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The spatiotemporal variability and trends of atmospheric blockings over the Euro-Atlantic region and their influence on the occurrence of the persisting extreme temperature conditions in Poland namely heat waves (HWs) and cold spells (CSs) during the period 1979–2023 were analyzed. Blockings were identified at 500 hPa geopotential level, using the meridional geopotential gradient method, supplemented with the quantile filter and persistence filter, using reanalysis data from the National Oceanic and Atmospheric Administration Physical Science Laboratory (NCEP-DOE AMIP-II R-2). HWs and CSs were defined as sequences of at least 3 days with the maximum air temperature above 30 °C or below -10 °C, respectively based on data obtained from the Institute of Meteorology and Water Management – National Research Institute (IMGW – PIB) for the period 1979–2022 across 37 stations in Poland. The climatology of Euro-Atlantic blocking occurrence in the zonal belt between 45 and 75 degrees in the northern hemisphere exhibits high spatiotemporal variability. Blocking structures are most frequent in the spring, particularly in May. A secondary peak of frequency is observed in July when the Ural blocking exhibits 15% frequency. Patterns of trends in blocking occurrence are variable and the strongest signals of changes are observed in spring. The occurrence of HWs in Poland is constantly accompanied by blocking situations, most often located northeast of Poland, while the winter CSs are associated with the blockings located over the North Atlantic and northern Scandinavia. [ABSTRACT FROM AUTHOR]

The Mediterranean faces frequent heavy precipitation, deadly heatwaves, and wildfires fueled by its climate. Greece, with its complex topography, experiences severe and extreme weather events that have escalated in recent years and are projected to continue rising under future climate conditions. This paper analyzes severe weather events and trends in Greece from 2010 to 2023, leveraging data from an expanded network of weather stations spanning across Greece, as well as long-term meteorological data from the reference weather station in the center of Athens. The focus includes analysis of heat waves, intense rainfall and droughts, thunderstorms, hail, tornadoes, and fire weather conditions. The societal impact of severe weather events is also discussed. The paper aims to provide both long-term (1901–2023) and recent year analyses (2010–2023). The main results show that between 2010 and 2023, Greece experienced: nearly one heatwave per summer; heavy rainfall events, most common in winter and autumn, showing a significant increase, particularly in the eastern Aegean and western continental Greece; dry spells, which are longest in southern Greece; thunderstorm and hail events peaking in spring and summer; fire weather conditions and risk peaking in southern Greece. Finally, societal impacts from weather hazards have increased in Greece over the past 14 years, with flash floods being the most frequent and damaging events, while public preparedness and effective risk communication remain low. [ABSTRACT FROM AUTHOR]

Sub-Saharan Africa (SSA) is a region vulnerable to extreme weather events due to its low level of adaptive capacity. In recent decades, SSA has been punctuated by more intense climatic phenomena that severely affect its population. Therefore, this study evaluates the performance of the ERA5 and CHIRPS datasets, and the spatio-temporal evolution of extreme weather indices and their potential relationship/response to climate variability modes in the Pacific, Indian, and Atlantic oceans, namely, the El Niño−Southern Oscillation, Indian Ocean Dipole, and Tropical Atlantic Variability (ENSO, IOD, and TAV). The CHIRPS dataset showed strong positive correlations with CPC in spatial patterns and similarity in simulating interannual variability and in almost all seasons. Based on daily CHIRPS and CPC data, nine extreme indices were evaluated focusing on regional trends and change detection, and the maximum lag correlation method was applied to investigate fluctuations caused by climate variability modes. The results revealed a significant decrease in total precipitation (PRCPTOT) in north−central SSA, accompanied by a reduction in Consecutive Wet Days (CWDs) and maximum 5-day precipitation indices (RX5DAYS). At the same time, there was an increase in Consecutive Dry Days (CDDs) and maximum rainfall in 1 day (RX1DAY). With regard to temperatures, absolute minimums and maximums (TNn and TXn) showed a tendency to increase in the center−north and decrease in the south of the SSA, while daily maximums and minimums (TXx and TNx) showed the opposite pattern. The IOD, TAV, and ENSO modes of climate variability influence temperature and precipitation variations in the SSA, with distinct regional responses and lags between the basins. [ABSTRACT FROM AUTHOR]

