Heat Wave Days Research Articles

Summer Heatwaves in Southeastern Australia

AbstractHeatwaves in southeastern Australia have characteristic weather patterns that are well understood but are outnumbered by days with similar synoptic‐scale patterns that are not heatwaves. Accordingly, the aim of this study is to identify the key differences between heatwave and non‐heatwave days from 40 years of reanalysis data. A synoptic climatology of seven weather states was constructed by ‐means cluster analysis. Four of these states account for more than 80% of heatwave days across south‐and‐central eastern Australia. Moreover, the spatial maxima in the frequency of the heatwave days are distinct and geographically separated. Heatwave days have a stronger upper anticyclone or ridge that has propagated further equatorward in comparison with non‐heatwave days. The air upstream of the ridge is more humid on heatwave days, whereas downstream of the ridge the air is much drier. These dry anomalies are co‐located with midtropospheric subsidence and the moist anomalies with ascent, and their respective spatial distributions are consistent with regions of adiabatic warming and latent heating identified in recent studies of southeast Australian heatwaves. The corresponding vertical motion on non‐heatwave days is weaker and shifted further poleward. Southeast Queensland heatwave days exhibit increased baroclinicity over the Australian Subtropics and reduced rainfall over Queensland. Further south and west, heatwave days are associated with more amplified Rossby waves and increased rainfall over the Australian Tropics. Anticyclonic Rossby wave breaking is greatly enhanced on heatwave days south of 30°S. For every day in each of these four weather states, the 3‐day‐mean maximum temperature in the region of peak heatwave day frequency is positively correlated with 500 hPa geopotential height anomalies on the equatorward flank of the cluster‐mean upper ridge. These findings underline the importance of equatorward Rossby wave propagation in the dynamics of southeast Australian heatwaves.

Extreme weather characteristics and influences on urban ecosystem services in Wuhan Urban Agglomeration

In recent years, there has been a pronounced increase in the frequency of extreme weather events. To comprehensively examine the impact of extreme weather on ecosystem services within the Wuhan Urban Agglomeration (WUA), this study utilized meteorological station data, the Mann-Kendall (MK) test, and the Standardized Precipitation-Evapotranspiration Index (SPEI) to quantify the variation trends in heatwaves (HW) and droughts from 1961 to 2020. Then the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model was employed to evaluate and compare the differences in water yield and climate regulation ecosystem services under various HW, droughts, and HW-drought combination scenarios. The results show that over the past 60 years, the temperature, duration, and frequency of HW have significantly increased in the WUA. Specifically, the highest HW temperature, total HW days, HW frequency, and average HW temperature showed changing trend of +0.17 ℃/decade, +1.4 day/decade, +0.19 event/decade, and +0.07 ℃/decade, respectively. The year 2000 was identified as a mutation year for HW, characterized by increased frequency and heightened severity thereafter. The SPEI value exhibited an insignificant upward trend, with 1980 marked as a mutation year, indicating a decreasing trend in drought occurrences after 1980. Heatwaves have a weakening effect on both water yield and climate regulation services, while drought significantly weakened water yield and had a relatively modest effect on climate regulation. During HW-drought composite period, the average monthly water yield showed a notable discrepancy of 60 mm compared to humid years. Besides, as heatwaves intensify, the area of low aggregation for ecosystem services expands, whereas the area of high aggregation decreases. This study provides a preliminary understanding of the impact of urban extreme weather on urban ecosystem services under changing climatic conditions.

How heatwaves affect short-term emergency hospital admissions due to bacterial foodborne diseases

