Intensity Of Heat Waves Research Articles

Heat Waves Coupled with Nanoparticles Induce Yield and Nutritional Losses in Rice by Regulating Stomatal Closure.

The frequency, duration, and intensity of heat waves (HWs) within terrestrial ecosystems are increasing, posing potential risks to agricultural production. Cerium dioxide nanoparticles (CeO2 NPs) are garnering increasing attention in the field of agriculture because of their potential to enhance photosynthesis and improve stress tolerance. In the present study, CeO2 NPs decreased the grain yield, grain protein content, and amino acid content by 16.2, 23.9, and 10.4%, respectively, under HW conditions. Individually, neither the CeO2 NPs nor HWs alone negatively affected rice production or triggered stomatal closure. However, under HW conditions, CeO2 NPs decreased the stomatal conductance and net photosynthetic rate by 67.6 and 33.5%, respectively. Moreover, stomatal closure in the presence of HWs and CeO2 NPs triggered reactive oxygen species (ROS) accumulation (increased by 32.3-57.1%), resulting in chloroplast distortion and reduced photosystem II activity (decreased by 9.4-36.4%). Metabolic, transcriptomic, and quantitative real-time polymerase chain reaction (qRT-PCR) analyses revealed that, under HW conditions, CeO2 NPs activated a stomatal closure pathway mediated by abscisic acid (ABA) and ROS by regulating gene expression (PP2C, NCED4, HPCA1, and RBOHD were upregulated, while CYP707A and ALMT9 were downregulated) and metabolite levels (the content of γ-aminobutyric acid (GABA) increased while that of gallic acid decreased). These findings elucidate the mechanism underlying the yield and nutritional losses induced by stomatal closure in the presence of CeO2 NPs and HWs and thus highlight the potential threat posed by CeO2 NPs to rice production during HWs.

Building resilience to a warming world: A contribution toward a definition of “Integrated Climate Resilience” specific for buildings - Literature review and proposals

With the forecast of a warmer world, with longer, more frequent and more intense heat waves, it becomes essential to have buildings that are resilient to a rapidly warming climate and able to withstand extreme temperature events.This research investigates the concept of buildings’ resilience. Specifically, the article collects definitions of resilient building found in 32 scientific articles referring primarily to thermal aspects and seeks to associate each definition with one of the two interpretations of resilience, namely the engineering and ecological ones, mainly identified within the theory on resilience. This aimed to assess whether there is a predominant and – more importantly – a clear understanding of resilience for buildings, to which extent this concept is well defined and clear, which is a topic that, to the best of our knowledge, no study on thermal resilience of buildings seems to have examined to date.Results showed a significant lack of consensus regarding the interpretation of buildings’ resilience within the selected literature. Such lack of consensus highlights the ongoing confusion about the concept of buildings’ resilience to the threats posed by the current and future climate; what should this concept include concretely? A certain discrepancy also emerged even between the interpretation used to define resilience and that used for its indicators. Furthermore, the available definitions are observed to be rather generic, not specific to buildings and, in any case, it does not seem easy to make them operative. In addition to the literature analysis, the article proposes a tentative approach, which could usefully arrive at an attempted definition of resilience that is specific to buildings and operative. Starting with buildings, the proposed “bottom-up” approach is innovative compared to the prevailing approach in the literature that starts with definitions of ecological and engineering resilience (top-down) instead. Furthermore, the article delivers a couple of considerations to be accounted for when applying the concept of resilience to buildings: the importance of considering not only extreme events but also climate change understood as an increase in average air temperature and the importance of also including the inherent resilience due to the presence of occupants, whose thermal adaptive behavior can mitigate the risk of power outages by making the building less vulnerable to the impacts of climate change.By providing an operational tool for researchers, engineers and planners who intend to strengthen the resilience of the building in the face of climate change, the research contributes to achieving a clearer and shared understanding of how the concept of buildings’ resilience should be declined.

