Compound Events Research Articles

Compound drought and heat waves variation and association with SST modes across China

Compound drought and heatwaves (CDH) have garnered increasing attention because concurrent extreme events can exacerbate the harmful impacts caused by univariate extremes. However, various severities in CDH events and their relationships with sea surface temperature (SST) variations in China remain little understood. Here, we accurately identify CDH events and multi-aspect of characteristics using the standardized precipitation evapotranspiration index (SPEI) and the excess heat factor (EHF) during the extended summer (May–September) of 1961–2017. The evolution of multifaceted characteristics of CDH and their association with SST variation are further explored. The results suggest that the number, frequency, duration and intensity of regional CDH events show heterogeneous spatial patterns, with a significant increasing trend. A consistent abrupt transition in CDH characteristics averaged over China occurred in the period of 1993–1996. Mild and moderate CDHs occur more commonly in Northwest and North China, whereas severe CDHs are mainly found in central and eastern regions. Mild and moderate CDHs are more susceptible to SST modes than severe CDH, and there are strong positive correlations between mild and moderate CDH characteristics and SST variations in the northwest and northern regions. Compared to El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) plays a dominant role in the intensifications of mild and moderate CDH events. Regionally, the northwest and north have experienced longer, more frequent and severe CDH events during the positive phase of IOD. These findings reveal the divergent evolutions in CDH characteristics with various severities and inconsistent impacts of different SST modes on the compound events.

Coastal Morphodynamics and Climate Change: A Review of Recent Advances

The shape of the coast and the processes that mold it change together as a complex system. There is constant feedback among the multiple components of the system, and when climate changes, all facets of the system change. Abrupt shifts to different states can also take place when certain tipping points are crossed. The coupling of rapid warming in the Arctic with melting sea ice is one example of positive feedback. Climate changes, particularly rising sea temperatures, are causing an increasing frequency of tropical storms and “compound events” such as storm surges combined with torrential rains. These events are superimposed on progressive rises in relative sea level and are anticipated to push many coastal morphodynamic systems to tipping points beyond which return to preexisting conditions is unlikely. Complex systems modeling results and long-term sets of observations from diverse cases help to anticipate future coastal threats. Innovative engineering solutions are needed to adapt to changes in coastal landscapes and environmental risks. New understandings of cascading climate-change-related physical, ecological, socioeconomic effects, and multi-faceted morphodynamic systems are continually contributing to the imperative search for resilience. Recent contributions, summarized here, are based on theory, observations, numerically modeled results, regional case studies, and global projections.

Human influences on spatially compounding flooding and heatwave events in China and future increasing risks

Attribution of high-impact weather events to anthropogenic climate change is important for disentangling long-term trends from natural variability and estimating potential future impacts. Up to this point, most attribution studies have focused on univariate drivers, despite the fact that many impacts are related to multiple compounding weather and climate drivers. For instance, co-occurring climate extremes in neighbouring regions can lead to very large combined impacts. Yet, attribution of spatially compounding events with different hazards poses a great challenge. Here, we present a comprehensive framework for compound event attribution to disentangle the effects of natural variability and anthropogenic climate change on the event. Taking the 2020 spatially compounding heavy precipitation and heatwave event in China as a showcase, we find that the respective dynamic and thermodynamic contributions to the intensity of this event are 51% (35–67%) and 39% (18–59%), and anthropogenic climate change has increased the occurrence probability of similar events at least 10-fold. We estimate that compared to the current climate, such events will become 10 times and 14 times more likely until the middle and end of the 21st century, respectively, under a high-emissions scenario. This increase in likelihood can be substantially reduced (to seven times more likely) under a low-emissions scenario. Our study demonstrates the effect of anthropogenic climate change on high-impact compound extreme events and highlights the urgent need to reduce greenhouse gas emissions.

Extreme and compound ocean events are key drivers of projected low pelagic fish biomass.