The coming decades are likely to see of extreme weather events becoming more intense and frequent across Europe as a whole and around the Mediterranean in particular. The reproduction rate of some microorganisms, including the bacteria that cause foodborne diseases, will also be affected by these events. The aim of this study was thus to ascertain whether there might be a statistically significant relationship between emergency hospital admissions due to the principal bacterial foodborne diseases (BFDs) and the various meteorological variables, including heatwaves.We conducted a time-series study, with daily observations of both the dependent variable (emergency hospital admissions due to BFDs) and the independent variables (meteorological variables and control variables of chemical air pollution) across the period 2013–2018 in the Madrid Region (Spain), using Generalised Linear Models with Poisson regression, in which control and lag variables were included for the purpose of fitting the models. We calculated the threshold value of the maximum daily temperature above which such admissions increased statistically significantly, analysed data for the whole year and for the summer months alone, and estimated the relative and attributable risks.The estimated attributable risk was 3.6 % for every one-degree rise in the maximum daily temperature above 12 °C throughout the year, and 12.21 % for every one degree rise in temperature above the threshold heatwave definition temperature (34 °C) in summer.Furthermore, different meteorological variables displayed a statistically significant association. Whereas hours of sunlight and mean wind speed proved significant in the analyses of both the whole year and summer, the variables “rain” and “relative humidity”, only showed a significant relationship in the analysis for the whole year.High ambient temperature is a risk factor that favours the increase in emergency hospitalisations attributable to the principal BFDs, with a greater impact being observed on days coinciding with heatwave periods. The results yielded by this study could serve as a basis for implementing BFD prevention strategies, especially on heatwave days.

Temperature exposure and sleep duration: Evidence from time use surveys

The Earth’s climate is projected to warm significantly in the 21st century, and this will affect human societies in many ways. Since sleep is a basic human need and part of everyone's life, the question of how temperature affects human sleep naturally arises. This paper examines the effect of daily mean temperature on sleep duration using nationally representative Hungarian time use surveys between 1976 and 2010. Compared to a day with an average temperature of 5–10 °C, colder temperatures do not influence sleep duration. However, as daily mean temperatures rise, sleep duration starts to strongly decline. The effect of a hot (>25 °C) day is −13.3 minutes, but if preceded by a few other hot days, the effect is even stronger, −24.7 minutes. The estimated sleep loss is especially large on weekends and public holidays, for older individuals, and men. Combining the estimated effects with temperature projections of twenty-four climate models shows that the warming climate will substantially decrease sleep duration. The projected impacts are especially large when taking into account the effects of heatwave days. This study also shows that different groups in society are likely to be affected in significantly different ways by a warming climate.

Impacts of heat and wildfire on preterm birth

BackgroundClimate change continues to increase the frequency, intensity, and duration of heat events and wildfires, both of which are associated with adverse pregnancy outcomes. Few studies simultaneously evaluated exposures to these increasingly common exposures. ObjectivesWe investigated the relationship between exposure to heat and wildfire smoke and preterm birth (PTB). MethodsIn this time-stratified case-crossover study, participants consisted of 85,806 California singleton PTBs (20–36 gestational weeks) from May through October of 2015–2019. Birthing parent ZIP codes were linked to high-resolution daily weather, PM2.5 from wildfire smoke, and ambient air pollution data. Heat day was defined as a day with apparent temperature >98th percentile within each ZIP code and heat wave was defined as ≥2 consecutive heat days. Wildfire-smoke day was defined as a day with any exposure to wildfire-smoke PM2.5. Conditional logistic regression was used to calculate the odds ratio (OR) and 95% confidence intervals (CI) comparing exposures during a hazard period (lags 0–6) compared to control periods. Analyses were adjusted for relative humidity, fine particles, and ozone. ResultsWildfire-smoke days were associated with 3.0% increased odds of PTB (ORlag0: 1.03, CI: 1.00–1.05). Compared with white participants, associations appeared stronger among Black, Hispanic, Asian, and American Indians/Alaskan Native participants. Heatwave days (ORlag2: 1.07, CI: 1.02–1.13) were positively associated with PTB, with stronger associations among those simultaneously exposed to wildfire smoke days (ORlag2: 1.19, CI: 1.11–1.27). Similar findings were observed for heat days and when other temperature metrics (e.g., maximum, minimum) were used. DiscussionHeat and wildfire increased PTB risk with evidence of synergism. As the occurrence and co-occurrence of these events increase, exposure reduction among pregnant people is critical, especially among racial/ethnic minorities.