The Effects of Climate Change on Streamflow, Nitrogen Loads, and Crop Yields in the Gordes Dam Basin, Turkey

The Mediterranean region is highly vulnerable to climate change. Longer and more intense heatwaves and droughts are expected. The Gordes Dam in Turkey provides drinking water for Izmir city and irrigation water for a wide range of crops grown in the basin. Using the Soil and Water Assessment Tool (SWAT), this study examined the effects of projected climate change (RCP 4.5 and RCP 8.5) on the simulated streamflow, nitrogen loads, and crop yields in the basin for the period of 2031–2060. A hierarchical approach to define the hydrological response units (HRUs) of SWAT and the Fast Automatic Calibration Tool (FACT) were used to reduce computational time and improve model performance. The simulations showed that the average annual discharge into the reservoir is projected to increase by between 0.7 m3/s and 4 m3/s under RCP 4.5 and RCP 8.5 climate change scenarios. The steep slopes and changes in precipitation in the study area may lead to higher simulated streamflow. In addition, the rising temperatures predicted in the projections could lead to earlier spring snowmelt. This could also lead to increased streamflow. Projected nitrogen loads increased by between 8.8 and 25.1 t/year. The results for agricultural production were more variable. While the yields of poppy, tobacco, winter barley, and winter wheat will increase to some extent because of climate change, the yields of maize, cucumbers, and potatoes are all predicted to be negatively affected. Non-continuous and limited data on water quality and crop yields lead to uncertainties, so that the accuracy of the model is affected by these limitations and inconsistencies. However, the results of this study provide a basis for developing sustainable water and land management practices at the catchment scale in response to climate change. The changes in water quality and quantity and the ecological balance resulting from changes in land use and management patterns for economic benefit could not be fully demonstrated in this study. To explore the most appropriate management strategies for sustainable crop production, the SWAT model developed in this study should be further used in a multi-criteria land use optimization analysis that considers not only crop yields but also water quantity and quality targets.

Amplification of the discrepancy between simplified and physics-based wet-bulb globe temperatures in a warmer climate

The Simplified Wet Bulb Globe Temperature (sWBGT) is widely used in heat stress assessments for climate-change studies, but its limitations have not been thoroughly explored. Building on recent critiques of sWBGT's use for current climate on global scale, this study examines sWBGT's biases using dynamically-downscaled sub-daily climate projections under multiple future emission scenarios. The analysis is aimed at understanding caveats in the application of sWBGT and the uncertainties in existing climate change analysis dependent on sWBGT. Results indicate sWBGT's biases are heavily influenced by local near-surface air temperature, with overestimation of heat stress in East Asia regions, particularly hot and humid areas, due to static assumptions of radiation and wind speed. This overestimation is amplified in warmer climates, leading to exaggerated projected heat stress increases in future. In contrast, underestimations are found for heat stress levels attributed to low wind speeds and strong radiations, such as over the Tibetan Plateau and certain extreme events. Additionally, sWBGT underestimates variability in extreme heatwave events compared to WBGT in both current and future climates, irrespective of overestimation in absolute heatwave intensities. This study emphasizes the limitations of sWBGT, especially in future warmer climates. Importance of sub-daily data for capturing daily maximum heat stress level and reflecting diurnal variations in different components is also discussed. In conclusion, we recommend using Liljegren's model (i.e., physics-based calculation) with high-resolution sub-daily climate data for more accurate outdoor heat stress assessments in climate change studies.

Integrating Remote Sensing and Ground-Based Data for Enhanced Spatial–Temporal Analysis of Heatwaves: A Machine Learning Approach

