaking extreme events caused by climate change poses a threat to human health and well‐being. Understanding the future impacts of such events on global populations can provide decision‐making support for policies aiming to mitigate climate change. Here, we investigated the population exposure to eight climate extreme indices and drivers of exposure trajectories based on National Aeronautics and Space Administration Earth Exchange Global Daily Downscaled Projections Coupled Model Intercomparison Project 6 and population projection data under four shared socioeconomic pathway scenarios at a spatial resolution of 0.25° × 0.25°. The results show that by the mid‐twenty‐first century, most regions worldwide, especially Africa and South America, will continue to experience record‐breaking temperatures and compound drought and heatwaves (CDHWs). Regarding population exposure, under SSP3‐7.0 in the late twenty‐first century, the mean value of the multimodel median expected annual exposure (EAE) of all extreme temperature indices and CDHW reaches 8.12 billion persons per year. Population exposure hotspots will be concentrated in Central Africa, South Asia, Southeast Asia, and East Asia, mostly in developing countries, where 55.01%–87.42% of the EAE is found. The drivers of exposure trajectories are spatially heterogeneous. The increase in record‐breaking probability contributes more than population growth to EAE growth in most regions of the world except Central Asia, the Middle East, and most of Africa. These findings reveal the future trajectories of record‐breaking probabilities and population exposures for climate extremes, which can inform understanding of the intersections between climate change and population change and future risk management.

While disaster events are consequential, they are rare. Ecological risk assessment processes tend to estimate risk through an “expected value” lens that focuses on the most probable events, which can drastically underappreciate the importance of rare events. Here, we show that expected value and average risk-based calculations underappreciate disaster events through questionable assumptions about equally weighing high probability low impact events with low probability high impact events, and in modeling probability as a chance among an ensemble of possible futures when many contexts of ecological risk assessment are focused on a single entity over time. We propose an update to ecological risk assessment that is specifically inclusive of disaster risk potential by adopting analytical processes that estimate the maximum hazard or impact that might be experienced in the future, borrowing from the practice of modeling “Value at Risk” in financial risk contexts. We show how this approach can be adopted in a variety of data contexts, including situations where no quantitative data is available and risk assessment is based on expert judgement, which is common for ecological risk assessment. Increased exposure to environmental variation requires assessment tools to better prepare for, mitigate, and respond to disasters.

The impacts of hot, dry, and compound hot‐dry extremes are significant for societies, economies, and ecosystems worldwide. Such events therefore need to be assessed in the light of anthropogenic climate change so that suitable adaptation measures can be implemented by governments and stakeholders. Here we show a comprehensive analysis of hot, dry, and compound hot‐dry extremes over global land regions using 25 Coupled Model Intercomparison Project Phase 6 models and four future emissions scenarios from 1950 to 2100. Hot, dry, and compound hot‐dry extremes are projected to increase over large parts of the globe by the end of the 21st century. Hot and compound hot‐dry extremes show the most widespread increases and dry extreme changes are sensitive to the index used. Many regional changes depend on the strength of greenhouse‐gas forcing, which highlights the potential to limit the changes with strong mitigation efforts. Plain Language Summary: Heatwaves, drought and their joint occurrences can negatively impact populations, economies, and natural systems worldwide. It is therefore of paramount importance that governments and stakeholders assess the risk from such events and adapt accordingly. In this study we use 25 climate models and four emission scenarios from 1950 to 2100 to assess how hot, dry, and compound hot‐dry extremes are expected to change in the future when compared to current climate conditions. We find that such extremes are projected to increase by the end of the 21st century over large parts of global land areas under the highest‐emission, no‐policy, climate change scenario. Hot and compound hot‐dry extremes show the most widespread increases, whereas dry extreme changes are sensitive and more regionally limited depending on the method by which they are computed. Most of the regional changes in hot, dry, and compound hot‐dry extremes can be reduced with strong climate change mitigation efforts to limit future green‐house gas emissions. Key Points: Hot extremes are projected to increase in frequency and intensity over almost all land areas by the end of the 21st centuryDrought changes depend on measure but increase robustly over central and northern South America, the Mediterranean, and southern AfricaCompound hot and dry extremes are sensitive to the drought measure but projected to increase in most regions globally [ABSTRACT FROM AUTHOR]

A 38-year hindcast water-level product is developed for the US Southeast Atlantic coastline from the entrance of Chesapeake Bay to the southeast tip of Florida. The water-level modeling framework utilized in this study combines a global-scale hydrodynamic model (Global Tide and Surge Model, GTSM-ERA5), a novel ensemble-based tide model, a parameterized wave setup model, and statistical corrections applied to improve modeled water-level components. Corrected water-level data are found to be skillful, with an RMSE of 13 cm, when compared to observed water-level measurement at tide gauge locations. The largest errors in the hindcast are location-based and typically found in the tidal component of the model. Extreme water levels across the region are driven by compound events, in this case referring to combined surge, tide, and wave forcing. However, the relative importance of water-level components varies spatially, such that tides are found to be more important in the center of the study region, non-tidal residual water levels to the north, and wave setup in the north and south. Hurricanes drive the most extreme water-level events within the study area, but non-hurricane events define the low to mid-level recurrence interval water-level events. This study presents a robust analysis of the complex oceanographic factors that drive coastal flood events. This dataset will support a variety of critical coastal research goals including research related to coastal hazards, landscape change, and community risk assessments. [ABSTRACT FROM AUTHOR]

The Canadian Prairies are a major grain production region, producing most of the wheat for export in Canada. Global warming and the associated changes in extreme precipitation and temperature events pose significant risks to agriculture on the Canadian Prairies. Compound hazards can cause higher crop failure than isolated events, especially in the main grain production regions in western Canada. To achieve informed climate risk management, it is critical to characterize the threats posed by compound hazards in current and future climates in western Canada. In this study, return periods of events were computed to assess the potential changes in the hotspots for agriculturally relevant compound events in western Canada using two convection‐permitting climate simulations: current (CTL) climate and future climate under the RCP8.5 scenario based on a pseudo‐global‐warming (PGW) approach. Specifically, our study analyzed agricultural drought, low precipitation, heatwaves, and cool waves related to cool‐season crops. The results showed the overall good performance of the CTL simulation in capturing spatial patterns of these compound events in western Canada. In the current climate, droughts and heatwaves co‐occur mostly in southeastern parts of the prairies. Under the RCP8.5 scenario, they are likely to increase in frequency and expand to cover the major croplands of western Canada. This study provides information that policymakers in the fields of climate change adaptation and agricultural disaster management will find useful. [ABSTRACT FROM AUTHOR]