High Temperature Days Research Articles

Association between heat exposure and Kawasaki disease: A time-stratified case-crossover study

Nationwide studies investigating the association between daily mean temperature and Kawasaki disease are lacking. This study aimed to examine the association between ambient temperature and Kawasaki disease by utilizing daily data from nationwide administrative claims databases. The daily number of Kawasaki disease patients younger than 15 years old, who were hospitalized from 2011 to 2022, was extracted from the nationwide administrative claims database of hospitalizations in Japan. Daily mean temperature data and relative humidity data were obtained from the Japan Meteorological Agency. Since the exposure of interest includes heat, hospitalizations during the five warmest months (May through September) were used for analysis. A time-stratified case-crossover study with conditional quasi-Poisson regression analysis was used to estimate the relative risk (RR) of weather exposure for Kawasaki disease hospitalization with a lag of 0–5 days by prefecture. Relative humidity was included in the model simultaneously to control for its potential confounding effect. Random-effects meta-analysis was used to estimate pooled RRs. There was a total of 48,784 cases of Kawasaki disease hospitalization during the study period, of which 87.9% were under 5 years of age. Exposure to high daily mean temperatures was associated with an increased risk of hospitalization for Kawasaki disease. Specifically, exposure to extreme high daily mean temperatures (99th percentile high temperature) was associated with higher risk of hospitalization by 33% (RR 1.33, 95% confidence interval (CI):1.08, 1.65). Similar results were obtained from sensitivity analysis. Future research should elucidate the mechanisms by which high temperature is associated with hospitalization for Kawasaki disease.

Relationship between urban traffic crashes and temporal/meteorological conditions: understanding and predicting the effects

Urban traffic accidents pose significant challenges to public safety and transportation management. Previous studies have revealed that temporal and meteorological factors are the key contributors to accident rate. Besides the inconsistent observations or lack of exploration in some aspects such as snowfall, fog, wind and daily temperatures, it has been shown that these factors are essentially entangled. Furthermore, existing methodologies of analysis or prediction have been limited to relative risk or traditional models. Hence, this study is centered on understanding the detailed correlations between temporal and meteorological factors and accident rate of two types of crashes – moving vehicle and fixed-object crashes using the traffic accident data from Dalian. Further, by incorporating a diverse set of the features, a prediction model leveraging the random forest algorithm is proposed and proved effective in anticipating accident occurrences on the district level. The feature importance analysis has shown that time period and factors such as holiday, temperature and season are most important factors. The rate is higher on working days and in spring, and collisions of both types peak at 6–7 am. When the highest daily temperature is 27 °C and the lowest is 20 °C or -8 °C, the incidence is relatively higher. On the basis, the recommendations are aimed at optimizing transportation systems, mitigating accident risks, and enhancing public safety in urban environments.

Source apportionment of Volatile Organic Compounds (VOCs) in the South Coast Air Basin (SoCAB) During RECAP-CA

Ozone (O3) concentrations in the South Coast Air Basin (SoCAB) surrounding Los Angeles remain at unhealthy levels despite multiple decades of control programs designed to reduce emissions of precursor Volatile Organic Compounds (VOCs). Here we report on comprehensive VOC measurements made at Redlands, which has the highest measured O3 concentrations in SoCAB, as part of the Re-Evaluating the Chemistry of Air Pollutants in California (RECAP-CA) field campaign (July–October 2021). Positive matrix factorization (PMF) analysis was applied to identify nine VOC factors. A photochemical chamber model initialized by field measurements was configured with a tagging technique to quantify the VOC factor contributions to O3 formation in Redlands. Biogenic VOCs (BVOCs) made the largest contribution (26.6%) to O3 formation, followed by traffic VOCs (21.2%), volatile chemical products (VCPs) (19%), and plant decomposition (14.9%). High O3 episodes were not driven by increased VOC emissions from any single source, but rather were associated with stagnation events that concentrated VOCs from all sources and high temperature days that enhanced O3 formation efficiency. This implies that VOC controls optimized to reduce O3 concentrations would look similar in both the NOx-limited and VOC-limited regimes that can occur at Redlands. These results suggest that control strategies that reduce VOC and NOx emissions from the on-road vehicle fleet, such as increasing electrification, may yield O3 reductions on days in both the NOx-limited and VOC-limited chemical regimes at Redlands.