In response to the urgent global threat posed by human-induced extreme climate hazards, heatwaves are still systematically under-reported and under-researched in Thailand. This region is confronting a significant rise in heat-related mortality, which has resulted in hundreds of deaths, underscoring a pressing issue that needs to be addressed. This research article is one of the first to present a solution for assessing heatwave dynamics, using machine learning (ML) algorithms and geospatial technologies in this country. It analyzes heatwave metrics like heatwave number (HWN), heatwave frequency (HWF), heatwave duration (HWD), heatwave magnitude (HWM), and heatwave amplitude (HWA), combining satellite-derived land surface temperature (LST) data with ground-based air temperature (Tair) observations from 1981 to 2019. The result reveals significant marked increases in both the frequency and intensity of daytime heatwaves in peri-urban areas, with the most pronounced changes being a 0.45-day/year in HWN, a 2.00-day/year in HWF, and a 0.27-day/year in HWD. This trend is notably less pronounced in urban areas. Conversely, rural regions are experiencing a significant escalation in nighttime heatwaves, with increases of 0.39 days/year in HWN, 1.44 days/year in HWF, and 0.14 days/year in HWD. Correlation analysis (p<0.05) reveals spatial heterogeneity in heatwave dynamics, with robust daytime correlations between Tair and LST in rural (HWN, HWF, HWD, r>0.90) and peri-urban (HWM, HWA, r>0.65) regions. This study emphasizes the importance of considering microclimatic variations in heatwave analysis, offering insights for targeted intervention strategies. It demonstrates how enhancing remote sensing with ML can facilitate the spatial–temporal analysis of heatwaves across diverse environments. This approach identifies critical risk areas in Thailand, guiding resilience efforts and serving as a model for managing similar microclimates, extending the applicability of this study. Overall, the study provides policymakers and stakeholders with potent tools for climate action and effective heatwave management. Furthermore, this research contributes to mitigating the impacts of extreme climate events, promoting resilience, and fostering environmental sustainability.

Forecasting personal heat strain under extremely hot environments: Utilizing feature importance in machine learning

Since the frequency and intensity of heatwaves are expected to increase due to global warming, it is crucial to establish a simplified approach to preventing personal heat-related illnesses as occupational hazard under extremely hot environments, by taking into account individual differences in heat strain. In light of this, this study proposed a simplified forecast model for personal heat strain under extremely hot environments by utilizing feature importance in machine learning, focused on enhancing its field applicability. Using the 1417 records gathered from the experiments under extremely hot conditions, the simplified model was developed by utilizing four types of machine learning algorithms (i.e., random forest, extreme gradient boosting, support vector regression, and multi-layer perceptron). As a result, the proposed simplified models with four principal features (i.e., dry-bulb temperature, radiant temperature, relative humidity, and percentage body fat) were found to be the most reliable, resulting in a small difference of 0.047 °C compared to the reference model. Since the principal biometric features can be easily measured by a simple and low-cost body composition test (but not with the physical measurement of personal core body temperature) before they are put into the field, the proposed approach will aid in providing more systematic and efficient management system for proactively preventing personal heat-related illnesses. Furthermore, it is expected that the field applicability of the proposed approach can be continuously enhanced by utilizing the accumulated big data gathered from the field-based living-lab projects over a lengthy period.

Influence of large-scale circulation and local feedbacks on extreme summer heat in Argentina in 2022/23

The summer of 2022/23 in Argentina set a record with ten heatwaves. Here, we compare the synoptic and thermodynamic conditions of the four heatwaves with the largest spatial extent using ERA5 reanalysis data. All heatwaves were associated with mid-level anticyclonic anomalies but with different characteristics: three were quasi-stationary high-pressure systems, while one was transient. We also find that enhanced surface fluxes strongly influenced the daily temperature evolution. Furthermore, we perform an attribution exercise using the analogue technique to measure the contributions of atmospheric circulation, soil moisture, and climate change. For quasi-stationary events, the main contribution came from the circulation (up to 2 °C relative to random flow in the present climate). Conversely, the transient heatwave showed a stronger association with extreme soil moisture deficits, with an estimated increase of ~+1 °C relative to wetter conditions. Climate change has also increased the intensity of heatwaves by +0.5 to +1.2 °C relative to previous decades.

Heatwave exacerbates air pollution in China through intertwined climate-energy-environment interactions

Climate change is increasing the frequency and intensity of heatwaves, raising concerns about their detrimental effects on air quality. However, a role for heatwave-human-environment interactions in air pollution exacerbation has not been established. In the summer of 2022, record-breaking heatwaves struck China and Europe. In this study, we use integrated observational data and machine learning to elucidate the formation mechanism underlying one of the most severe ozone pollution seasons on record in central eastern China, an area that encompasses approximately half of China’s total population and sown land. Our findings reveal that the worsened ozone and nitrogen dioxide pollution resulted from a mismatch between energy demand and supply, which was driven by both heatwaves and energy policy-related factors. The observed adverse heatwave-energy-environment feedback loop highlights the need for the diversification of clean energy sources, more resilient energy structures and power policies, and further emission control to confront the escalating climate challenge in the future.