The amount of moisture in the soil can significantly influence hot extremes, such as heatwaves and droughts, through various direct and indirect mechanisms. This study examines the impact of soil moisture initialisation on the simulations of the 2009 heatwave event over India using the Weather Research and Forecasting model (WRF) model. Multiple initial conditions were produced by modifying actual soil moisture in ERA-5 reanalysis. The impact of soil moisture on the intensity and spatial extension of heatwave is studied, and physical mechanisms are examined in detail. The control simulations have reasonably simulated spatial patterns of soil moisture and maximum temperature when compared with gridded observations. Our results show that an increase (decrease) in initial soil moisture simulates a heatwave with reduced (enhanced) magnitude and spatial extent. Interestingly, an increase in soil moisture does have more influence on heat waves than a decrease in soil moisture. In wet simulations, we see a greater increase in latent heat flux when compared to a decrease in sensible heat. Additionally, wet simulations shift soil moisture-temperature coupling from a dry regime to a transitional regime. An overall increase in net radiation is observed in wet simulations through water vapour and cloud feedback. Reduced soil moisture enhances the high-pressure system associated with heatwaves through positive feedback on geopotential height in the mid-troposphere. [ABSTRACT FROM AUTHOR]

Regional climate studies are essential for pinpointing climate hotspots and developing effective resilience strategies. This study examined trends in eight precipitation and ten temperature extremes in Odisha, India, using RClimDex in R studio with data from the India Meteorological Department, Pune, covering 1980 to 2010 for Khordha, Keonjhar, and Sambalpur. Statistical significance was tested through linear regression and Mann-Kendall tests. Results show a significant shift in climate, particularly in Sambalpur and Khordha, where nine and seven out of ten temperature indices, respectively, exhibited significant changes. The mean maximum temperature increased significantly in Khordha (0.03 °C/year) and Sambalpur (0.026 °C/year), while the mean minimum temperature rose significantly in Khordha (0.03 °C/year) but decreased in Keonjhar (-0.029 °C/year) and Sambalpur (-0.061 °C/year). Cool nights significantly decreased in Khordha (-0.229 days/year) and increased in Sambalpur (0.557 days/year). Warm nights rose significantly in Khordha (0.484 days/year) but declined in Sambalpur (-0.421 days/year). The warm spell duration indicator showed significant increases across all regions, with increments of 0.308, 0.438, and 0.689 days/year in Khordha, Keonjhar, and Sambalpur, respectively. Warm days also rose significantly in Khordha (0.301 days/year) and Sambalpur (0.379 days/year). Regarding precipitation, Khordha showed positive trends in all eight indices, with a significant change in heavy rainfall days. In Keonjhar, no significant changes were observed, while Sambalpur experienced a significant decrease in total annual rainfall (-9.621 mm/year). These findings highlight a significant shift in climate patterns within Odisha, with Sambalpur and Khordha more vulnerable to extreme events compared to Keonjhar. [ABSTRACT FROM AUTHOR]