Distinguishing High Daytime From Nighttime Temperature Effects During Early Vegetative Growth in Cotton

ABSTRACTHigh‐temperature limits early season vegetative growth of cotton, and the physiological response of cotton (Gossypium hirsutum L.) to high daytime or nighttime temperature needs to be explored. The objectives of the current study were to determine (1) plant growth response, (2) physiological contributors to variation in biomass production and (3) mechanisms driving variation in net photosynthetic rate (AN) in response to different combinations of high daytime and nighttime temperatures. Beginning at planting, cotton was exposed to four different growth temperature regimes: (1) optimum (30/20°C day/night), (2) high nighttime (30/30°C), (3) high daytime (40/20°C) and combined high daytime and nighttime (40/30°C) for 4 weeks. Relative to the 30/20°C treatment, plant growth was positively affected by high nighttime temperature and negatively affected by high daytime temperature and combined high day and night temperature. Increased leaf area mainly contributed to increased biomass production in high nighttime temperature; higher nighttime respiration (RN) drove reductions in biomass in combined high daytime and nighttime temperature; and decreased leaf area and AN and increased RN drove reductions in biomass under high daytime temperature alone. AN was not impacted by high nighttime temperature, while decreased under high daytime temperature and increased with combined high daytime and nighttime temperature. Adjustments in leaf traits contributed to increases in AN in combined high daytime and nighttime temperature, and increased photorespiration and respiration contributed to reductions in AN under high daytime temperature. Overall, early season vegetative growth of cotton exhibited differential responses to high daytime and nighttime temperatures.

Exploration of Geographical Environmental Factors Influencing Regional Population Mortality Patterns inChina.

The regional population mortality patterns in China exhibit substantial geographical distribution characteristics. This paper aims to explore the impact and mechanisms of geographical environmental factors on regional population mortality patterns. This study first utilized the data from China's Seventh Population Census to obtain mortality patterns for the 31 provincial-level administrative regions. Subsequently, a functional regression method was employed to explore the geographical environmental driving factors of regional mortality patterns. The study provides a detailed explanation of the mechanisms and marginal contributions of key geographical environmental factors at different age groups. (1) The impact of geographical environmental factors on mortality patterns shows distinct phased characteristics. Mortality patterns before the age of 40 years are hardly influenced by geographical environmental factors, with a noticeable impact beginning at ages 40-69 years and reaching the maximum influence after the age of 70 years. (2) In mortality patterns at ages 40-69 years, average altitude have the most substantial impact, followed by extreme low-temperature days and PM2.5 concentration. In mortality patterns at ages 70-94 years, high-temperature days have the greatest influence, followed by the impact of SO2 concentration. (3) In comparisons based on gender, socioeconomic factors, and geographical environmental factors, gender and urban-rural differences have the most significant impact on regional population mortality patterns, followed by the influence of other socioeconomic factors, with geographical environmental factors having a relatively smaller impact.

Future changes in extremes across China based on NEX-GDDP-CMIP6 models

This paper evaluates the NASA Earth Exchange Global Daily Downscaled Projections’ (NEX-GDDP) CMIP6 models’ performance in simulating extreme climate indices across China and its eight subregions for the period 2081–2100 under SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios. The models effectively reproduce the spatial patterns of extreme high temperatures, especially in northern China. They show enhanced capabilities in accurately simulating the maximum daily maximum temperature (TXx) and the number of high temperature days (T35). They improve the cold bias of the TXx index in Northwest China and warm bias in South China. In terms of precipitation, the models demonstrate strong performance, evidenced by significant spatial correlations in total wet day precipitation (PTOT) simulations. They reduce the biases of PTOT and simple daily intensity (SDII) compared to CMIP6 models. Regionally, they enhance PTOT accuracy along southern coasts and in Yunnan, better captures very heavy precipitation days (R20) in the Southwest region, max 5-day precipitation (RX5D) in North China and Southwest region, and SDII in the Northeast region and Yunnan. Under SSP5-8.5 scenario, significant impacts include increased TXx in Northwest China, more heatwave days in Southwest China, and more T35 in South China. Extreme precipitation will become more frequent in South and East China, with the greatest intensity increases in Southwest China (SWC1). North China will see fewest consecutive dry days (CDD) indices, while consecutive wet days (CWD) will prominently rise in SWC1.

