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In this work, we compare the rate of warming of summertime extreme temperatures (summer maximum value of daily maximum temperature; TXx) relative to the local mean (summer mean daily maximum temperature; TXm) over the Northern Hemisphere in observations and one set of large ensemble (LE) simulations. During the 1979–2021 historical period, observations and simulations show robust warming trends in both TXm and TXx almost everywhere in the Northern Hemisphere, except over the eastern U.S. where observations show a slight cooling trend in TXx, which may be a manifestation of internal variability. We find that the observed warming rate in TXx is significantly smaller than in TXm in North Africa, western North America, Siberia, and Eastern Asia, whereas the warming rate in TXx is significantly larger over the Eastern U.S., the U.K., and Northwestern Europe. This observed geographical pattern is successfully reproduced by the vast majority of the LE members over the historical period, and is persistent (although less intense) in future climate projections over the 2051–2100 period. We also find that these relative warming patterns are mostly driven by the local hydroclimate conditions. TXx warms slower than TXm in the hyper-arid, arid, semi-arid and moist regions, where trends in the partitioning of the turbulent surface fluxes between the latent and sensible heat flux are similar during regular and extreme hot days. In contrast, TXx warms faster than TXm in dry-subhumid regions where trends in the partitioning of the surface fluxes are significantly different between regular and extreme hot days, with a larger role of sensible heat flux during the extreme hot days.

In this study, the daily maximum and minimum temperatures measured over the period 1961–2020 by 18 stations located near the Mediterranean coast are analysed to evaluate temperature trends and to compute 10 climate indices, selected among those proposed by the Expert Team on Climate Change Detection and Indices to monitor the occurrence of climate extremes of temperature. The trend analysis is performed using the Seasonal‐Kendall test. The results show statistically significant positive trends in both above‐mentioned variables throughout the Mediterranean, although the rate of warming is more marked in the minimum than in the maximum temperature and is more evident in the western portion of the Mediterranean Basin from 1990 onward. The climate extremes indices are evaluated assuming two different base periods (1961–1990 and 1991–2020). The shift forward of the base period involves a general rise in the percentile‐based thresholds used for identifying temperature extremes, as a natural consequence of the current atmospheric warming, resulting in fewer warm events and more cold events since the 1990s using a warmer/later base period. The application of the Seasonal‐Kendall test to the occurrence of extreme warm and cold events reveals that the western portion of the Mediterranean and the Adriatic Sea are the subregions most influenced by the base period update. This study demonstrates that the selection of the base period for the identification of extreme temperature events significantly impacts the results, and that the choice of a recent base period partially masks the ongoing atmospheric warming. The results suggest that the base period 1961–1990 might be more appropriate for climatological studies, as it provides a solid and stable baseline, and that attention must be paid when scientific results are shared with stakeholders, so as not to alter the communication of warnings and specific risks for the population. [ABSTRACT FROM AUTHOR]

This study examines the trends in heatwave characteristics across mainland Portugal from 1980/1981 to 2022/2023, utilising ERA5-Land reanalysis data. To achieve this, the study applies the Heatwave Magnitude Index (HWMI) to identify heatwave days for minimum (Tmin) and maximum (Tmax) temperatures across 15 grid-points representing Portugal's diverse geography and climate. Three key annual parameters are analysed: the number of heatwave days (ANDH), the average temperature during heatwaves (AATW), and the intensity of heatwave events (AIHD). Results reveal a consistent increase in heatwave persistence throughout mainland Portugal, with more pronounced trends observed for Tmax compared to Tmin. ANDH Tmin shows upward trends across all grid-points, with increases ranging from 0.8 to 4.2 days per decade. ANDH Tmax exhibits even more significant increases, with 11 out of 15 grid-points showing statistically significant rises, ranging from 2.2 to 4.4 days per decade. Coastal areas, particularly in the south, demonstrate the most substantial increases in heatwave persistence. The intensity of heatwaves, as measured by AIHD, also shows positive trends across all grid-points for both Tmin and Tmax, with southern locations experiencing the most significant increases. The study also discusses decadal trends in annual averages of Tmin and Tmax, as well as extreme measures such as annual minimum (AMIN) and annual maximum (AMAX), daily temperatures spatially represented across mainland Portugal. These analyses reveal widespread warming trends, with more pronounced increases in Tmax compared to Tmin. The AMIN and AMAX trends further corroborate the overall warming pattern from the heatwave analyses, with notable spatial variations observed. The findings indicate a substantial worsening in the occurrence, duration, and intensity of heatwave events. This increased persistence of heatwaves, especially evident from the early 2000s onwards, suggests a potential climate regime shift in mainland Portugal. The results underscore the need for adaptive strategies to address the growing challenges posed by more frequent and intense heatwaves in the region. [ABSTRACT FROM AUTHOR]