Surface urban heat island analysis based on local climate zones using ECOSTRESS and Landsat data: A case study of Valencia city (Spain)

Extreme heat events in cities are becoming more intense, frequent and prolonged. The spatiotemporal dynamics of surface temperature are closely related to land cover and atmospheric conditions, especially for urban areas with extensive surface heterogeneity. Two high spatial resolution satellites, ECOSTRESS and Landsat, provide land surface temperature (LST) for a typical Mediterranean climate city, Valencia, Spain. In total of 17 images throughout two heatwaves in the period of July and August from 2022 to 2023 were selected to monitor LST and surface urban heat island (SUHI). The Local Climate Zone (LCZ) scheme and hotspot analysis were applied to analyze the patterns of LST and SUHI during and after the heatwaves. Daytime images show LCZ 2/3/6/8 and LCZ C/E/F exhibit elevated SUHI intensity, meanwhile the LCZ 4, A/B and G have lower SUHI. The SUHI intensity of compact buildings (LCZ 1/2/3), LCZ 8/E/G are significantly higher at night, especially on heatwave days, the SUHI of all types increased by 0.1–0.9 °C. Furthermore, the meteorological parameters were introduced trying to explain the obvious diurnal difference of SUHI during heatwaves. This research serves as a proxy for understanding the spatiotemporal dynamics of SUHI during heatwave events, offering valuable insights for city planners and policymakers to enhance thermal comfortable level and effectively cope with extreme weather.

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.

Evaluating the Impact of Heat Mitigation Strategies Using Added Urban Green Spaces during a Heatwave in a Medium-Sized City

Recognizing the growing trend of the urban population and the undeniable fact of global and regional climate change, it becomes increasingly important to explore how we can improve the livability of our cities not only in the distant future but also in the next few years. A critical aspect of this endeavor involves studying how we can effectively mitigate human heat load in urban areas. In our research, in the case of a medium-sized city (Szeged, Hungary), we examined the effect of surface modifications caused by vegetation on human thermal perception during the day and night of two heatwave days. To achieve this, we used the MUKLIMO_3 micro-scale climate model to simulate the thermal climate of Szeged, while the thermal load was assessed with the perceived temperature calculated by the Klima-Michel model. Our analysis also relied on the local climate zone (LCZ) system to describe the original land cover and the additional urban green spaces in the study area. We scrutinized the effects of added vegetation of different types and densities, as well as the presence of protective forests surrounding the city. Our findings revealed that the effect of the added vegetation can only be detected on the modified surfaces and in their immediate vicinity. Notably, dense urban greenery resulted in up to a 2–3 °C reduction in perceived temperature in certain areas during the daytime, highlighting the profound impact of targeted green space development. In addition, it is crucial to consider the airflow-blocking effect of woody vegetation, which can increase thermal load by 1–3 °C in the areas located in a downwind direction. Therefore, the changing regional climatic conditions (e.g., wind direction) and the development of the right type and location of urban green areas deserve special attention during modern urban planning processes.

Increasing duration of heatwaves poses a threat to oyster sustainability in the Gulf of Mexico

The future of the wild oyster fishery in the northern Gulf of Mexico is largely uncertain due to changing environmental conditions and declining abundance of harvestable oysters. Specifically, rising temperatures can directly impact the physiological thresholds of the eastern oyster (Crassostrea virginica) at all life history stages and alter the narrow ecological niche this oyster occupies. The impact of rising temperatures is likely most pronounced during atmospheric heatwaves, defined as three or more days above the 90th percentile of daily maximum air temperatures, which have been shown to be increasing in frequency. Increasing exposure to high temperature extremes may contribute to and exacerbate an already declining oyster fishery. Critical to fishery health is recruitment i.e., the addition of new harvestable biomass, which is a dynamic process strongly driven by temperature. Here, we examine the relationship between heatwave characteristics and the prediction of poor oyster recruitment, measured as the abundance of post-larval oysters (e.g. spat) below the site-specific median density observed in historically productive oyster fisheries over 46-years (1976 – 2020) in Mobile Bay, Alabama and 21-years (1993 – 2014) in Apalachicola Bay, Florida. We acquired daily maximum air temperature measurements measured over 50 years (1970 – 2020) at weather monitoring stations adjacent to the bays to identify site specific annual heatwave events (maximum yearly air temperature, yearly and consecutive heatwave days, and number of annual heatwaves). Then, years with extreme heatwaves that exceeded the 75th percentile for the 50-year measurements were compared to years with non-extreme heatwave events. Years with extreme total heatwave days and extreme consecutive heatwave days were correlated with low post-larval oyster density. Across both bay systems, if consecutive heatwave days exceeded 11 days, then poor recruitment of oysters occurred 83 % of the time. Extreme heatwave duration as an indicator for poor recruitment has the potential to be a powerful tool for fishery managers to forecast recruitment and inform sustainable oyster harvest based on year-to-year variability in heatwave duration and long-term warming trends. Our findings illustrate how extreme temperatures can exacerbate multiple physiological and ecological stressors resulting in the loss of a keystone species for healthy and resilient coastal ecosystems.