Potential processes leading to winter reddening of young Douglas-fir Pseudotsuga menziesii Mirb. Franco. in Europe

Key messageWinter reddening of young Douglas-fir (Pseudotsuga menziesii Mirb. Franco), triggered by large thermal fluctuations in late winter, is a critical problem for European forestry. A literature review identified certain climatic conditions that are characteristic of ‘reddening’ years, including warm daily temperatures, high daily temperature amplitude, low relative humidity, moderate wind speeds, as well as the occurrence of freeze-thaw cycles with cold night temperatures.By describing the triggering environmental and stand factors, we propose three hypotheses for the physiological processes leading to winter reddening, namely (i) hydraulic failure due to winter drought stress, (ii) photo-oxidative stress in shade-acclimated trees, and (iii) early cold deacclimation during warm periods.i) Low soil temperature, by reducing root water uptake, combined with anticyclonic conditions, by increasing water losses, can induce hydraulic failure in the xylem. Hydraulic failure may be further accelerated by night frosts.ii) Winter reddening can occur when low temperature and high irradiance coincide, disrupting photostasis. Overwhelming of winter photo-protection may lead to photodamage and subsequent reddening.iii) Warm periods, by inducing cold deacclimation, make trees susceptible to frost damage.Finally, the three processes may interact under atypical anticyclonic conditions in late winter (e.g. cold or dry soils, warm days, high irradiance and/or freezing nights). Indeed, trees under water stress would develop a higher sensitivity to freezing night and photooxidative stress. We therefore proposed mitigation actions to avoid exposing trees to stressful conditions based on e.g. stand characteristics, understorey vegetation and planting.

The Research Effects of Variable Temperature and Early Strength Agent on the Mechanical Properties of Cement-Stabilized Macadam.

In cold regions with high daily temperature gradients (>20 °C), the durability of cement-stabilized macadam (CSM) base materials is poor and prone to cracking. To effectively reduce the cracking of semi-rigid base layers in cold regions with high daily temperature gradients and extend fatigue life, this study focused on cracking and fatigue characteristics of CSM with a 10% commercial early strength agent (ESA) added by the external mixing method under different curing conditions. The ESA was manufactured by Jiangsu Subote New Materials Co., Ltd. (Nanjing, China). The curing conditions were divided into variable temperature (0-20 °C) and standard temperature (20 °C). CSM curing was carried out through a programmable curing box. The research results indicated that the variable temperature curing conditions reduced the strength and fatigue resistance of CSM and accelerated the modulus attenuation rate of CSM. At the same time, the drying shrinkage of CSM was greater. The temperature shrinkage coefficient and strain of CSM under variable temperature conditions were smaller than those under standard temperature conditions. The effect of variable temperature conditions on the cracking and durability of CSM could not be ignored in cold regions. Compared to standard temperature curing conditions, the indirect tensile strength of CSM reduced by 31.04% under variable temperature conditions, the coefficient of variation increased by 2.97 times, and the discrete type significantly increased. Compared with CSM without ESA, the dry and temperature shrinkage strains of CSM with 10% ESA were reduced by 24.65% and 26.10%, respectively. At a stress level of 0.6, compared to standard temperature curing conditions, the fatigue life of CSM decreased by 97.19% under variable temperature conditions. Under variable temperature conditions, the fatigue life of CSM with 10% ESA increased by 196 times compared to 0% ESA. Adding ESA enhanced the anti-shrinkage cracking, strength, and durability of CSM under variable temperatures. ESA incorporation effectively compensated for the weakened characteristics of CSM under variable temperature conditions. The study proposed a practical approach for boosting the durability of CSM in cold environments.