Abstract Global warming has significantly increased the risk of heat waves (HWs) globally, with India being particularly vulnerable during the summer months (March-June; MAMJ). This study investigated the critical relationship between Indian summer monsoon rainfall (ISMR) and the occurrence of premonsoon HWs in subsequent years across the Indian subcontinent. It has been hypothesized that droughts during the ISMR could lead to more frequent HWs in the following MAMJ period. Using the Indian Meteorological Department's (IMD) gridded observed surface air daily maximum temperature (Tmax) dataset for the period 1951–2023, we analyzed the climatic patterns, interannual variability (IAV), and coefficient of variation (CV) of Tmax across India. The analysis compares two distinct periods: 1951–1999 (P1) and 2000–2023 (P2), with focus on Tmax trends and HW duration, distinguishing between short-duration HWs (SHWs, 2 days) and long-duration HWs (LHWs, 5 days or more). A key purpose of this study is to examine the relationship between the preceding all India summer monsoon rainfall (AISMR) and the occurance of various types of HW in the subsequent premonsoon season. In particular extreme AISMR events, such as droughts or excess rainfall, influence HW occurrence. The findings reveal a significant rise in Tmax across many regions of India during the MAMJ period, with the highest temperatures (> 37 °C) observed in northwestern, central, and eastern coastal areas. Northern India, particularly the Himalayan region, exhibits a greater interannual variability in Tmax, with June showing the most pronounced fluctuations. The study also highlights an increase in the frequency and intensity of HWs, especially in central and southern India, with the Chandigarh-Haryana-Delhi region recording the highest occurrences. A critical finding is the strong inverse relationship between the AISMR and conditions in the subsequent premonsoon season. Specifically, drought in the antecedent AISMR results in reduced soil moisture, which is strongly associated with higher premonsoon Tmax and an increased frequency of extreme heat events across India, particularly in regions prone to severe heat during this season. Drought conditions during AISMR are closely linked to higher HW frequencies in the following summer, especially in the central, northeast-central, and east-coastal regions. The frequencies of HW days, SHWs, and LHWs are significantly greater in years following AISMR droughts than in those following excess rainfall, indicating that drought years are more likely to lead to widespread HW activity. Despite the overall warming trends, some regions, such as the Indo-Gangetic Plain and parts of the Himalayan region, show cooling trends, although these trends are less widespread. The onset of the monsoon in June tends to reduce the intensity and spatial extent of warming, particularly in the central and eastern coastal regions, although significant HW trends persist in northwestern India and along the east coast. This study underscores the crucial role of AISMR in influencing HW events across India and highlights the need for adaptive strategies that account for the interactions between monsoon rainfall and HW risk, providing valuable insights for mitigating the impacts of HWs in the context of global warming.

Abstract This study explores the dynamic of emergency department (ED) access during heat waves. Given the importance of avoiding overcrowding and long waits in an ED, it is important to explore all the possible determinants of ED inflows. We shed some light on the impact that heat waves have on this dynamic, via a quantitative analysis of the number of ED visits in the Campania region of Italy during the summers between 2016 and 2019. Aggregating individual-level data, we examine the relationship between extreme heat events and number of ED visits, controlling for social, demographic and economic characteristics. Our findings, obtained through Random Effects Poisson and fractional probit estimations, show that heat waves above 39 perceived degrees Celsius significantly increase the number of ED visits, revealing the impact that heat waves have on ED utilization in Campania. Insights for local public health strategies and emergency preparedness initiatives are discussed.

Heat waves (HW) are prolonged periods of excessively hot weather that can cause severe socioeconomic and environmental impacts. This study aims to evaluate the differences in stored heat and turbulent flux partitioning during a heat wave event in Mexico City, using observations from an eddy covariance tower during the period from 14 June to 21 June 2023. During this period, net radiation (Rn) and sensible heat flux (H) increased significantly, particularly from noon to evening, reflecting stable atmospheric conditions. The air temperature showed a noticeable increase in the afternoon and evening, whereas absolute humidity decreased. We found that during the heat wave, the Bowen ratio (β) increased by 80% during daylight hours and 65% over a full 24-hour period compared to the pre-heat wave period. This heat release at night prolonged warm conditions, intensifying heat stress. The partitioning of net radiation for latent heat (LE), sensible heat (H), and heat storage (ΔQs) showed significant changes; during the heat wave, 51% of Rn was allocated to H and 34% to ΔQs, compared to pre-heat wave values of 49% and 27%, respectively. This study introduces a new characterization of heat waves in terms of energy, emphasizing the significant shifts in energy flux partitioning and storage. The new characterization highlights the critical role of urban heat storage and its release in exacerbating heat stress during and after heat wave events. This approach provides a comprehensive understanding of the energy dynamics during heat waves, which is essential for developing effective mitigation strategies to combat the adverse effects of extreme heat in urban environments. [ABSTRACT FROM AUTHOR]