Ocean extreme events, such as marine heatwaves, can have harmful impacts on marine ecosystems. Understanding the risks posed by such extreme events is key to develop strategies to predict and mitigate their effects. However, the underlying ocean conditions driving severe impacts on marine ecosystems are complex and often unknown as risks to marine ecosystems arise not only from hazards but also from the interactions between hazards, exposure and vulnerability. Marine ecosystems may not be impacted by extreme events in single drivers but rather by the compounding effects of moderate ocean anomalies. Here, we employ an ensemble climate-impact modeling approach that combines a global marine fish model with output from a large ensemble simulation of an Earth system model, to identify the key ocean ecosystem drivers associated with the most severe impacts on the total biomass of 326 pelagic fish species. We show that low net primary productivity is the most influential driver of extremely low fish biomass over 68% of the ocean area considered by the model, especially in the subtropics and the mid-latitudes, followed by high temperature and low oxygen in the eastern equatorial Pacific and the high latitudes. Severe biomass loss is generally driven by extreme anomalies in at least one ocean ecosystem driver, except in the tropics, where a combination of moderate ocean anomalies is sufficient to drive extreme impacts. Single moderate anomalies never drive extremely low fish biomass. Compound events with either moderate or extreme ocean conditions are a necessary condition for extremely low fish biomass over 78% of the global ocean, and compound events with at least one extreme variable are a necessary condition over 61% of the global ocean. Overall, our model results highlight the crucial role of extreme and compound events in driving severe impacts on pelagic marine ecosystems.

Assessing the compound flood risk in coastal areas: Framework formulation and demonstration

Storm surge and river runoff can result in compound flooding in coastal areas. The impact of these events can be more significant than that generated by each component individually. This paper describes a framework for characterizing flooding during compound events and quantifying the relative importance of surge and river flows in controlling inundation depth (ID). For the analysis, we considered 1051 simulations of historical flood events covering about 40 years in Connecticut (CT), USA, and several simulated storms associated with synthetic climate scenarios. We simulated river discharge time series for each event using a physically based distributed hydrological model and retrieved the storm surge from tidal stations. These time series are used as upstream and downstream boundary conditions in 2D hydrodynamic simulation. We focused the analysis on seven locations along the coast of Connecticut covered by LiDAR-derived 1 m DEM. To capture the variability of inundation characteristics over the full-scale gradient from river to coast, we introduced a new topographic index, D-Index, that distinguishes topologic variabilities. Results from this study highlight that there is a correlation of ID to different drivers in distinct categories of the D-Index, which can correctly label the main source of hazard, either coast, river, or compound. We identified thresholds of standard deviation (σ) of the D-Index to identify areas where ID strongly correlates with either flow peak and volume, surge peak, or a combination of both. The study also shows that it is possible to use the results obtained from the 1 m analysis to generalize the findings for the entire CT coast to derive zones dominated by surge, river flow, or the compound effect of the two. This study can help coastal communities better understand the risk of the compound impacts of coastal storms, which is essential for increasing climate resilience.

Acute Health Effects of Wildfire Smoke Exposure During a Compound Event: A Case-Crossover Study of the 2016 Great Smoky Mountain Wildfires.

In 2016, unprecedented intense wildfires burned over 150,000 acres in the southern Appalachian Mountains in the United States. Smoke from these fires greatly impacted the region and exposure to this smoke was significant. A bidirectional case-crossover design was applied to assess the relationship between PM2.5 (a surrogate for wildfire smoke) exposure and respiratory- and cardiovascular-related emergency department (ED) visits in Western North Carolina during these events. For 0-, 3-, and 7-day lags, findings indicated a significant increase in the odds of being admitted to the ED for a respiratory (ORs: 1.055, 95% CI: 1.048-1.063; 1.083, 1.074-1.092; 1.066, 1.058-1.074; respectively) or cardiovascular event (ORs: 1.052, 95% CI: 1.045-1.060; 1.074, 1.066-1.081; 1.067, 1.060-1.075; respectively) for every 5μg/m3 increase in PM2.5 over a chosen cutpoint of 20.4μg/m3. For all endpoints assessed except for emphysema, there were statistically significant increases in odds from 5.1% to 8.3%. In general, this increase was most pronounced 3days after exposure. Additionally, individuals aged 55+ generally experience higher odds of heart disease at the 3- and 7-day lag points, and Black/African Americans generally experience higher odds of asthma at the 3-day lag point. In general, larger fires and increased numbers of fires within counties resulted in higher health burden at same day exposure. In a secondary analysis, the odds of an ED visit increased by over 40% in several cases among people exposed to days above the Environmental Protection Agency 24-hr PM2.5 standard of 35μg/m3. Our findings provide new understanding on the health impacts of wildfires on rural populations in the southeastern US.