The associations between atmospheric temperature and congenital heart disease (CHD) and its subtypes are still inconclusive. In this population-based retrospective case-control study, 643 CHD cases and 3,215 non-CHD controls were analyzed through distributed lag nonlinear model to estimate the effect of weekly temperature exposure on CHD risk and to identify potentially vulnerable windows. Through the binary logistic regression model, we found that elevated temperature in the first trimester was associated with an increased risk of overall CHD and ventricular septal defect (VSD) (OR: 1.059, 95% CI: 1.002–1.119; OR: 1.094, 95% CI: 1.005–1.190, respectively), while increased temperature in the second trimester was significantly positively correlated with atrial septal defect (ASD) risk. However, the results of the DLNM showed a nonlinear relationship between the weekly average temperature and the risk of total CHDs and the subtypes. Exposure to extremely, moderately, and mildly high temperatures significantly increased the risk of overall CHD, ASD and VSD, and the critical windows were mainly concentrated at the 5th-11th and 23rd-27th weeks of gestation. Low-temperature extreme exposure resulted in vulnerable windows for ASD only: 13th-14th gestational weeks. No significant positive associations were found between extreme temperature and patent ductus arteriosus or tetralogy of Fallot. In the current context of climate change, our results add new evidence to the present understanding of the effects of high- and low-temperature extreme exposure on CHD and its main subtypes. [ABSTRACT FROM AUTHOR]

This study investigates the medium‐range predictability of warm and cold extremes in the Northern Hemisphere and the role that upper‐tropospheric circulation biases play in this regard. Deterministic ERA5 reforecasts for the period 1979–2019 are evaluated based on the ERA5 reanalysis of the respective period, thus providing a large sample for verification and bias identification. The predictability of temperature extremes at 850 hPa is assessed based on the Gilbert Skill Score and other metrics and is shown to exhibit regional and seasonal variations. Summer is generally characterized by lower forecast skill scores than winter for both warm and cold extremes. Moreover, cold extremes in summer have slightly lower skill scores than warm extremes, while the opposite is true in winter. Biases in the frequency of temperature extremes are, to some extent, consistent with biases in mean temperature and indicate an underestimation in the total amount of extremes for much of the hemisphere in summer. Associated with the latter, biases also emerge in the standard deviation of the daily temperature distribution, with the summer values being largely underestimated over most of the hemisphere. The role of upper‐tropospheric circulation in these biases is then assessed by verifying the representation of Rossby‐wave packet (RWP) properties. It is found that the amplitude of RWPs is systematically underestimated in most of the hemisphere in summer, while it is overestimated in many parts of the midlatitudes in winter. Overall, the results suggest that the underestimation of RWP amplitude in summer hinders the medium‐range predictability of temperature extremes in the explored retrospective and operational forecasts. Although operational European Centre for Medium‐Range Weather Forecasts (ECMWF) forecasts gradually improve between 2013 and 2022 in terms of the 850‐hPa temperature and 300‐hPa RWP amplitude absolute errors, the aforementioned summer biases remain qualitatively similar. [ABSTRACT FROM AUTHOR]