The population of Senegal faces health challenges related to desert dust and heat waves (HWs). This study aims to (a) update the documentation of HWs in Senegal, expanding on the work of Sambou et al. (2019); (b) investigate the modulation of dust indicators during HWs; and (c) assess the distinct impacts of dust content on night-time and daytime HWs. We use [i] the daily maximum air temperature (Tx), minimum air temperature (Tn), and apparent temperature (Ta) from 12 stations in the Global Surface Summary of the Day (GSOD) database and [ii] the Dust Aerosol Optical Depth (Dust AOD), particulate matter (PM) concentrations, 925 hPa wind, and Mean Sea Level Pressure (MSLP) from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis. HWs are defined for each station in spring as periods when Tx, Tn, or Ta exceeds the 95th percentile for at least three consecutive days. Three homogeneous zones from the Atlantic coast to inland Senegal are identified using hierarchical cluster analysis: Zone 1 (Saint-Louis, Dakar-Yoff, Ziguinchor, and Cap Skirring), Zone 2 (Podor, Linguère, Diourbel, and Kaolack), and Zone 3 (Matam, Tambacounda, Kédougou, and Kolda). Our results show that Zone 1 records the highest number of HWs for Tx, Tn, and Ta, while Zone 3 experiences more HWs in terms of Tn and Ta than Zone 2. The influence of dust is notably stronger for HWs linked to Tn and Ta than for those related to Tx. Analysis of the mechanisms shows that the presence of dust in Senegal and its surrounding regions is detected up to four days before the onset of HWs. These findings suggest that dust conditions associated with spring HWs in Senegal may be better distinguished and predicted. [ABSTRACT FROM AUTHOR]

Defining the effect of an exposure of interest and selecting an appropriate estimation method are prerequisites for causal inference. Current understanding of the ways in which an association between heat waves (ie, consecutive days of extremely high temperature) and an outcome depends on whether adjustment was made for temperature and how such adjustment was conducted is limited. In this paper we aim to investigate this dependency, demonstrate that temperature is a confounder in heat-wave–outcome associations, and introduce a new modeling approach with which to estimate a new heat-wave–outcome relationship: E[ R (Y)| HW  = 1, Z ]/E[ R (Y)| T  = OT , Z ], where HW is a daily binary variable used to indicate the presence of a heat wave; 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 heat-wave–outcome relationships and careful selection of modeling approaches to understand the impacts of heat waves under climate change. We demonstrate our approach using real-world data for Seoul, South Korea. Our demonstration suggests that the total effect of heat waves may be larger than what may be inferred from the extant literature. An R package, HEAT , has been developed and made publicly available. This article is part of a Special Collection on Environmental Epidemiology. [ABSTRACT FROM AUTHOR]

The urban heat island (UHI) effect, marked by higher temperatures in urban areas compared to rural ones, is a key indicator of human-driven environmental changes. This study aims to identify the key morphological parameters that primarily contribute to the development of surface urban heat island intensity (SUHII) and investigates the relationship between SUHII and urban morphology using land surface temperature (LST) data from the Sentinel-3 satellite. The research focuses on Milan and Lecce, analyzing how urban geometry affects SUHII. Factors such as building height, aspect ratio, sky visibility, and surface cover are examined using approximately 1000 satellite images from 2022 and 2023. The study highlights seasonal and diurnal variations in SUHII, with particular emphasis on HW periods. Through multicollinearity and multiple regression analyses, the study identifies the main morphological drivers influencing SUHII in the two cities, specifically the Impervious Surface Fraction (ISF) and Mean Building Height (HM). Milan consistently exhibits higher SUHII, particularly during HWs, while Lecce experiences a negative SUHII, especially during the summer, due to lower urban density, more vegetation, and the low soil moisture around the urban area. Both cities show positive SUHII values at night, which are slightly elevated during HWs. The heat wave analysis reveals the areas most susceptible to overheating, typically characterized by high urban density, with ISF and HM values in some cases above the 90th percentile (0.8 and 13.0 m, respectively) compared to the overall distribution, particularly for Milan. The research emphasizes the importance of urban morphology in influencing SUHII, suggesting that detailed morphological analysis is crucial for developing climate adaptation and urban planning strategies to reduce urban overheating and improve urban resilience to climate change. [ABSTRACT FROM AUTHOR]