Effect of heatwaves on daily hospital admissions in Portugal, 2000–18: an observational study

Climate change has increased the frequency, intensity, and duration of heatwaves, posing a serious threat to public health. Although the link between high temperatures and premature mortality has been extensively studied, the comprehensive quantification of heatwave effects on morbidity remains underexplored. In this observational study, we assessed the relationship between heatwaves and daily hospital admissions at a county level in Portugal. We considered all major diagnostic categories and age groups (<18 years, 18-64 years, and ≥65 years), over a 19-year period from 2000 to 2018, during the extended summer season, defined as May 1, to Sept 30. We did a comprehensive geospatial analysis, integrating over 12 million hospital admission records with heatwave events indexed by the Excess Heat Factor (EHF), covering all 278 mainland counties. We obtained data from the Hospital Morbidity Database and E-OBS daily gridded meteorological data for Europe from 1950 to present derived from in-situ observations. To estimate the effect of heatwaves on hospital admissions, we applied negative binomial regression models at both national and county levels. We found a statistically significant overall increase in daily hospital admissions during heatwave days (incidence rate ratio 1·189 [95% CI 1·179-1·198]; p<0·0001). All age groups were affected, with children younger than 18 years being the most affected (21·7% [20·6-22·7] increase in admissions; p<0·0001), followed by the working-age (19·7% [18·7-20·7]; p<0·0001) and elderly individuals (17·2% [16·2-18·2]; p<0·0001). All 25 major disease diagnostic categories showed significant increases in hospital admissions, particularly burns (34·3% [28·7-40·1]; p<0·0001), multiple significant trauma (26·8% [22·2-31·6]; p<0·0001), and infectious and parasitic diseases (25·4% [23·5-27·3]; p<0·0001). We also found notable increases in endocrine, nutritional, and metabolic diseases (25·1% [23·4-26·8]; p<0·0001), mental diseases and disorders (23·0% [21·1-24·8]; p<0·0001), respiratory diseases (22·4% [21·2-23·6]; p<0·0001), and circulatory system disorders (15·8% [14·7-16·9]; p<0·0001). Our results provide statistically significant evidence of the association between heatwaves and increased hospitalisations across all age groups and for all major causes of disease. To our knowledge, this is the first study to estimate the full extent of heatwaves' impact on hospitalisations using the EHF index over a 19-year period, encompassing an entire country, and spanning 25 disease categories during multiple heatwave events. Our data offer crucial information to guide policy makers in effectively and efficiently allocating resources to address the profound health-care consequences resulting from climate change. None.

Surface heat fluxes at coarse blocky Murtèl rock glacier (Engadine, eastern Swiss Alps)

Abstract. We estimate the surface energy balance (SEB) of the Murtèl rock glacier, a seasonally snow-covered permafrost landform with a ventilated coarse blocky active layer (AL) located in the eastern Swiss Alps. We focus on the parameterisation of the turbulent heat fluxes. Seasonally contrasting atmospheric conditions occur in the Murtèl cirque, with downslope katabatic jets in winter and a strongly unstable atmosphere over the heated blocky surface in summer. We use a novel comprehensive sensor array both above the ground surface and in the coarse blocky AL to track the rapid coupling by convective heat and moisture fluxes between the atmosphere, the snow cover, and the AL for the time period September 2020–September 2022. The in situ sensor array includes a sonic anemometer for eddy-covariance flux above-ground and sub-surface long-wave radiation measurements in a natural cavity between the AL blocks. During the thaw seasons, the measurements suggest an efficient (∼ 90 %) export of the available net radiation by sensible and latent turbulent fluxes, thereby strongly limiting the heat available for melting ground ice. Turbulent export of heat and moisture drawn from the permeable AL contributes to the well-known insulating effect of the coarse blocky AL and partly explains the climate resiliency of rock glaciers. This self-cooling capacity is counteracted by an early snow melt-out date, exposing the low-albedo blocky surface to the intense June–July insolation and causing reduced evaporative cooling due to exacerbated moisture scarcity in the near-surface AL during dry spells. With climate change, earlier snowmelt and increased frequency, duration, and intensity of heat waves and droughts are projected. Regarding the parameterisation of the turbulent fluxes, we estimated the year-round turbulent fluxes using a modified Louis (1979) scheme. The monthly SEB is closed within 20 W m−2 except during the snowmelt months and under katabatic drainage winds in winter. Detected sensible turbulent fluxes from nocturnal ventilation processes, although a potentially important ground cooling mechanism, are within our 20 W m−2 uncertainty because nighttime wind speeds are low. Wintertime katabatic wind speeds needed to be scaled to close the SEB, which hints at the limits of parameterisations based on the Monin–Obukhov similarity theory in complex mountain terrain and katabatic drainage winds. The present work contributes to the process understanding of the SEB and climate sensitivity of coarse blocky landforms.