With recent advances in technology and modelling, ecologists are increasingly advised to use microclimate, not the usual coarse scale macroclimate based on weather stations, to better reflect the proximal conditions that species experience. This is especially relevant in forest ecosystems, where natural disturbances and management create substantial heterogeneity in microclimates. Under dense canopies, species may experience buffered (less extreme) microclimate temperatures relative to macroclimate, as well as increased relative humidity, reduced light and wind. Focusing on understorey plants, we investigated species response curves to the buffering capacity of the canopy layer, measured as the log‐transformed slope parameter of the microclimate to macroclimate linear relationship. If lower or higher than zero, microclimate temperatures are buffered or amplified, respectively, relative to macroclimate. During leaf‐on conditions (July–September 2021), we measured hourly microclimate temperatures in 157 plots across three temperate deciduous forests with contrasted macroclimates. We used paired hourly macroclimate measurements from nearby weather stations to derive the slope parameter, quantifying microclimate buffering. We surveyed vascular plant and bryophyte communities in 400 m2 plots centred on our microclimate sensors. Species were classified into three groups of forest affinity: core specialists; edge specialists; and generalists. We fitted generalized linear mixed‐effects models, by forest affinity group and by species, to obtain logistic response curves of the probability of occurrence against microclimate buffering. The species' optimum was computed as the microclimate effect that maximizes the species' probability of presence. We found contrasted microclimate preferences: Most bryophytes as well as the vascular plants classified as forest core specialists had an optimum in microclimate buffering, while forest edge specialists and generalists among vascular plants had an optimum in microclimate amplification. As canopies undergo increased disturbance frequency and intensity, more generalists and less forest core specialists might thus be expected in understorey communities, especially for bryophytes. Synthesis. Understorey plants have a species‐specific affinity to the forest microclimate, which we quantify for the first time. The investigation of species response curves to microclimate processes—buffering or amplification—can improve our understanding of the ecology of understorey plants, and help us anticipate their redistribution under climate change. [ABSTRACT FROM AUTHOR]

Assessing the impacts of anthropogenic land use and land cover change (LULCC) on climate extremes is crucial for the public. This necessitates the utilization of state-of-the-art experiments and datasets to enhance our understanding. Here, we used CMIP6-LUMIP experimental results to show the biogeophysical effects of LULCC on extreme temperature and precipitation during the historical period. Three regions with intense LULCC in the Northern Hemisphere experienced cooling effects caused by LULCC. In contrast, only the highest maximum temperature (TXx) showed slight warming effects in three regions with intense LULCC in the Southern Hemisphere near the tropics. The maximum changes in intensity were an ∼ 0.8 °C decrease in the TXx and nearly a 2 °C decrease in the 90th percentile in the lowest minimum temperature (TNn) in North America. South Asia experienced ∼ 4% and 10-day decreases in warm days (TX90p) and warm spell duration (WSDI), respectively, in the 90th percentile. The precipitation response to LULCC displayed a clear difference between the Northern Hemisphere (wetter) and the Southern Hemisphere (drier), especially in terms of mean precipitation and wet days (R1mm). Previous studies support our findings that the impacts of LULCC on temperature extremes are greater in regions with intense LULCC than in remote areas. Seasonal results showed that March-April-May (MAM) and June-July-August (JJA) contributed more to the maximum temperature changes, while the minimum temperature experienced greater responses in MAM and December-January-February (DJF). LULCC tended to induce a shift toward either warmer and drier conditions or wetter and colder conditions in approximately two-thirds of season–region pairs. [ABSTRACT FROM AUTHOR]

The effects of climate change may manifest themselves in different ways, but when it comes to coastal tourism, extreme temperatures, which are the unavoidable consequences of climate change, come to the fore. The study examined the changes that extreme temperatures can make on major coastal tourism destinations by using such indices as hot summer days, tropical nights, combined hot days and tropical nights, and days with dangerous apparent temperature (> 40.6 °C). Under the RCP4.5 and RCP8.5 scenarios, increases in these indices are expected for Antalya, Aydın, Balıkesir, İzmir, and Muğla on the Turquoise Coast in the near (2021-2050) and distant (2071-2100) future. The projections based on both scenarios indicate that there might be a rise in the number of hot summer days, tropical nights, and days exceeding the critical human thermal comfort conditions on the Turquoise Coast. Expected increases may reach the highest values under the pessimistic scenario at the end of the century. The increase in these indices caused by rising temperatures may adversely affect the tourism sector due to changes in tourism demands, destinations, and seasonal shifts. [ABSTRACT FROM AUTHOR]