The probability of heat extremes is often estimated using the non-stationary generalized extreme value distribution (GEVD) applied to time series of annual maximum temperature. Here, this practice was assessed using a global sample of temperature time series, from reanalysis (both at the grid point and the region scale) as well as station observations. This assessment used forecast negative log-likelihood as the main performance measure, which is particularly sensitive to the most extreme heat waves. It was found that the computationally simpler normal distribution outperforms the GEVD in providing probabilistic year-ahead forecasts of temperature extremes. Given these findings, it is suggested to consider alternatives to the GEVD for assessing the risk of extreme heat. [ABSTRACT FROM AUTHOR]

Given rapid glacier thinning and retreat observed in the Pyrenees in recent decades, an updated glacier inventory and continuous mass balance assessments are important to understand the ongoing variability and changes of these very small glaciers (< 0.5 km2). The mass balance years 2021/22 and 2022/23 were characterised by prolonged extreme heat waves and reduced snow duration that severely affected the Pyrenees, which also impacted their glaciers. This paper reviews the criteria for classifying ice bodies as glaciers or ice patches, presents the latest high-resolution glacier inventory for the Pyrenees, and quantifies the mass losses caused by the extreme climate conditions in 2022 and 2023. The glacierised area was determined by manual mapping of high-resolution (0.2 m spatial resolution) aerial orthomosaics acquired by unmanned aerial vehicles (UAVs) and aerial orthophotos (0.25 m spatial resolution) for the few glaciers not surveyed by UAVs. 3D point clouds, also obtained from UAV flights, were used to update the results for the change in surface elevation (glacier thickness) and mass balance between 2020 and 2023. For the Pyrenees, the total glacierised area in 2023 is 143.2 ± 1.8 ha in 15 different glaciers and 8 ice masses were degraded to ice patches according to our criteria. The resulting area change between 2020 and 2023 is -94.8 ha, representing a -39.8% decrease of the glaciarised area from 2020 to 2023, increasing the annual ratio of area change from 2020 to 2023 by -8.7% yr−1 compared to the period 2011–2020 (-2.4% yr−1). The change in glacier thickness measured on 12 glaciers shows a decrease of -2.52 m yr−1 for the period 2020–2023, which represents a significant acceleration in glacier thickness loss compared to -0.80 m yr−1 for the period 2011–2020. The three glaciers (Infiernos, Monte Perdido and Aneto) on which annual geodetic measurements were carried out showed slightly higher glacier thickness losses (-0.91 m yr−1) in the first mass balance year (2020/21) than in the previous decade (2011–2020), while the losses in the last two mass balance years (2021/22 and 2022/23) were three to four times higher (-3.42 m yr−1 and -3.07 m yr−1 respectively) and exceeded the record values. [ABSTRACT FROM AUTHOR]

This study explores the dynamic of emergency department (ED) access during heat waves. Given the importance of avoiding overcrowding and long waits in an ED, it is important to explore all the possible determinants of ED inflows. We shed some light on the impact that heat waves have on this dynamic, via a quantitative analysis of the number of ED visits in the Campania region of Italy during the summers between 2016 and 2019. Aggregating individual-level data, we examine the relationship between extreme heat events and number of ED visits, controlling for social, demographic and economic characteristics. Our findings, obtained through Random Effects Poisson and fractional probit estimations, show that heat waves above 39 perceived degrees Celsius significantly increase the number of ED visits, revealing the impact that heat waves have on ED utilization in Campania. Insights for local public health strategies and emergency preparedness initiatives are discussed. [ABSTRACT FROM AUTHOR]

Climate change has significant implications for agriculture, especially in viticulture, where temperature plays a crucial role in grapevine (Vitis vinifera) growth. Mendoza's climate is ideal for producing high-quality wines, but 21st-century climate change is expected to have negative impacts. This study aimed to evaluate the effects of increased temperature on the phenology, physiology, and yield of Malbec, Bonarda, and Syrah. A field trial was conducted over two seasons (2019–2020 and 2020–2021) in an experimental vineyard with an active canopy heating system (+2–4 °C). Phenological stages (budburst, flowering, fruit set, veraison, harvest), shoot growth (SG), number of shoots (NS), stomatal conductance (gs), chlorophyll content (CC), chlorophyll fluorescence (CF), and water potential (ψa) were measured. Additionally, temperature, relative humidity, light intensity, and canopy temperature were recorded. Heat treatment advanced all phenological stages by approximately two weeks, increased SG and NS, and reduced gs and ψa during the hottest months. CC and CF remained unaffected. The treatment also resulted in lower yields, reduced acidity, and increased °Brix in both seasons. Overall, rising temperatures due to climate change advance the phenological phases of Malbec, Syrah, and Bonarda, leading to lower yields, higher °Brix, and lower acidity, although physiological variables remained largely unchanged. [ABSTRACT FROM AUTHOR]