Climatic impacts induced by winter wheat irrigation over North China simulated by the nonhydrostatic RegCM4.7

Quantification of the impact of winter wheat irrigation on the climate and the occurrence of extreme climatic events over North China is crucial for regional adaptation planning. Previous related studies mainly focused on the impact on surface processes; however, few focused on the effects of extreme events using high-resolution nonhydrostatic regional climate models. Here, the 9-km-resolution nonhydrostatic RegCM4.7 was coupled with a crop irrigation scheme and an updated winter wheat irrigation dataset to better simulate irrigation effects. Two experiments were conducted with and without winter wheat irrigation to isolate the effects of irrigation. Results showed that irrigation simulation reduces the model biases in temperature, precipitation, latent heat flux, soil moisture, sensitive heat flux, and top-layer soil moisture. Moreover, it also reduces the bias and increases the correlation with observations obtained in irrigated areas, especially in summer, indicating better representation of irrigation schemes. Winter wheat irrigation tends to cause substantial cooling of the local surface maximum, minimum, and mean air temperatures (by −1.68, −0.34, and −0.79 °C, respectively) over irrigated areas of North China, with the largest changes observed in relation to maximum temperature. Additionally, precipitation is found to increase during spring and summer, which is strongly related to water vapor transport in the lower levels of the atmosphere. Further analyses indicated that the number of annual mean hot days decrease (−13.9 d), whereas the number of both comfort days (+10.2 d) and rainy days (days with total precipitation greater than 1 mm: +6.6 d) increase over irrigated areas, demonstrating beneficial feedback to human perception and agriculture. Fortunately, although the heat wave risk increases (number of annual mean heat wave days: +5.8 d), the impact is limited to small areas within irrigated region. Additionally, no notable change was found in terms of heavy rainfall events and precipitation intensity, which might be an undereastimation caused by the less water use in model simulation. Although winter wheat irrigation does not have notable impact on the climate of the surrounding region, it is an important factor for the local-scale climate.

Risk factors associated with heatwave mortality in Chinese adults over 65 years.

Aging populations are susceptible to heat-related mortality because of physiological factors and comorbidities. However, the understanding of individual vulnerabilities in the aging population is incomplete. In the Chinese Longitudinal Healthy Longevity Survey, we assessed daily heatwave exposure individually for 13,527 participants (median age = 89 years) and 3,249 summer mortalities during follow-up from 2008 to 2018. The mortality risk during heatwave days according to relative temperature is approximately doubled (hazard ratio (HR) range = 1.78-1.98). We found that heatwave mortality risks were increased for individuals with functional declines in mobility (HR range = 2.32-3.20), dependency in activities of daily living (HR range = 2.22-3.27), cognitive impairment (HR = 2.22) and social isolation reflected by having nobody to ask for help during difficulties (HR range = 2.14-10.21). Contrary to current understanding, older age was not predictive of heatwave mortality risk after accounting for individual functional declines; no statistical differences were detected according to sex. Beyond age as a risk factor, our findings emphasize that functional aging is an underlying factor in enhancing heatwave resilience. Assessment of functional decline and implementing care strategies are crucial for targeted prevention of mortality during heatwaves.

The effect of temperature on birth rates in Europe

Using data from 32 European countries for nearly 244 million live births between 1969 and 2021, this paper examines the effects of temperatures on birth rates. The results show that exposure to hot days slightly reduces birth rates five to eight months later, while much stronger negative effects are observed nine to ten months after exposure to hot temperatures. Thereafter, a partial recovery is observed, with slightly increased birth rates. This study also shows that the effect of high-humidity hot days is much stronger than that of hot days with low humidity. Besides, the effect of heatwave days has been found to be more severe than that of hot days that are not preceded by other hot days. This study finds that some adaptation to heat might be expected only in the long run.