BackgroundWhile temperature extremes have been shown to be associated with an increased risk of hospital admissions, evidence of their impact on the length of hospital stay, which may capture the lingering effects of temperature extremes, is scarce.ObjectivesWe aimed to evaluate the association between daily variation in ambient temperature and daily variation in daily total length of stay (daily TLOS), a composite measure encompassing the daily count of hospital admissions and their corresponding length of hospital stay among cardiopulmonary patients. Additionally, we quantified the burden of TLOS attributable to non-optimal temperatures among Hong Kong’s older adult population.MethodsWe used a generalized linear regression with a distributed lag non-linear model to estimate the association between ambient temperature and daily TLOS. The analysis used 13 years of time-series data (1998–2010) on daily temperature and hospital admissions for cardiopulmonary diseases through accident and emergency departments among Hong Kong’s older adult population. We quantified the attributable risk of TLOS by calculating the temperature-related days of hospital stay and the attributable fraction (AF).ResultsWe recorded a total of 4,095,722 hospital stay days for cardiovascular patients and 4,492,697 days for respiratory patients. We found that both cold and heat were associated with increased TLOS for cardiopulmonary disease. The temperature-related AF was 11.5% (95% empirical CI: 5.3–17.2%) for cardiovascular disease, corresponding to an annual increase of 36,174 days (95% empirical CI: 15,286–57,018). For respiratory disease, the AF was 10.7% (95% empirical CI: 7.1–13.9%), equating to an annual increase of 36,897 days (95% empirical CI: 24,949–49,024) days annually.ConclusionExtreme temperatures were associated with increased TLOS for cardiopulmonary patients in Hong Kong’s older adult population. These findings highlight the need for hospitals to prepare in advance for extreme temperature events by implementing specific measures in terms of human resources and medical resources. In addition, the results provide valuable scientific evidence to support public health policies and inform hospital planning and management.

Abstract The Paris Agreement and the Special Report on Global Warming of 1.5 °C from the Intergovernmental Panel on Climate Change (IPCC) highlighted the potential risks of climate change across different global warming levels (GWLs). The increasing occurrence of extreme high-temperature events is linked to a warmer climate that is particularly prevalent in the Arabian Peninsula (AP). This study investigates future changes in temperatures and related extremes over AP, under four GWLs, such as 1.5 °C, 2.0 °C, 3.0 °C, and 4.0 °C, with three different Shared Socioeconomic Pathways (SSPs: SSP1-2.6, SSP2-4.5, and SSP5-8.5). The study uses high-resolution datasets of 27 models from the NASA Earth Exchange Global Daily Downscaled Projections of the Coupled Model Intercomparison Project Phase 6 (NEX-GDDP-CMIP6). The results showed that the NEX-GDDP-CMIP6 individual models and their multi-model means reasonably captured the extreme temperature events. The summer maximum and winter minimum temperatures are projected to increase by 0.11–0.67 °C and 0.09–0.70 °C per decade under the selected SSPs. Likewise, the projected temperature extremes exhibit significant warming with varying degrees across the GWLs under the selected SSPs. The warm temperature extremes are projected to increase, while the cold extremes are projected to decrease under all GWLs and the selected SSPs. Overall, the findings provide a comprehensive assessment of temperature changes over AP in response to global warming, which can be helpful in the development of climate adaptation and mitigation strategies.

The Paris Agreement and the Special Report on Global Warming of 1.5 °C from the Intergovernmental Panel on Climate Change (IPCC) highlighted the potential risks of climate change across different global warming levels (GWLs). The increasing occurrence of extreme high-temperature events is linked to a warmer climate that is particularly prevalent in the Arabian Peninsula (AP). This study investigates future changes in temperatures and related extremes over AP, under four GWLs, such as 1.5 °C, 2.0 °C, 3.0 °C, and 4.0 °C, with three different Shared Socioeconomic Pathways (SSPs: SSP1-2.6, SSP2-4.5, and SSP5-8.5). The study uses high-resolution datasets of 27 models from the NASA Earth Exchange Global Daily Downscaled Projections of the Coupled Model Intercomparison Project Phase 6 (NEX-GDDP-CMIP6). The results showed that the NEX-GDDP-CMIP6 individual models and their multi-model means reasonably captured the extreme temperature events. The summer maximum and winter minimum temperatures are projected to increase by 0.11–0.67 °C and 0.09–0.70 °C per decade under the selected SSPs. Likewise, the projected temperature extremes exhibit significant warming with varying degrees across the GWLs under the selected SSPs. The warm temperature extremes are projected to increase, while the cold extremes are projected to decrease under all GWLs and the selected SSPs. Overall, the findings provide a comprehensive assessment of temperature changes over AP in response to global warming, which can be helpful in the development of climate adaptation and mitigation strategies. [ABSTRACT FROM AUTHOR]