Global warming has significantly increased the risk of heat waves (HWs) globally, with India being particularly vulnerable during the summer months (March-June; MAMJ). This study investigated the critical relationship between Indian summer monsoon rainfall (ISMR) and the occurrence of premonsoon HWs in subsequent years across the Indian subcontinent. It has been hypothesized that droughts during the ISMR could lead to more frequent HWs in the following MAMJ period. Using the Indian Meteorological Department's (IMD) gridded observed surface air daily maximum temperature (Tmax) dataset for the period 1951–2023, we analyzed the climatic patterns, interannual variability (IAV), and coefficient of variation (CV) of Tmax across India. The analysis compares two distinct periods: 1951–1999 (P1) and 2000–2023 (P2), with focus on Tmax trends and HW duration, distinguishing between short-duration HWs (SHWs, 2 days) and long-duration HWs (LHWs, 5 days or more). A key purpose of this study is to examine the relationship between the preceding all India summer monsoon rainfall (AISMR) and the occurance of various types of HW in the subsequent premonsoon season. In particular extreme AISMR events, such as droughts or excess rainfall, influence HW occurrence. The findings reveal a significant rise in Tmax across many regions of India during the MAMJ period, with the highest temperatures (> 37 °C) observed in northwestern, central, and eastern coastal areas. Northern India, particularly the Himalayan region, exhibits a greater interannual variability in Tmax, with June showing the most pronounced fluctuations. The study also highlights an increase in the frequency and intensity of HWs, especially in central and southern India, with the Chandigarh-Haryana-Delhi region recording the highest occurrences. A critical finding is the strong inverse relationship between the AISMR and conditions in the subsequent premonsoon season. Specifically, drought in the antecedent AISMR results in reduced soil moisture, which is strongly associated with higher premonsoon Tmax and an increased frequency of extreme heat events across India, particularly in regions prone to severe heat during this season. Drought conditions during AISMR are closely linked to higher HW frequencies in the following summer, especially in the central, northeast-central, and east-coastal regions. The frequencies of HW days, SHWs, and LHWs are significantly greater in years following AISMR droughts than in those following excess rainfall, indicating that drought years are more likely to lead to widespread HW activity. Despite the overall warming trends, some regions, such as the Indo-Gangetic Plain and parts of the Himalayan region, show cooling trends, although these trends are less widespread. The onset of the monsoon in June tends to reduce the intensity and spatial extent of warming, particularly in the central and eastern coastal regions, although significant HW trends persist in northwestern India and along the east coast. This study underscores the crucial role of AISMR in influencing HW events across India and highlights the need for adaptive strategies that account for the interactions between monsoon rainfall and HW risk, providing valuable insights for mitigating the impacts of HWs in the context of global warming. [ABSTRACT FROM AUTHOR]

This paper presents a novel hybrid approach for the probabilistic reconstruction of meteorological fields based on the combined use of the analogue method (AM) and deep autoencoders (AEs). The AE–AM algorithm trains a deep AE in the predictor fields, which the encoder filters towards a compressed space of reduced dimensionality. The AM is then applied in this latent space to find similar situations (analogues) in the historical record, from which the target field can be reconstructed. The AE–AM is compared to the classical AM, in which flow analogues are explicitly searched in the fully resolved field of the predictor, which may contain useless information for the reconstruction. We evaluate the performance of these two approaches in reconstructing the daily maximum temperature (target) from sea‐level pressure fields (predictor) recorded during eight major European heat waves of the 1950–2010 period. We show that the proposed AE–AM approach outperforms the standard AM algorithm in reconstructing the magnitude and spatial pattern of the considered heat wave events. The improvement ranges from 7% to 22% in skill score, depending on the heat wave analyzed, demonstrating the potential added value of the hybrid method. [ABSTRACT FROM AUTHOR]