Impact of Recent Heat Wave on Public Health in Bangladesh

Bangladesh, a country already grappling with a challenging climate, recently experienced a severe heat wave. This study investigates the impact of this heat wave on public health. We conduct a comprehensive literature review to understand the established health risks associated with heat waves. Next, we describe the methodology employed for data collection and analysis. This includes gathering data on hospital admissions, emergency department visits, and mortality rates during the heat wave period compared to historical controls. Additionally, we explore sociodemographic factors that might have exacerbated health risks. Statistical analysis will be performed to identify correlations between heat wave intensity and health outcomes. The findings will be presented, highlighting the prevalence of heat-related illnesses, vulnerable populations, and potential long-term health consequences. Finally, the study will discuss limitations and propose recommendations for future heat wave preparedness and response strategies in Bangladesh.

Determination of heat wave definition temperatures in Spain at an isoclimatic level: time trend of heat wave duration and intensity across the decade 2009–2018

BackgroundIn line with WHO guidelines for the implementation of public health prevention plans targeted at the impacts of high temperatures, a heat wave definition temperature (Tthreshold) was calculated for 182 so-called “isoclimatic zones” (IZ) in Spain. As the dependent variable for determining this Tthreshold, we analysed daily all-cause mortality data (ICD-10: A00-R99) for each IZ across the period 2009–2018. The independent variable used was the mean value of the maximum daily temperature of the summer months recorded at meteorological observatories in each IZ. We used Box–Jenkins models to ascertain mortality anomalies, and scatterplots to link these anomalies to the temperatures at which they occurred, thereby determining the Tthreshold for each IZ. We then calculated how many heat waves had occurred in each IZ, as well as their intensity, and analysed their time trend over this period.ResultsThe results showed that in 52.5% of the IZ, the percentile of the maximum temperatures series of the summer months to which Tthreshold corresponded was below the 95th percentile of the meteorological heat wave definition in Spain: indeed, it only coincided in 30.7% of cases. The geographical distribution of these percentiles displayed great heterogeneity as a consequence of the local factors that influence the temperature–mortality relationship. The trend in the number of heat waves analysed indicated an overall increase in Spain at a rate of 3.9 heat waves per decade, and a similar rise in mean annual intensity of 9.5 °C/decade. These time-trend values were higher than those yielded by analysing the trend in meteorological heat waves based on the 95th percentile.ConclusionsThe results obtained in this study indicate the need to use a heat wave definition based on epidemiological temperature–mortality studies, rather than on values based on meteorological percentiles. This could be minimising estimated health impacts in analyses of future impacts attributable to heat.

Heat Stress in India: A Review

Global warming and climate changes have increased the frequency and intensity of heat waves globally as well as in India. The morbidity and mortality of heat stress are under-reported in India. This review was conducted to identify the studies which have reported morbidity and mortality in India and synthesise evidence on the impact of heat stress in the country. Authors identified 373 studies from PubMed and Embase. After removing duplicates and screening for inclusion criteria, 17 articles were selected for the review. Nine articles reported the mortality of heat stress in India, whereas seven articles reported the morbidity. All the studies reported increased mortality due to extreme heat. Eight studies reported excess mortality, which ranged from 5.6% in a study in Varanasi to as high as 43.1 % in Ahmedabad. The studies that have reported morbidity highlight elderly individuals, pregnant women and neonates as the vulnerable population. The discussion focuses on the preventive strategies, heat action plans and primary healthcare reforms needed to manage heat-related illness. Prioritising and focussing on heat-related illness can prevent mortality as well as increase the productivity of the workforce and improve the economy of the country.