Sectoral water use responses to droughts and heatwaves: analyses from local to global scales for 1990–2019

Water use for various sectors (e.g. irrigation, livestock, domestic, energy and manufacturing) is increasing due to a growing global population and economic development. Additionally, increases in frequency and severity of droughts, heatwaves and compound drought-heatwave events, also lead to responses in sectoral water use and a reduction in water availability, intensifying water scarcity. However, limited knowledge exists on the responses in sectoral water use during these hydroclimatic extremes. In this study we quantify the impacts of droughts, heatwaves and compound events on water use of irrigation, livestock, domestic, energy and manufacturing sectors at global, country and local scales. To achieve this, datasets of reported and downscaled sectoral water use (i.e. withdrawal and consumption) were evaluated during these hydroclimatic extremes and compared to normal (non-extreme) periods for 1990–2019. Our analysis shows that these hydroclimatic extremes affect water use patterns differently per sector and region. Reported data show that domestic and irrigation water use increases during heatwaves in Eastern Europe and central continental United States, while water use decreases for thermoelectric sector, particularly in Europe while it increases in north and Eastern Asia. Additionally, global water use response patterns reveal that irrigation and domestic sectors are mostly prioritized over livestock, thermoelectric and manufacturing. Reported local-scale data reveal that for most sectors and regions/locations, stronger water use responses are found for heatwaves and compound events compared to impacts during hydrological droughts. Our outcomes provide improved understanding of sectoral water use behaviour under hydroclimatic extremes. Nonetheless, given the future threats to water availability and the limited accessible information of water use, there is an urgency to collect more monitored-driven data of sectoral water use for improved assessments of water scarcity under these extremes. Consequently, this research reveals the necessity of more realistic water use models to better represent the sectoral responses to hydroclimatic extremes.

Quantifying Multi-hazards and Impacts Over Different Growth Periods of Maize: A Study Based on Index Construction

AbstractOwing to the complexity and variability of global climate, the study of extreme events to ensure food security is particularly critical. The standardized precipitation requirement index (SPRI) and chilling injury index (ICi) were introduced using data from agrometeorological stations on the Songliao Plain between 1981 and 2020 to identify the spatial and temporal variability of drought, waterlogging, and low-temperature cold damage during various maize growth periods. Compound drought and low-temperature cold damage events (CDLEs) and compound waterlogging and low-temperature cold damage events (CWLEs) were then identified. To measure the intensity of compound events, the compound drought and low-temperature cold damage magnitude index (CDLMI), and compound waterlogging and low-temperature cold damage magnitude index (CWLMI) were constructed by fitting marginal distributions. Finally, the effects of extreme events of various intensities on maize output were examined. The findings demonstrate that: (1) There were significant differences in the temporal trends of the SPRI and ICi during different maize growth periods. Drought predominated in the middle growth period (MP), waterlogging predominated in the early growth period (EP) and late growth period (LP), and both drought and waterlogging tended to increase in intensity and frequency. The frequency of low-temperature cold damage showed a decreasing trend in all periods. (2) The CDLMI and CWLMI can effectively determine the intensity of CDLEs and CWLEs in the study area; these CDLEs and CWLEs had higher intensity and frequency in the late growth period. (3) Compared to single events, maize relative meteorological yield had a more significant negative correlation with the CDLMI and CWLMI.

Investigating Spatial Variations of Compound Heat–Precipitation Events in Guangdong, China through a Convection-Permitting Model

Compound heat–precipitation events exert significant impacts on severe weather occurrences. Intense vertical air movement, driving vigorous convection, primarily contributes to the formation of extreme precipitation. Nevertheless, such compound events’ temporal and spatial variation patterns at convection-permitting resolutions remain inadequately explored. This study assesses the performance of the Convection-Permitting Model (CPM) against a model of convection parameterization while investigating the spatial dynamics of compound heat–precipitation events in Guangdong, China. Our findings indicate that the CPM exhibits heightened reliability and precision in simulating temperature and precipitation patterns, especially in extreme precipitation simulation, which would be highly underestimated without a convection-permitting process. Projections from the CPM reveal that, across historical and future periods, the occurrence frequency and fraction of T-P events (instances of extreme heat followed by extreme precipitation) surpass those of P-T events (occurrences of extreme precipitation followed by extreme heat). For T-P events, the CPM exhibits better capability in capturing high-frequency occurrence areas, whereas the results of the relatively low-resolution model show less distinct spatial variations. Both types of events exhibit noticeable upward trends yearly within each period. By the close of this century, the provincial average frequency of P-T events is anticipated to decrease from 20.32 times to 14.55 times. In contrast, the frequency of T-P events is projected to increase from 87.7 times to 101.38 times. These projected changes underscore the shifting dynamics of compound heat–precipitation events in the study region.