Temperature extremes exert a significant influence on terrestrial ecosystems, but the precise levels at which these extremes trigger adverse shifts in vegetation productivity have remained elusive. In this study, we have derived two critical thresholds, using standard deviations (SDs) of growing‐season temperature and satellite‐based vegetation productivity as key indicators. Our findings reveal that, on average, vegetation productivity experiences rapid suppression when confronted with temperature anomalies exceeding 1.45 SD above the mean temperature during 2001–2018. Furthermore, at temperatures exceeding 2.98 SD above the mean, we observe the maximum level of suppression, particularly in response to the most extreme high‐temperature events. When Earth System Models are driven by a future medium emission scenario, they project that mean temperatures will routinely surpass both of these critical thresholds by approximately the years 2050 and 2070, respectively. However, it is important to note that the timing of these threshold crossings exhibits spatial variation and will appear much earlier in tropical regions. Our finding highlights that restricting global warming to just 1.5°C can increase safe areas for vegetation growth by 13% compared to allowing warming to reach 2°C above preindustrial levels. This mitigation strategy helps avoid exposure to detrimental extreme temperatures that breach these thresholds. Our study underscores the pivotal role of climate mitigation policies in fostering the sustainable development of terrestrial ecosystems in a warming world. [ABSTRACT FROM AUTHOR]

The rise of extreme heat events and increase in heat stress under changing climate has been a major concern in recent periods. The present study has been undertaken to analyze temperature extremes and heat stress patterns over Eastern India during the period 1981–2020 for April, May, and June (AMJ). Six indices namely, Monthly maximum value of daily maximum temperature (TXx), Monthly maximum value of daily minimum temperature (TNx), Monthly minimum value of daily maximum temperature (TXn), Monthly minimum value of daily minimum temperature (TNn), Percentage of days when maximum temperature > 90th percentile (TX90p) and minimum temperature > 90th percentile (TN90p) have been utilized to assess the changes in temperature extremes. Furthermore, three heat stress indices (HSIs) namely, Humidex, Simplified Wet-Bulb Globe Temperature, and Apparent Temperature have been used to estimate and categorize heat stress levels. Mixed results with both increasing and decreasing trends over different parts of the study area have been observed during three months in case of TXx, TXn, TNx, and TNn. During AMJ, there has been amplification in the frequency of TX90p over coastal regions of West Bengal and Odisha in latest decades. Increasing TN90p frequency has been found over Sikkim, Bihar, and North Bengal while it has decreased over Chhattisgarh and Odisha. The frequency of strong heat stress has intensified over Gangetic West Bengal and Bihar during recent decades. Spatial coverage of strong stress has also gradually extended and the area under no stress has decreased during AMJ season. [ABSTRACT FROM AUTHOR]

This study addresses a regional research gap by analyzing summertime wet-bulb temperature (Tw) projections in South America (SA) and their implications for heatwaves in central-east Argentina (CEA). Tw emerges as a relevant variable to address the potential impact of humid and warm extremes under future climate conditions, while allowing comparison with more classical analyses based on dry-bulb temperature indices. The analyses presented in this work are based on outputs from Regional Climate Models provided by CORDEX (COordinated Regional climate Downscaling EXperiment) South America database. Tw increases in all SA stem from rising temperature and specific humidity at lower atmospheric layers. Projected Tw rise surpasses the expected maximum dry-bulb temperature (Tmax) increase across most of SA, exhibiting pronounced disparities in subtropical areas and intensifying further in CEA towards the century's end. Projected trends in Tw and minimum dry-bulb temperature (Tmin) show similarities across SA, except for a limited area within CEA where relatively larger Tw increases are expected. The frequency and intensity of heat extremes are also anticipated to increase in the coming years in SA. Noteworthy findings encompass projected increases in hot days, hot nights, and wet days, with the tropical region standing out for its pronounced projections. Remarkably, the number of wet days would rise significantly, followed by less prominent increases in the number of hot nights and days. Moreover, heightened persistence is expected for wet days compared to hot days and nights. A bivariate statistical analysis of heatwave projections in CEA reveals a transition towards warmer and more humid spells. This underscores the critical need to integrate air humidity conditions for accurate assessments of future health risks. Despite inherent uncertainties in climate change projections, consensus emerges on the direction of the expected changes, as well as on the urgency of limiting greenhouse gas emissions to mitigate the imminent threat of humid heatwaves in CEA. [ABSTRACT FROM AUTHOR]