Land surface processes such as the soil moisture—air temperature coupling influence compound climate anomalies like heatwaves and droughts, yet the spatial and temporal variability of the coupling strength is still understudied. We assess global land exposure to concurrent heat waves and drought since the 1980s. We found that drought significantly shapes the spatial distribution of the risk of heat waves. We show that the portion of global land experiencing drought‐conditioned heat anomalies more than tripled in less than 3 decades. However, using such traditional heat waves indicators, the level of spatial coupling between heat waves and drought seems to decline. Conversely, time‐dependent approaches accounting for the baseline climate change offer a more stable perspective. We conclude that tailoring hazard definitions to specific processes and impacts is crucial. Early warning systems can play a prominent role in mitigating the impacts of global warming to society. Plain Language Summary: Climate change is increasing the risk of simultaneous heatwaves and droughts, which significantly impact ecosystems and society. These events are influenced by soil moisture and air temperature interactions, but the variability of this relationship is not well understood. Using data from observations and forecasts since the 1980s, we analyzed global exposure to these compound events. We found that drought significantly influences where heatwaves occur, with the area experiencing both drought and heatwaves more than tripling in less than 30 years. Traditional methods for detecting temperature anomalies may give misleading results, so we recommend using time‐dependent approaches that account for climate change. These approaches provide a clearer understanding of soil moisture‐air temperature interactions and are better for studying the impacts on adaptable systems. Traditional methods are still useful for assessing impacts on less adaptable ecosystems and some societal sectors. We also highlight the importance of weather forecasts in providing early warnings to help society adapt to global warming. Key Points: Drought significantly influences heatwave locations. The affected global land area tripled in under 30 yearsTime‐dependent approaches better reflect soil moisture‐air temperature interactions amid climate changeWeather forecasts are crucial for early warnings, aiding societal adaptation to global warming [ABSTRACT FROM AUTHOR]

Climate change and heat stress pose significant challenges to livestock. Local breeds, particularly small ruminants, are gaining importance due to their adaptability to harsh climates. However, the extensive system they are commonly reared in leaves them exposed to the effects of climate change. This study aims to describe the distribution and climate-related challenges faced by registered Italian sheep and goat breeds over the past seven decades. Geolocalized data from all registered small ruminant farms were combined with climatic information retrieved from the "ERA-5-Land hourly data from 1950 to present" dataset. These data were used to calculate average daily temperature, temperature humidity index (THI), and total precipitation during summer. Additionally, THI-based heat waves (HWs) were examined, including the yearly number of HW days and mean THI during HW days. These data were analysed through linear regression models including region or breed, year, and their interaction as fixed factors. The climate data indicate a concerning trend of rising summer temperatures, THI, and HW frequency and intensity, particularly over the past three decades. Central-northern Italy, including the Po Valley and the Alpine Arch, is the most affected region, impacting breeds like Rosset and Brogne sheep, and Lariana and Frisa Valtellinese goats. This is of particular concern because these populations have not been selected for hot climates, and their already small population size exacerbates the problem. Conversely, southern Italy, characterized by hotter and drier temperatures, remained relatively stable. Breeds from this region, such as Girgentana and Nicastrese goats and Nera di Arbus sheep, might represent excellent case studies for climatic adaptation and potential resources for selection for resilience in the face of ongoing climate changes. The findings presented here are essential for the development of monitoring and intervention strategies for breeds facing future vulnerabilities, as well as for designing experiments to explore environmental adaptability in small ruminants. [ABSTRACT FROM AUTHOR]

The aim of this paper is twofold. From the practical point of view, an enhanced model for the description of thermoelectric effects at nanoscale is proposed. From the theoretical point of view, instead, in the particular case of the proposed model, the equivalence between two classical techniques for the exploitation of the second law of thermodynamics is shown, i.e., Onsager's method and Liu's technique. An analysis of the heat-wave propagation is performed as well. [ABSTRACT FROM AUTHOR]