Multiscale analysis of drought, heatwaves, and compound events in the Brazilian Pantanal in 2019–2021

Multiscale analysis of drought, heatwaves, and compound events in the Brazilian Pantanal in 2019–2021

Compound events of wet and dry extremes: Identification, variations, and risky patterns

Compound hydrometeorological extremes have been widely examined under climate change, they have significant impacts on ecological and societal well-being. This study sheds light on a new category compound of contrasting extremes, namely compounding wet and dry extremes (CWDEs). The CWDEs are characterized as devastating dry events (EDs) accompanied by wet extremes (EWs) in a given time window. Notably, we first adopt a separate system to identify coinciding events considering the different evolving processes and impacting patterns of EDs and EWs. The peak-over-threshold and standardized index methods are used in a daily and monthly window to identify EWs and EDs respectively. Furthermore, the spatial-temporal changes and risky patterns of CWDEs are revealed by using the Mann-Kendall test, the Ordinary Least Squares, and the Global and Local Moran indices. Germany is the study case. As one major finding, the results indicate a pronounced seasonal effect and spatial clustering pattern of CWDEs. The summer is the most vulnerable period for CWDEs, and the spatial hotspots are mainly located in the southern tip of Germany, as well as in the vicinity of the capital city Berlin. Besides, robust uptrends in CWDEs across all evaluation metrics have been discovered in historical periods, and the moist climate and complex geography collectively contribute to severe CWDEs. Unexpectedly, the study finds that compounding events in dry regions are mainly driven by wet extremes, whereas they show a higher dependency on dry anomalies in wet regions. The research provides new insights into compound extremes which are composed of individual hazards with distinct features. Related findings will aid decision-makers in producing effective risk mitigation plans for prioritizing vulnerable regions. Lastly, the robust framework and open access data allow for extensive exploration of various compounding hazards in different regions.

Exploring the relationship between flood insurance claims, crowdsourced rainfall, and tide levels for coastal urban communities: Case study for the mid-Atlantic United States

The Federal Emergency Management Agency (FEMA) recently released a large dataset (∼2.5 million records) of flood insurance claim transactions from the National Flood Insurance Program (NFIP) that are geolocated by census tract. In this study, we present a methodology for using these NFIP flood claims along with agency rainfall and tide level data, combined with high-resolution rainfall data collected from growing networks of crowdsourced Personal Weather Stations (PWSs), to investigate the characteristics of storm events that result in flood insurance claims. Using 25 cities/counties in five metropolitan areas in the Mid-Atlantic region as case studies for testing the methodology, we find that the majority of flood claim events in this region were associated with rainfall below a 1-year return period and a tide level below the NOAA minor flood risk tide level. When storm events exceeded these rainfall and tide thresholds, the probability of a flood claim occurring could reach 100% for rainfall only events and 33% for tidal only events, depending on the region. While compound events of both high rainfall and high tide were rare, when seen in Virginia Beach, the probability of insurance claims being made during these events far exceeded the probability that would be expected if rainfall and tide were independent, showing how compound events in this region exacerbate flood impacts. Additionally, analysis of 110 heavy rainfall events showed that crowdsourced PWSs, can better capture rainfall extremes associated with insurance claims due to their higher spatial density compared to federal agency rainfall networks. This suggests that the PWS networks, once quality controlled, can offer greater insights into which rainfall events are likely to contribute to insurance claims. These region-specific findings and the general methodology presented in this study can benefit multiple stakeholders including researchers, risk management officials, insurers as well as the general public in understanding the impacts of rainfall, tidal, and compound flooding, along with the value of crowdsourced data in assessing flood risk.