In this work, we compare the rate of warming of summertime extreme temperatures (summer maximum value of daily maximum temperature; TXx) relative to the local mean (summer mean daily maximum temperature; TXm) over the Northern Hemisphere in observations and one set of large ensemble (LE) simulations. During the 1979–2021 historical period, observations and simulations show robust warming trends in both TXm and TXx almost everywhere in the Northern Hemisphere, except over the eastern U.S. where observations show a slight cooling trend in TXx, which may be a manifestation of internal variability. We find that the observed warming rate in TXx is significantly smaller than in TXm in North Africa, western North America, Siberia, and Eastern Asia, whereas the warming rate in TXx is significantly larger over the Eastern U.S., the U.K., and Northwestern Europe. This observed geographical pattern is successfully reproduced by the vast majority of the LE members over the historical period, and is persistent (although less intense) in future climate projections over the 2051–2100 period. We also find that these relative warming patterns are mostly driven by the local hydroclimate conditions. TXx warms slower than TXm in the hyper-arid, arid, semi-arid and moist regions, where trends in the partitioning of the turbulent surface fluxes between the latent and sensible heat flux are similar during regular and extreme hot days. In contrast, TXx warms faster than TXm in dry-subhumid regions where trends in the partitioning of the surface fluxes are significantly different between regular and extreme hot days, with a larger role of sensible heat flux during the extreme hot days.

The increasing temperatures and shifts in meteorological conditions have heightened the vulnerability of Bangladesh's densely populated regions, known for their high heat and humidity, to potential health hazards. While the Wet Bulb Globe Temperature (WBGT) is a widely acknowledged and robust measure for evaluating heat stress in various occupational and outdoor environments, its widespread application is impeded by the complexity of calculations, the substantial computational resources required, and the need for specialized expertise, particularly in developing nations. Therefore, this study aimed to develop simplified equations for estimating WBGT in Bangladesh using meteorological variables. This study applied Liljegren's model on high‐resolution reanalysis data of the European Centre for Medium‐Range Weather Forecasts (ERA5) to calculate WBGT from 1979 to 2021. Subsequently, linear and nonlinear regressions were used to derive simplified equations for estimating Liljegren WBGT in Bangladesh. The quadratic regression models offer simplified equations for WBGT estimation. The model with only temperature (Ta) as an input estimates WBGT with an R2 of 0.967 and an RMSE of 0.716, effectively capturing a significant portion of WBGT variability. The inclusion of solar radiation (SR) with Ta improved the performance, with an R2 of 0.996 and an RMSE of 0.242. The best parsimonious model, with an R2 of 0.986 and an RMSE of 0.471, is derived when wind speed is considered with Ta and SR inputs, achieving an R2 of 0.993 and an RMSE of 0.331. Comprehensive graphical and statistical analyses confirm the high accuracy of all models. The three‐input model notably demonstrates exceptional performance, attaining optimal values for critical metrics, including extreme WBGT. The results affirm the practical suitability of the derived models for accurate estimations of WBGT in Bangladesh. These equations provide simplified tools for assessing heat stress conditions, contributing to public health initiatives, occupational safety guidelines, and climate change adaptation strategies. [ABSTRACT FROM AUTHOR]