Climate state of the Three Gorges Region in the Yangtze River basin in 2022–2023

Based on daily observation data of the Three Gorges Region (TGR) of the Yangtze River basin and global reanalysis data, the climate characteristics, climate events, and meteorological disasters of the TGR in 2022 and 2023 were analyzed. For the TGR, the average annual temperature for 2022 and 2023 was 0.8 °C and 0.4 °C higher than normal, respectively, making them the two warmest years in the past decade. In 2022, the TGR experienced its warmest summer on record. The average air temperature was 2.4 °C higher than the average, and there were 24.8 days of above-average high temperature days during summer. Rainfall in the TGR varied significantly between 2022 and 2023. Annual rainfall was 18.4 % below normal and drier than normal in most parts of the region. In contrast, the precipitation in 2023 was considerably higher than the long-term average, and above normal for almost the entire year. The average wind speed exhibited minimal variation between the two years. However, the number of foggy days and relative humidity increased in 2023 compared to 2022. In 2022–2023, the TGR mainly experienced meteorological disasters such as extreme high temperatures, regional heavy rain and flooding, overcast rain, and inverted spring chill. Analysis indicates that the abnormal western Pacific subtropical high and the abnormal persistence of the eastward-shifted South Asian high were the two important drivers of the durative enhancement of record-breaking high temperature in the summer of 2022.摘要基于长江三峡地区观测资料和全球再分析资料, 分析了该地区 2022–2023年气候特征, 酸雨状况以及主要天气气候事件. 2022 年和2023年三峡地区平均气温分别较常年偏高0.8 °C和0.4 °C, 是近十年来最暖的两年, 特别是2022年夏季出现破记录极端高温; 2022年三峡地区降水量较常年偏少18.4 %, 2023年降水量转为偏多15.3 %. 在这两年中该地区主要出现了极端高温, 区域性暴雨洪涝, 连阴雨和倒春寒等气候事件. 分析表明, 西太平洋副热带高压和南亚高压协同异常是2022年夏季极端高温维持的两个重要因素.

Volatilomics of Cabernet Sauvignon grapes and sensory perception of wines are affected by canopy side in vineyards with different row orientations

This study aimed to clarify how microclimate diversity altered volatilomics in Cabernet Sauvignon grapes and wines. Four row-oriented vineyards were selected, and metabolites of grapes and wines were determined from separate canopy sides. Results showed that shaded sides received 59% of the solar radiation and experienced 55% of the high-temperature days compared to the exposed sides on average. Grape primary metabolites were slightly affected by the canopy side. Herbaceous aromas were consistently more abundant in grapes and wines from shaded clusters. Heat-stressed canopy sides accelerated terpenoid loss and increased norisoprenoid levels in grapes, while β-damascenone in north-side wines was 13%–32% higher than that in south-side wines of the east-west vineyard. The northeast-southwest vineyard showed the most notable variation in taste and aroma sensory scores, with four parameters significantly different. There were 32 aroma series identified in wines, and banana, pineapple, and strawberry odors were highly correlated with aroma sensory score.

Climatic characteristics of heat wave events (1959–2023) in Jiangxi Province, China

This study investigated the temporal and spatial patterns of heat wave (HW) events in Jiangxi, China. Our analysis is based on the observation data, including daily maximum temperature and daily average air relative humidity from 81 meteorological stations from 1959 to 2023. We also examined the impact of HW events on summer electricity consumption by taking the capital city of Jiangxi, Nanchang, as a case study. The results reveal an overall increase in the frequency of HW events over the past 65 years, with a pronounced increase since 1997, particularly in central and southern Jiangxi. The onset of HW events has generally occurred earlier, while their cessation has been delayed across most areas of Jiangxi Province, resulting in extended HW periods. Economic growth in regions like the Jitai Basin, the Ganfu Plain, and the hilly areas of northeastern Jiangxi has been accompanied by more intense and prolonged HW events. In Nanchang City, the summer electricity load increased by approximately 9% on holidays compared to working days and by about 20% on high-temperature days compared to normal conditions. These insights highlight the need for adaptive strategies to mitigate the impacts of increasing HW occurrences.

Taxonomic diversity and environmental tolerance of cultivable extremophilic bacteria from a high-altitude meltwater pond on Ojos del Salado (Chile).

Earth harbors unique environments where only microorganisms adapted to extreme conditions, known as extremophiles, can survive. This study focused on a high-altitude meltwater pond, located in the Puna de Atacama, Dry Andes. The extremophilic bacteria of this habitat must adapt to a range of extremities, including cold and dry climate, high UV radiation, high daily temperature fluctuations, low-nutrient availability, and negative water balance. This study aimed to explore the taxonomic diversity of cultivable extremophilic bacteria from sediment samples of a desiccated, high-altitude, meltwater pond using media with different organic matter contents and different incubation temperatures. Based on the 16S rRNA gene sequence analysis, the isolates were identified as members of the phyla Actinobacteria, Proteobacteria, and Firmicutes. The most abundant genera were Arthrobacter and Pseudoarthrobacter. The isolates had oligocarbophilic and psychrotrophic properties, suggesting that they have adapted to the extreme environmental parameters of their natural habitats. The results indicate a positive correlation between nutrient concentration and temperature tolerance.