COMPOUND URBAN COASTAL FLOOD MODELING: INTEGRATING TIDE, WAVES, PRECIPITATION AND HYDRAULIC INFRASTRUCTURE

Compound coastal flooding considers the joint impacts of marine and hydrologic interactions and has recently been identified as an international research priority. Along the US West Coast, winter storms often bring high marine water levels along with energetic waves and precipitation. Hydrodynamic models have been widely used to estimate flood impacts, including extreme estuarine water levels in compound events (e.g., riverine discharge-tide-storm surge interactions), and produced satisfactory results. However, few studies further consider overland flow routing and high-resolution flood mapping in highly urbanized, low-lying coastal areas. Here, an integrated Delft3D-FM based numerical modeling framework is used to explicitly resolve multi-pathway flood processes (i.e., high marine water levels, waves overtopping, precipitation) and infrastructure (e.g., seawalls, storm drains, artificial dunes).

Spatial-temporal changes of compound temperature-humidity extremes in humid subtropical high-density cities: An observational study in Hong Kong from 1961 to 2020

In the humid subtropics, rising temperatures can cause higher humidity via enhanced evaporation which exacerbates heat-related health problems. This study uses multi-station observational data to reveal the spatial-temporal changes of compound temperature-humidity extreme events in Hong Kong during 1961–2020. Based on the 90th and 10th percentiles of temperature and specific humidity, four types of compound events were identified, i.e., Compound Hot and Wet (CHW), Hot and Dry (CHD), Cold and Wet (CCW), and Cold and Dry (CCD) events. Over the past six decades, there has been a significant increase of CHW (+3.45 events/decade) and decrease of CCD (−3.00 events/decade). The greatest increase of CHW was observed during the warm period of the 2010s (+4 events/year/month). Meanwhile, the trends of CHD and CCW were less evident. Spatially, more frequent compound events (especially those with high humidity (CHW and CCW)) were observed in built-up areas compared to rural areas, while the intensity of these events remained similar. The results imply that both regional climate and urban factors contribute to the increase of extreme hot and humid weather. The study generalizes mechanisms for these spatial-temporal changes, and discussed implications for compound extremes management in Hong Kong and other similar cities.

Assessment of changes in severity of compound drought and saltwater intrusion events based on a multi‐index approach in Pearl River estuary

AbstractGlobal warming alters the inherent variability of climate variables and induces more frequent extremes of hydroclimatic compound events with substantial impacts. The concurrence of hydrological drought and saltwater intrusion in the estuary can have devastating effects on agricultural production, water security, and ecological health. In this study, the compound drought and saltwater intrusion extreme indices, including the Blend Drought and Saltwater intrusion Index (BDSI), the Compound drought and Saltwater intrusion Index (CDSI) and the Standardized Drought and Saltwater intrusion Index (SDSI), were constructed to monitor compound extremes in the critical zone of Pearl River Estuary during the dry season from 1999 to 2016. The results reveal that the three compound indices can effectively depict different aspects of compound drought and saltwater intrusion extreme events in the critical zone of Pearl River Estuary. Among the three indices, the SDSI performed best in depicting compound drought‐saltwater intrusion events, while the BDSI outperformed the other indices in depicting high value of Standardized Runoff Index (SRI) and Standardized Saltwater intrusion Index (SSI), and the CDSI outperformed the other indices in depicting low values of SRI and SSI. Using those developed compound indices, we found that the frequency of abnormal and moderate compound drought‐saltwater intrusion events increased from 9.26% to 12.03% during the period of 1999–2016, while severe, extreme and exceptional compound drought‐saltwater intrusion events were rare.

Understanding changes in heat waves, droughts, and compound events in Yangtze River Valley and the corresponding atmospheric circulation patterns

Heat waves, droughts, and compound drought and heat waves (CDHWs) have received extensive attention because of their disastrous impacts on agriculture, ecosystems, human health, and society. Here, we computed the heat wave magnitude index (HWMI), drought magnitude index (DMI), and compound drought and heat wave magnitude index (CDHMI) for Yangtze River Valley (YRV) from July to August during 1961–2022. We compared the large-scale atmospheric circulation characteristics of different extreme events based on these indexes. The results show that the positive center with sink motion in East Asia provides a favorable circulation background for heat wave events. Drought events are mainly affected by the zonal wave train dominated by a significant negative anomaly in Siberia and a high-pressure anomaly upstream, and a anticyclonic water vapor with strong divergence over the Yangtze River basin. During CDHW events, both anomalous systems that affect heat waves and droughts appear and strengthen simultaneously. Specifically, in the middle and upper troposphere, the positive height anomaly center in YRV expands abnormally, and the “+–+” wave train over the northern 50° N region of East Asia becomes more obvious. Therefore, the positive anomaly and water vapor anomaly brought by the two circulation patterns at different latitudes are superimposed over the YRV, leading to severe CDHWs. At the same time, the warm positive eddy center and cold negative eddy center in high latitudes exhibit more stable positive pressure features, which are conducive to the persistent development and strengthening of CDHWs. In addition, the anomalous warm sea surface temperature in western Pacific moderating the favorable circulation patterns may also promote the occurrence of CDHWs in the YRV during the same period.