Contrasting heat tolerance of evergreen and deciduous urban woody species during heat waves

Abstract The increasing frequency and intensity of heat waves caused significant damages to urban woody species, and the different leaf structures between evergreen and deciduous species may be closely related to leaf heat tolerance. However, whether the different leaf structural traits of evergreen and deciduous plants contribute to their different responses under heat waves is still unclear. During the record‐breaking and long‐lasting 2022 summer heat waves in China, we investigated the relationships between leaf thermal indices and leaf structural traits of 36 urban woody species in four cities along the Yangtze River. We found that all the four thermal indices were significantly but weakly related with leaf damage status. The critical temperature that causes the initial 15% damage to photosystem II (Tcrit) may serve as a sensitive measure of heat tolerance. Evergreen species suffered less leaf damage during the heat waves and exhibited higher leaf heat tolerance, thicker leaves than deciduous species. Tcrit was significantly correlated with leaf mass per area, leaf thickness and thickness of spongy tissue. Synthesis. Urban woody species with higher Tcrit, leaf mass per area and leaf thickness tend to be more tolerant to heat stress. This study provides insights for predicting leaf heat tolerance of urban woody plants in subtropical China and their physiological and ecological responses to severe heat waves. Read the free Plain Language Summary for this article on the Journal blog.

The risk of concurrent heatwaves and extreme sea levels along the global coastline is increasing

Concurrent heatwaves and extreme sea levels could pose a serious threat to coastal communities under climate change; however, the spatiotemporal characteristics and dynamic evolution of them along global coastline remain poorly understood. Here, we use reanalysis datasets and model projections to assess historical and future changes in global concurrent heatwaves and extreme sea levels. We find that 87.73% of coastlines experienced such concurrent extremes during 1979–2017. There is an average increase of 3.72 days in the occurrence during 1998–2017 compared to 1979–1998. A one-percentile increase in heatwave intensity is associated with a 2.07% increase in the likelihood of concurrent extremes. Global coastlines are projected to experience 38 days of concurrent extremes each year during 2025–2049 under the highest emission scenario. The weakening of geopotential height associated with a surface low-pressure system may serve as an important indicator for the occurrence of extreme sea levels during heatwaves.

Negative synergistic effects of drought and heat during flowering and seed setting in soybean

Rising intense heat waves combined with lower precipitations are the new norms of current global scenarios. These altered climatic conditions negatively impact soybean yield potential and quality. Ten soybean cultivars were subjected to four different growing conditions: control, drought, heat, and combined drought and heat to understand the physiological, yield, quality and molecular changes. Stomatal conductance was reduced by 62% and 10% under drought and heat, respectively. This reduction was further exacerbated to 93% when exposed to combined stress. The highest canopy temperature was recorded at +8 °C with combined stress treatment, whereas drought and heat exhibited +2 °C and +5.4 °C, respectively. Furthermore, combined stress displayed a more pronounced negative impact on greenness-associated vegetative index; the gene expression analysis further corroborated these findings. Each degree Celsius increase in temperature during flowering and seed-filling reduced seed weight by approximately 7% and 4% with and without drought, respectively. The seed protein increased under drought, whereas the oil showed a converse trend under drought and combined stresses. Most physiological and yield traits showed no significant correlations between control and individual or combined stress. This suggests that selecting crops for combined stress tolerance may not be appropriate based on nonstress or individual stress performance. Thus, incorporating combined stress-resilient traits into elite soybean cultivars could significantly boost soybean production under hot and dry climatic conditions.