Mechanical performance analysis of double-block ballastless tracks in intercity railways under temperature and train loads

The coupling effect of environmental temperature and moving train loads significantly impacts the mechanical performance of ballastless tracks on intercity railways. To further explore the thermal performance of double-block ballastless tracks (DBBTs) under complex temperature conditions, an initial test was conducted on a 1/4 geometric scale DBBT model across three temperature scenarios. Following the validation of these experimental results, thermal-mechanical coupling models for two types of DBBTs (unitized and longitudinal) on subgrades with two different boundary constraints were developed. These models aimed to examine their mechanical responses under train speeds ranging from 120 km/h to 200 km/h and their interaction with high daily temperatures. The findings indicate that temperature change rates in the track slab are significantly higher than those in the supporting layer, with the stresses in the limiting groove and supporting layer being the highest and lowest, respectively. The relationship between temperature and stress in the track slab follows a second-order quadratic polynomial. Additionally, measured longitudinal displacement results are smaller than theoretical predictions, especially under dropping temperatures. Furthermore, under all three train speeds, both dynamic stress and displacement are higher in the longitudinal DBBT than in the unitized DBBT. The coupling effect of temperature and moving train loads notably increases the dynamic stress in both types of DBBTs, with a more pronounced effect on the dynamic displacement of the longitudinal DBBT compared to the unitized DBBT.

How predictable is the anomaly pattern of summer extreme high-temperature days over Central Asia?

How predictable is the anomaly pattern of summer extreme high-temperature days over Central Asia?

Predictability of the anomaly pattern of summer extreme high temperature days over northern China

Predictability of the anomaly pattern of summer extreme high temperature days over northern China

Daily heat and mortality among people experiencing homelessness in 2 urban US counties, 2015-2022.

High and low daily ambient temperatures are associated with higher mortality in the general population. People experiencing homelessness (PEH) are thought to be particularly vulnerable, but there is almost no direct evidence available. We examined the temperature-mortality association among PEH in 2 populous, urban counties in hot-climate regions of the United States, focusing on heat effects. Study setting was Los Angeles County, CA, and Clark County, NV, which encompass the cities of Los Angeles and Las Vegas, respectively. Outcomes were 2015-2022 deaths among decedents categorized as homeless in county administrative records. We used quasi-Poisson distributed lag nonlinear models to estimate the association of mortality with daily temperatures and with 7-day lagged temperatures, adjusting for day of week, seasonality, and long-term trends. We estimated the minimum mortality temperature and fraction of mortality attributable to temperatures above and below minimum mortality temperature. The association between daily temperature and PEH mortality was skewed towards greater risk at higher temperatures, especially in Clark County. Temperature-attributable mortality equaled 50.1% of deaths in Clark County (95% CI, 29.0-62.8) and 7.0% in Los Angeles County (95% CI, 1.4-12.1). In both counties, most temperature-attributable deaths were attributable to heat rather than cold. In these hot-climate urban counties, our estimates of heat-attributable mortality among PEH were orders of magnitude greater than those reported in prior research on the general population. These results indicate that temperature vulnerability, particularly heat vulnerability, requires stronger public health and policy responses. This article is part of a Special Collection on Environmental Epidemiology.

Urban Vulnerability under the Extreme High Temperatures in the Chengdu-Chongqing Area, Western China

The frequent occurrence of extreme high-temperature events in the summer under global climate change poses a serious threat to Chinese society. An urban vulnerability evaluation system for counties in the Chengdu-Chongqing Area was constructed to calculate the urban vulnerability and distribution characteristics of each district. In this study, a vulnerability-contribution model was used to analyze the types of urban vulnerability in the Chengdu-Chongqing Area. Additionally, combined with the optimal parameter geographic detector (OPGD) model, the main influencing factors and interactions of urban vulnerability were explored. The results show that: ① The urban vulnerability of the Chengdu-Chongqing Area is high in the east and low in the west, with vulnerability degree mostly below the medium degree. ② Exposure contributes more than 50% to severe and general urban vulnerability in the region, while adaptability contributes the highest proportion to mild urban vulnerability, reaching 47.53%. ③ From the factor perspective, the impact ratio of high-temperature days on urban vulnerability is 39.1%, and the interaction between various meteorological factors and social factors produces an enhancement effect, with the highest interaction q-value reaching 0.7863.