Interactive effects of atmospheric oxidising pollutants and heat waves on the risk of residential mortality

ABSTRACT Background The impact of heat waves and atmospheric oxidising pollutants on residential mortality within the framework of global climate change has become increasingly important. Objective In this research, the interactive effects of heat waves and oxidising pollutants on the risk of residential mortality in Fuzhou were examined. Methods We collected environmental, meteorological, and residential mortality data in Fuzhou from 1 January 2016, to 31 December 2021. We then applied a generalised additive model, distributed lagged nonlinear model, and bivariate three-dimensional model to investigate the effects and interactions of various atmospheric oxidising pollutants and heat waves on the risk of residential mortality. Results Atmospheric oxidising pollutants increased the risk of residential mortality at lower concentrations, and O3 and Ox were positively associated with a maximum risk of 2.19% (95% CI: 0.74–3.66) and 1.29% (95% CI: 0.51–2.08). The risk of residential mortality increased with increasing temperature, with a strong and long-lasting effect and a maximum cumulative lagged effect of 1.11% (95% CI: 1.01, 1.23). Furthermore, an interaction between atmospheric oxidising pollutants and heat waves may have occurred: the larger effects in the longest cumulative lag time on residential mortality per 10 µg/m3 increase in O3, NO2 and Ox during heat waves compared to non-heat waves were [−3.81% (95% CI: −14.82, 8.63)]; [−0.45% (95% CI: −2.67, 1.81)]; [67.90% (95% CI: 11.55, 152.71)]; 16.37% (95% CI: 2.43, 32.20)]; [−3.00% (95% CI: −20.80, 18.79)]; [−0.30% (95% CI: −3.53, 3.04)]. The risk on heat wave days was significantly higher than that on non-heat wave days and higher than the separate effects of oxidising pollutants and heat waves. Conclusions Overall, we found some evidence suggesting that heat waves increase the impact of oxidising atmospheric pollutants on residential mortality to some extent.

Fidelity of WRF model in simulating heat wave events over India

The evaluation of Weather Research and Forecasting (WRF) model has been performed for simulating episodic Heat Wave (HW) events of 2015 and 2016 with varied horizontal resolutions of 27 km for the entire India (d01), 9 km for the North West (NW (d02)) and South East (SE (d03)) domain. Study compares the maximum temperature (Tmax) simulated by WRF model, using six different combination of parameterization schemes, with observations from the India Meteorological Department (IMD) during the HW events. Among the six experiments, Exp2 (i.e., combination of WSM6 microphysics (MP) together with radiation parameterization CAM, Yonsei (PBL), NOAH land surface and Grell-3D convective schemes) is found closest to the observations in reproducing the temperature. The model exhibits an uncertainty of ± 2 °C in maximum temperature (Tmax) for both the regions, suggesting regional temperature is influenced by the location and complex orography. Overall, statistical results reveal that the best performance is achieved with Exp2. Further, to understand the dynamics of rising HW intensity, two case studies of HW days along with influencing parameters like Tmax, RH and prevailing wind distribution have been simulated. Model simulated Tmax during 2015 reaches up to 44 °C in NW and SE part of India. In 2016, HW is more prevailing towards NW, while in SE region Tmax reaches upto 34–38 °C with high RH (60–85%). The comparative research made it abundantly evident that these episodic events are unique in terms of duration and geographical spread which can be used to assess the WRF performance for future projections of HW.

Heat wave characteristics: evaluation of regional climate model performances for Germany

Abstract. Heat waves are among the most severe climate extreme events. In this study, we address the impact of increased model resolution and tailored model settings on the reproduction of these events by evaluating different regional climate model outputs for Germany and its near surroundings between 1980–2009. Outputs of an ensemble of six EURO-CORDEX models with 12.5 km grid resolution and outputs from a high-resolution (5 km) WRF (Weather Research and Forecasting) model run are employed. The latter was especially tailored for the study region regarding the physics configuration. We analyze the reproduction of the maximum temperature, number of heat wave days, heat wave characteristics (frequency, duration and intensity), the 2003 major event, and trends in the annual number of heat waves. E-OBS is used as the reference, and we utilize the Taylor diagram, the Mann–Kendall trend test and the spatial efficiency metric, while the cumulative heat index is used as a measure of intensity. Averaged over the domain, heat waves occurred about 31 times in the study period, with an average duration of 4 d and an average heat excess of 10 ∘C. The maximum temperature was only reproduced satisfactorily by some models. Despite using the same forcing, the models exhibited a large spread in heat wave reproduction. The domain mean conditions for heat wave frequency and duration were captured reasonably well, but the intensity was reproduced weakly. The spread was particularly pronounced for the 2003 event, indicating how difficult it was for the models to reproduce single major events. All models underestimated the spatial extent of the observed increasing trends. WRF generally did not perform significantly better than the other models. We conclude that increasing the model resolution does not add significant value to heat wave simulation if the base resolution is already relatively high. Tailored model settings seem to play a minor role. The sometimes pronounced differences in performance, however, highlight that the choice of model can be crucial.