Diverse marine heatwave intensity trends in the marginal seas of China

Diverse marine heatwave intensity trends in the marginal seas of China

Human adaptation to heat in the context of climate change: A conceptual framework

Climate change is causing serious damage to natural and social systems, as well as having an impact on human health. Among the direct effects of climate change is the rise in global surface temperatures and the increase in the frequency, duration, intensity and severity of heat waves. In addition, understanding of the adaptation process of the exposed population remains limited, posing a challenge in accurately estimating heat-related morbidity and mortality. In this context, this study seeks to establish a conceptual framework that would make it easier to understand and organise knowledge about human adaptation to heat and the factors that may influence this process. An inductive approach based on grounded theory was used, through the analysis of case studies connecting concepts. The proposed conceptual framework is made up of five components (climate change, vulnerability, health risks of heat, axes of inequality and health outcomes), three heat-adaptation domains (physiological, cultural and political), two levels (individual and social), and the pre-existing before a heat event. The application of this conceptual framework facilitates the assistance of decision-makers in planning and implementing effective adaptation measures. Recognizing the importance of addressing heat adaptation as a health problem that calls for political solutions and social changes. Accordingly, this requires a multidisciplinary approach that would foster the participation and collaboration of multiple actors for the purpose of proposing effective measures to address the health impact of the rise in temperature.

Impact of heat islands vs. city greening: Real-time monitoring and modeling of drinking water temperature in the city of Montreal in Canada

Urbanization increases the land surface temperature through surface mineralization, adversely affecting vegetation and enhancing the urban heat island (UHI) effect. Global climate change has intensified this warming effect with more frequent and intense heatwaves during hot seasons. While these transformations influence soil temperature, their consequences on drinking water temperature within the drinking water distribution system (DWDS) remains poorly understood. Literature proposes to increase pipe burial depths to mitigate drinking water heating during summer. In this study, we monitored drinking water temperatures in a DWDS in Montreal, Canada with deeply buried pipes (average 1.8 m) during the summer of 2022, focusing on two contrasting zones in terms of UHI and green coverage. Monitoring revealed a 8°C heating effect compared to the water treatment plant, attributed to low green coverage and anthropogenic heat. Conversely, the greener zone exhibited cooler drinking water temperatures, reaching a maximum cooling effect of 8°C as compared to the temperature at the exit of the water treatment plant. Utilizing a soil and water temperature model, we predicted drinking water temperatures within the DWDS with acceptable accuracy. Soil temperature modeling results aligned well with measured water temperatures, highlighting DWDS water temperature approaching its surrounding soil temperature fairly quickly. Despite heatwaves, no immediate correlation emerged between air temperature records and measured water temperatures, emphasizing soil temperature as a superior indicator. An increase in water age displayed no correlation with an increase in measured water temperature, underscoring the dominant influence of UHI and green coverage on water temperature. These findings highlight the cooling advantages of green spaces during summer, providing valuable insights for sustainable urban planning.

Are longer and more intense heatwaves more prone to extreme precipitation?

Simultaneous/sequential occurrence of multiple extreme climate events has the tendency to inflict greater damage compared to isolated extreme climate events. The exploration of simultaneous or continuous extreme events holds profound implications for disaster risk prevention. Therefore, we identified the compound heatwaves and extreme precipitation events (CHP, extreme precipitation events following heatwaves) in China based on ERA5 data. Then, the individual extreme events and compound events were undertaken through event coincidence analysis. Furthermore, the atmospheric background of individual extreme events and compound extreme events was further investigated. The results show that the CHP events with an increasing trend mainly occurred in northern China and northeastern the Qinghai-Tibet Plateau (QTP). Notably, after the year 2000, the time interval of extreme precipitation in CHP events was significantly shortened. In July and August, the trigger coincidence rate of extreme precipitations by heatwaves occurred higher and extreme precipitation events following heatwaves accounted for 40%. Moreover, Extreme precipitation is more likely to occur after a longer duration and higher intensity heatwave in the QTP. Convective effective potential energy (CAPE) and relative humidity manifest a considerable increase during the heatwave duration, greatly augmenting the risk of extreme precipitation events. In addition, the frequency of CHP events is higher in northern and northeastern China during El Niño years. While it predominantly concentrates in the northeast region in La Niña years.