Intensified warming suppressed the snowmelt in the Tibetan Plateau

Understanding how hydrological factors interrelate is crucial when examining the impact of climate warming on snowmelt. However, these connections are often overlooked, leading to an unclear relationship between temperature and snowmelt. This study investigates the complex interplay between temperature and snowmelt in the Tibetan Plateau from 1961 to 2020, focusing on how extreme high-temperature events affect the frequency of extreme snowmelt. Using a structural equation model, we detected three temperature-related factors that predominantly influenced snowmelt and extreme snowmelt. The annual average temperature was found to have a significant indirect impact on snowmelt, mediated by changes in snowfall, snow depth and snow cover. By contrast, high-temperature days (daily maximum temperatures exceeding the 90th percentile) and heat waves (at least three consecutive high-temperature days) negatively affected extreme snowmelt directly or indirectly. The direct effect of increasing extreme temperature events was associated with an earlier onset of high-temperature periods, which accelerated snowmelt and shortened the duration of extreme snowmelt periods. Additionally, the reduction in snow cover owing to warming emerged as a main factor suppressing snowmelt and extreme snowmelt frequencies. We also revealed spatiotemporal variations in the temperature‒snowmelt relationship that highly depended on changes in snowmelt patterns. The study elucidated why warming suppresses snowmelt and extreme snowmelt events in the Tibetan Plateau, highlighting the mediating roles of snow-related and phenological factors. The findings will provide scientific support for climate simulation and water management policymaking in alpine regions worldwide.

Nutritional quality of kabuli and desi chickpea in Argentina: Effects of environment

AbstractThe environment to which a crop is exposed during the growing season has a significant impact on seed composition. The objectives of this study were to (1) estimate the contribution of genotype (G), environment (E), and their interaction (G × E) to the agronomic features and seed quality of chickpea and (2) identify climatic variables that significantly affect chickpea nutritional composition. A total of 10 pre‐commercial and commercial cultivars of Cicer arietinum L. were evaluated in 15 environments in Argentina. Average plant height ranged between 44.7 and 55.2 cm, 100‐seed weight was 38 and 27 g, and grain yield was 750 and 1500 kg ha−1 for kabuli and desi chickpea, respectively. The results obtained from the variance component analysis showed statistically significant (p < 0.05) contributions of the effects of G, E, and G × E interaction on the nutritional quality of chickpea seeds. Protein, carbohydrates, and mineral content were mostly affected by E, whereas oil content was G‐dependent. Only tocopherols were affected by G × E interaction. The total phenotypic variance is mostly composed of environmental effects captured during the seed filling period. High mean daily air temperature had a negative effect on carbohydrates and increased protein and mineral content. The fatty acid profile and gamma tocopherol contents were affected by accumulated precipitation and evapotranspiration. Air humidity was negatively correlated with protein content and iodine value. Results from this research are useful for breeders to broaden the genetic background of chickpea genotypes and for farmers to identify climatic conditions that impact grain quality.

On adjustment for temperature in heatwave epidemiology: a new method and toward clarification of methods to estimate health effects of heatwaves.

Defining the effect of exposure of interest and selecting an appropriate estimation method are prerequisite for causal inference. Understanding the ways in which association between heatwaves (i.e., consecutive days of extreme high temperature) and an outcome depends on whether adjustment was made for temperature and how such adjustment was conducted, is limited. This paper aims to investigate this dependency, demonstrate that temperature is a confounder in heatwave-outcome associations, and introduce a new modeling approach to estimate a new heatwave-outcome relation: E[R(Y)|HW=1, Z]/E[R(Y)|T=OT, Z], where HW is a daily binary variable to indicate the presence of a heatwave; R(Y) is the risk of an outcome, Y; T is a temperature variable; OT is optimal temperature; and Z is a set of confounders including typical confounders but also some types of T as a confounder. We recommend characterization of heatwave-outcome relations and careful selection of modeling approaches to understand the impacts of heatwaves under climate change. We demonstrate our approach using real-world data for Seoul, which suggests that the total effect of heatwaves may be larger than what may be inferred from the extant literature. An R package, HEAT (Heatwave effect Estimation via Adjustment for Temperature), was developed and made publicly available.