Future Projections of Heat Waves and Associated Mortality Risk in a Coastal Mediterranean City

Climate change has been linked to the escalating frequency, duration, and intensity of heat waves in the Mediterranean region, intensifying health concerns for the general populace. Urban environments face elevated health risks due to concentrated populations and the urban heat island effect, further amplifying nighttime heat conditions. This study aims to project changes in heat wave characteristics and the associated population exposure risk in a large Mediterranean city, Thessaloniki, Greece. High-resolution climate simulations, using the WRF model, were conducted for three 5-year periods (2006–2010, 2046–2050, 2096–2100) under the RCP8.5 emission scenario, covering Thessaloniki with a 2 km grid. By the end of the century, Thessaloniki is projected to experience over 60 annual heat wave days, compared to ~8 in the present climate, while some episodes were found to persist beyond 30 days. The relative risk during heat wave days is expected to rise, which is primarily due to nighttime heat stress. Interestingly, the results indicate that minimum apparent temperature might be a more reliable indicator in predicting heat-related mortality compared to maximum apparent temperature. These findings emphasize the growing importance of informed heat mitigation and adaptation strategies and healthcare preparedness in urban areas facing escalating heat-related health challenges.

Are hotspots and frequencies of heat waves changing over time? Exploring causes of heat waves in a tropical country.

Heat waves significantly impact people's lives and livelihoods and are becoming very alarming and recognized as hot topics worldwide, including in Bangladesh. However, much less is understood regarding recent hotspots, the frequency of heat waves over time, and their underlying causes in Bangladesh. The objective of the study is to explore the current scenario and frequency of heat waves and their possible causes across Bangladesh. The Mann-Kendall and Sen's slope techniques were used to determine seasonal and annual temperature trend patterns of heat wave frequencies. Daily maximum temperature datasets collected from the Bangladesh Meteorological Department (BMD) during 1991-2021 are applied. The frequency of days with Tmax≥ 36°C as the threshold was used to compute different types of heat waves based on the BMD's operational definition. The results show that the mild heat wave (MHW) days followed the subsequent hotspot order: Rajshahi (103) > Chuadanga (79), Ishurdi (60), and Jessore (58), respectively. The frequency of days with Tmax≥36°C was persistence for many days in 2014, especially in the western part of Bangladesh compared to other parts. Similarly, the heat waves condition shown its deadliest event by increasing more days in 2021. The highest increasing trend was identified at the Patuakhali site, with a rate of 0.516 days/year, while the highest decreasing trend was noticed at the Chuadanga site, with a rate of -0.588 days/year. The frequency of days (Tmax≥36°C) is an increasing trend in the south-western part of Bangladesh. The synoptic condition in and around Bangladesh demonstrates that the entrance of heat waves in Bangladesh is due to the advection of higher temperatures from the south/southwest of the Bay of Bengal. The outcomes will guide the national appraisal of heatwave effects, shedding light on the primary causes of definite heatwave phenomena, which are crucial for developing practical adaptation tools.

Excess Mortality Risk Due to Heat Stress in Different Climatic Zones of India.