Correcting biases in regional climate model boundary variables for improved simulation of high-impact compound events

Although climate models have been used to assess compound events, the combination of multiple hazards or drivers poses uncertainties because of the systemic biases present. Here, we investigate multivariate bias correction for correcting systemic bias in the boundaries that form the inputs of regional climate models (RCMs). This improves the representation of physical relationships among variables, essential for accurate characterization of compound events. We address four types of compound events that result from eight different hazards. The results show that while the RCM simulations presented here exhibit similar performance for some event types, the multivariate bias correction broadly improves the RCM representation of compound events compared to no correction or univariate correction, particularly for coincident high temperature and high precipitation. The RCM with uncorrected boundaries tends to produce a negative bias in the return period of these events, suggesting a tendency to over-simulate compound events with respect to observed events.

Multi‐index characterization of compound dry hot events in India

AbstractCompound dry hot events (CDHEs), where hot events and droughts coexist, have received a lot of attention lately due to their catastrophic effects on the economy, environment and human health. In this study, we use two CDHE indices, the Standardized Compound Event Indicator (SCEI) and the Standardized Dry and Hot Index (SDHI), to assess changes in CDHE characteristics (severity, frequency, spatial extent) over the historical past and future CMIP6 simulations across the Indian subcontinent. To understand the role of the drought index selected on CDHE characterization two drought indices namely the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) are employed in the calculation of the CDHE indices. Further, the role of climatic oscillations such as El Nino Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Equatorial Indian Ocean Monsoon Oscillation and Indian Ocean Dipole in modulating CDHE characteristics have also been explored. Results show that SPI and SPEI based CDHE indices exhibit contrasting trends in northern India, while similar trends are observed in southern India in the historical past. Also, more frequent, extended, and severe CDHEs are reported by CDHE indices calculated using SPEI than by SPI. Temperature is found to be the dominant factor contributing to increases in CDHEs in the recent past and ENSO phases significantly modulate the severity and frequency of CDHE events in India. CMIP6 simulations generally report an increase in CDHE events for a 3°C global warming scenario. Overall, our findings show that the choice of the drought index has a greater impact on CDHE characterization than the choice of the CDHE index itself. Results from this study provide useful information towards understanding the risk of CDHEs in India under global warming and urge for the development and implementation of adaptation and mitigation measures.

Compound heatwave and drought hotspots and their trends in Southeast Australia

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.

Hot and dry compound events in South America: present climate and future projections, and their association with the Pacific Ocean

Compound hot and dry events can cause greater impacts than those generated by individual extreme events. Understanding the physical mechanisms that lead to their development is particularly important for an early warning. The aim of this study is to assess the ability of global climate models (GCMs) to simulate hot/dry compound events in South America (SA) during the historical period 1979–2014, in comparison with observational and reanalysis datasets. Additionally, this work seeks to investigate the potential changes in these events under two future climate scenarios for the period 2065–2100. Furthermore, we analyze the spatial patterns of sea surface temperature anomalies (SSTA) in the Pacific Ocean associated with these events in tropical and extratropical SA. In the historical period, reanalysis tends to overestimate the number of hot/dry events, while the ensemble median of GCMs performs better than the individual ones. The future projections under the high emissions scenario show longer heat waves, but a low model agreement about the number of compound events in tropical SA. For southern SA, an increase in the annual frequency of compound events is projected, and more than two hot/dry events per year are expected to occur relative to the 1979–2014 baseline. Finally, we find that compound events in tropical SA are favored during the El Niño phase, even though two other SSTA patterns have gained prominence in recent years. In southern SA, hot/dry events are associated with the negative phase of the Pacific Decadal Oscillation and the La Niña phase.