Climate change predictions indicate that future conditions will be hotter and drier, and rainfall will be more variable. Climatic conditions can affect individual condition and shape offspring sex ratios. The implications that climate change have for mammalian sex allocation are vast but are currently poorly understood.There are several scenarios under which climate‐driven sex allocation responses might emerge. Here, I make predictions on the direction of offspring sex ratio biases under hypothetical situations of restricted resource availability and altered social/spatial structures that may result from hotter, drier conditions.I searched the literature for existing evidence of climate‐driven offspring sex ratio biases among individuals studied in wild populations. There was no strong, directional support for the production of sons or daughters under 'good' or 'poor' climatic conditions among the 30 studies had reported on climatic variables and offspring sex ratio.I also searched the literature for studies that assessed maternal condition and offspring sex ratio in natural populations (i.e. there is a link between climate, resource availability and maternal condition). Of the 27 investigations, half reported a bias in favour of sons born to mothers in 'good' condition (56%). I discuss how this outcome could be due to a publication bias, or that it may indicate that low resource availability has the potential to lead to mothers in poor condition and the production of fewer sons.I consider the conservation implications of climate‐driven offspring sex ratios skews being carried through to the population level. I discuss the challenge of being able to account for the multiple factors that influence offspring sex ratios in natural populations and emphasise the growing need for more research in this important area of mammalian evolutionary ecology. [ABSTRACT FROM AUTHOR]

Research on heat waves is greatly important not only due to their effect on social, economic, and ecological systems, but also due to the complexity of the processes that create them. Therefore, this research mainly investigated the trend of long-term changes in various characteristics of heat waves in hot and dry regions of Iran. For this purpose, the daily maximum temperature data of 15 meteorological stations in the central and southeastern parts of Iran were used from 1985 to 2018. Using the excess heat factor (EHF) index, five different features of heat waves including the number of heat waves (HWN), heat waves duration (HWD), heat waves frequency (HWF), heat waves mean (HWM), and heat waves magnitude (HWA) were extracted for all the studied stations. Then, their trend of long-term changes was analyzed using the Sen's slope estimator nonparametric method. The results showed that on a regional scale, all five characteristics of heat waves have an increasing trend at a significance level of 95%, so an increase of 0.5 events per decade has been observed for the HWN. The trend of long-term changes in the HWD has also indicated an increase of 0.91 days per decade. The HWF has shown more drastic changes than other characteristics of heat waves, so in every decade 2.61 days have been added to the frequency of days contributing to the occurrence of heat waves. The regional intensity of HWM and HWA also show an increase of 0.1 and 0.4 °C in each decade, respectively. These findings show the importance of choosing a suitable index for monitoring different characteristics of heat waves. The EHF index is a suitable index, which can be one of the efficient indices in this regard. [ABSTRACT FROM AUTHOR]

Abstract Heat waves harm human health and adversely impact the natural environment and society, especially in urban regions. Understanding the differences between heat waves in urban agglomerations and their driving mechanisms is essential for sustainable development. In this study, we investigate the spatiotemporal distribution of summertime heat waves and their association with sea surface temperature modes in two of China's most densely populated urban areas: the Beijing–Tianjin–Hebei (BTH) and the Yangtze River Economic Belt (YREB). The results indicate an increase in the frequency of heat waves for BTH and YREB by 0.02 times a−1 and 0.1 times a−1 and duration by 0.09d a−1 and 0.48d a−1, respectively. Regarding spatial distribution, the duration and frequency of BTH heat waves gradually decreased from northeast to southwest. In contrast, the heat waves in YREB were concentrated in the upper and parts of the lower reaches. The Atlantic Multidecadal Oscillation significantly influences heat waves in both the BTH and YREB regions. Nevertheless, the Pacific Decadal Oscillation, Indian Ocean Basin‐Wide Index, and Cold‐tongue ENSO Index primarily impact heat waves in the YREB region, with limited influence observed in the BTH region. This study provides a scientific basis for accurately identifying heat waves and understanding their changes, assisting decision‐makers in formulating mitigation, adaptation strategies, and disaster prevention policies related to heat‐induced consequences.