India is at a high risk of heat stress-induced health impacts and economic losses owing to its tropical climate, high population density, and inadequate adaptive planning. The health impacts of heat stress across climate zones in India have not been adequately explored. Here, we examine and report the vulnerability to heat stress in India using 42 years (1979-2020) of meteorological data from ERA-5 and developed climate-zone-specific percentile-based human comfort class thresholds. We found that the heat stress is usually 1-4 °C higher on heatwave (HW) days than on nonheatwave (NHW) days. However, the stress on NHW days remains considerable and cannot be neglected. We then showed the association of a newly formulated India heat index (IHI) with daily all-cause mortality in three cities - Delhi (semiarid), Varanasi (humid subtropical), and Chennai (tropical wet and dry), using a semiparametric quasi-Poisson regression model, adjusted for nonlinear confounding effects of time and PM2.5. The all-cause mortality risk was enhanced by 8.1% (95% confidence interval, CI: 6.0-10.3), 5.9% (4.6-7.2), and 8.0% (1.7-14.2) during "sweltering" days in Varanasi, Delhi, and Chennai, respectively, relative to "comfortable" days. Across four age groups, the impact was more severe in Varanasi (ranging from a 3.2 to 7.5% increase in mortality risk for a unit rise in IHI) than in Delhi (2.6-4.2% higher risk) and Chennai (0.9-5.7% higher risk). We observed a 3-6 days lag effect of heat stress on mortality in these cities. Our results reveal heterogeneity in heat stress impact across diverse climate zones in India and call for developing an early warning system keeping in mind these regional variations.

Projected changes in heatwaves and its impact on human discomfort over India due to global warming under the CORDEX-CORE framework

Due to climate change, rapid warming and its further intensification over different parts of the globe have been recently reported. This has a direct impact on human health, agriculture, water availability, power generation, various ecosystems, and socioeconomic conditions of the exposed population. The current study thus investigates the frequency and duration of heatwaves, human discomfort, and exposure of the human population to these extremes using the high-resolution regional climate model experiments under two Representative Concentration Pathways (RCP2.6, RCP8.5) over India. We find that more than 90% of India will be exposed to uncomfortable warm nights by the end of the 21st century with the highest rise over western India, Madhya Pradesh (MP), Uttar Pradesh (UP), Punjab, and the Haryana region. States like Odisha, Chhattisgarh, eastern parts of MP and UP, and some parts of J&K will be the worst hit by the intense and frequent heatwaves and human discomfort followed by the densely populated Indo-Gangetic plains under RCP8.5. Strict enforcement of the stringent policies on stabilization of population growth, improvement of local adaptive capacities, and economic status of the vulnerable population along with enforcing effective measures to curb greenhouse gas emissions are important to reduce human exposure to future heat stress. We demonstrate that a proper mitigation-based development (RCP2.6) instead of a business-as-usual scenario (RCP8.5) may help to reduce 50–200 heatwave days, 3–10 heatwave spells, and 10–35% warm nights over the Indian region. Consequently, this can avoid the exposure of 135–143 million population to severe discomfort due to extreme heat conditions by the end of the 21st century.

Spatial characterization of global heat waves using satellite-based land surface temperature

The warming world greatly suffers the increase of frequency, severity and duration of heat wave events, which would cause the significant societal and environmental damages and implications from local to global scales. In order to eliminate the limitations of site observations in accurate spatial extent identification and large scale monitoring, this study tried to investigate global heat waves in 2018 using spatial datasets of land surface temperature (LST) derived from AQUA TIR sensors. A 15-year daily maximum LST dataset was used to identify the hot days and heat wave events using the relative threshold method based on the probability density function analysis of LST sequences, then they were adopted in analyzing spatial patterns of duration, frequency and intensity of heat wave events using heat wave numbers (HWN), the frequency of the appeared heat wave days (HWF) and the amplitude of heat wave impacts (HWA) indices, respectively. Our results indicated that more heat wave events and longer heat wave duration happened in low and middle latitudes under the warmer land surface in 2018 than last decade, especially many heat wave events occurred in the environmentally fragile regions and the dense population area. Urban regions achieved the largest HWA by 45.5 ± 6.9℃. Both annual HWF and HWN highlighted seven hot spot regions influenced by heat waves, and most of them distributed around the latitude 30°N and the latitude 30°S. Extreme heat wave of hot spot regions in the Southern Hemisphere mainly happened in winter and spring in contrast to that in North Hemisphere appeared in summer and autumn. Dry climate could contribute to the occurrence of heat waves, and heat wave indices variations also implied the compound consequences between heat waves and drought. Our findings demonstrate that remote sensing datasets are capable of providing the continuous whole-Earth coverage of heat wave changes, and they would play more important roles in preventing or mitigating the impacts of extreme heat events on people and natural environment.