To cope with abiotic and biotic stressors, plants have developed mutualistic associations with beneficial soil microbes, but little is known about how extreme abiotic conditions impact on microbe‐induce resistance to insect herbivores.Extreme temperatures are often accompanied by extremes in plant water availability, which together reduce plant growth and change plant physiology. There are potential consequences for increasing plant susceptibility to biotic stresses, and this poses a real challenge for plant productivity.We evaluated how the effects of beneficial soil bacteria (Acidovorax radicis N35e) on barley plant growth and resultant resistance against aphid infestation (Sitobion avenae) were impacted by a single heatwave event across a plant water availability gradient. We also tested if timing of bacterial inoculation (before or after the temperature treatment) affected bacteria‐plant interactions on aphids.We found that heatwaves affected plant biomass allocation from above‐ground to below‐ground tissues. Inoculation with A. radicis led to reduction of aphid numbers, but depended on timing of inoculation, and led to stronger resistance when inoculations occurred closer to aphid infestation. Remarkably, microbe‐induced resistance against aphids was consistent across heatwave and water availability treatments.This study provides evidence that beneficial plant‐bacteria interactions may represent a potential solution for sustainable agricultural practices to enhance plant growth and response to insect pests under climate change. Future field trials should investigate the consistency of beneficial effects reported here for a better understanding of multispecies interactions in the context of global change. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Global warming and associated climate change impacts have posed major threats to this 21st century's world, especially for developing countries like India, given various socio‐economic factors. Considering the extensive spatial diversity of this warming‐induced climate changes, suitable region‐specific strategies must be adopted to combat its potential implications. Therefore, it becomes crucial to identify the places most exposed to this changing scenario. This study attempts to shed some light towards this by identifying futuristic "temperature‐based hotspots" across India through a comprehensive multimodel multiscenario analysis at various spatiotemporal scales. A new and more informative index named "Temperature‐based Hotspot Index (THIn)" is proposed for this purpose, which encapsulates various attributes of changing temperature, including its mean, variability and extremes (magnitude, frequency and severity) into a single metric. Bias‐corrected future‐projected temperature data from 14 state‐of‐the‐art general circulation models (GCMs) have been considered for the analysis, which are participating in the coupled model intercomparison project version 6 (CMIP6). The overall analysis identifies temperature‐based hotspots to span predominantly in the west, north and northeast parts of the country. On the other hand, the southern and eastern part of India along the eastern coast are found to be comparatively less exposed to temperature changes in future. Overall, we expect the findings of this study to be beneficial to plan and adopt suitable region‐specific management strategies to combat the challenging future in sufficient advance. [ABSTRACT FROM AUTHOR]

Extreme temperature events have increased in Iran in recent decades. In this research, we evaluate the performance of CMIP6-DCPP individual models and a multi-model ensemble (MME) from CMIP6-DCPP against observational data in Iran. We used the delta change factor (DCF) and the independence weighted mean (IWM) methods to correct the bias of individual models and generate the MME. Eighteen temperature indices recommended by ETCCDI were used to predict extreme temperatures in the near term by comparing the hindcast (1981–2019) and forecast (2021–2028) periods. The result shows that DCPP-MME performed well in simulating temperature over most parts of Iran. Positive anomalies in mean, minimum, and maximum temperatures are obvious in Iran in the next decade, which is amplified by the elevation. As a key result, the minimum temperature will increase at a higher rate than the maximum temperature, which will make a negative diurnal temperature range anomaly in most regions in the near-term period. The frequency and intensity of warm (cold) extremes would increase (decrease) in the upcoming years. Therefore, in mountainous and high-latitude regions of Iran, the coldest days and nights are getting warmer compared to the hottest days and nights. In addition, ice days and frost days decrease considerably by almost 15 and 11 days in the north of Iran, respectively. Tropical nights and summer days will increase in all regions, with their maxima in central and eastern arid regions. Also, warm spell duration with an increase of 14 days is very noticeable in the forecast period. [ABSTRACT FROM AUTHOR]

Background: Children are more vulnerable than adults to climate-related health threats, but reviews examining how climate change affects human health have been mainly descriptive and lack an assessment of the magnitude of health effects children face. This is the first systematic review and meta-analysis that identifies which climate health relationships pose the greatest threats to children. Objectives: We reviewed epidemiologic studies to analyse various child health outcomes due to climate change and identify the relationships with the largest effect size. We identify population-specific risks and provide recommendations for future research. Methods: We searched four large online databases for observational studies published up to 5 January 2023 following PRISMA (systematic review) guidelines. We evaluated each included study individually and aggregated relevant quantitative data. We used quantitative data in our meta-analysis, where we standardised effect sizes and compared them among different groupings of climate variables and health outcomes. [ABSTRACT FROM AUTHOR]

Terrestrial diatoms are widespread in a large variety of habitats and are regularly recorded in biocrusts. Although diatoms have long been known to live in terrestrial habitats, only a few studies have focused on their diversity of ecophysiology. Here we present a study on the ecophysiological performance of five terrestrial diatom cultures from biocrusts, which were collected in sand dunes of the German coast of the Baltic Sea. The sampling sites were selected along a gradient of human impacts on the dunes. The richness of diatom species, roughly estimated from permanent slides, was around 30 species per sampling site. The species abundance was calculated in the same way revealing a high proportion of broken diatom frustules. All diatom cultures established in the laboratory showed no photoinhibition and high oxygen production along a light gradient. The desiccation tolerance differed among the strains, with high recovery observed for Hantzschia abundans and Achnanthes coarctata and low to no recovery for Pinnularia borealis and Pinnularia intermedia. The maximum growth rate for most strains was between 25 and 30°C. These temperatures can be easily reached in their natural environments. Nevertheless, during short-term exposure to elevated temperatures, oxygen production was recorded up to 35°C. Interestingly, two of five diatom cultures (Hantzschia abundans and Pinnularia borealis) produced mycosporine-like amino acids. These UV-protective substances are known from marine diatoms but not previously reported in terrestrial diatoms. [ABSTRACT FROM AUTHOR]

Quantitative methods to pinpoint the origin of atmospheric temperature anomalies (T′) associated with heatwaves are pivotal for the construction of physically plausible synoptic storylines of heatwave formation and their evaluation in models. Here, we combine a Lagrangian T′ decomposition with concepts from moisture tracking techniques to identify where and when the principal physical processes generate T′ and to attribute these sources to synoptic weather systems. Applying this framework to near‐surface and free‐tropospheric T′ associated with the record‐shattering 2021 heatwave in the Pacific Northwest shows that ascending, diabatic air streams in North Pacific cyclones contribute more than 50% of free‐tropospheric T′, whereas near‐surface T′ is mainly produced by local subsidence and diabatic heating with only marginal upstream contributions. Since free‐tropospheric T′ facilitates near‐surface accumulation of locally produced T′ by rendering the atmosphere stable to moist convection, our findings corroborate the notion of top‐down induced heatwave formation fueled by upstream diabatic processes. Plain Language Summary: Heatwaves, characterized by strongly above normal air temperatures, are amongst the most severe weather related threats to human lives and economic activities. Understanding the processes causing heatwaves and evaluating their representation in climate models requires suitable quantitative methods to diagnose the process' contributions to temperature anomalies. While it is well established which physical processes can create positive temperature anomalies, that is, transport of air from climatologically warmer regions, warming of air as it is compressed in sinking motion, and heating, for example, by a hot surface, it remains challenging to diagnose where and when these processes create temperature anomalies. Here, we present a quantitative framework based on the tracking of air parcels that allows us to obtain this kind of information. Applying this method to a recent devastating heatwave in the Pacific Northwest, we show that even though the air at the surface acquired its temperature anomaly mainly by local heating, storms over the North Pacific contributed substantially to warming the air aloft. This anomalously warm air aloft, in turn, was a pre‐requisite for the extreme accumulation of heat near the surface by suppressing the formation of thunderstorms, which would have had a cooling effect. Key Points: Novel diagnostic framework quantifies sources of atmospheric temperature anomalies (T′) generated by principal physical processesUpstream warm conveyor belts (WCBs) contributed >50% of free‐tropospheric T′ and <15% of near‐surface T′ to the 2021 Pacific Northwest (PNW) heatwaveImportance of upstream sources of free‐tropospheric T′ corroborate top‐down induced formation of PNW heatwave fueled by WCBs [ABSTRACT FROM AUTHOR]

Global declines in abundance and diversity of insects are now well-documented and increasingly concerning given the critical and diverse roles insects play in all ecosystems. Habitat loss, invasive species, and anthropogenic chemicals are all clearly detrimental to insect populations, but mounting evidence implicates climate change as a key driver of insect declines globally. Warming temperatures combined with increased variability may expose organisms to extreme heat that exceeds tolerance, potentially driving local extirpations. In this context, heat tolerance limits (e.g., critical thermal maximum, CTmax) have been measured for many invertebrates and are often closely linked to climate regions where animals are found. However, temperatures well below CTmax may also have pronounced effects on insects, but have been relatively less studied. Additionally, many insects with out-sized ecological and economic footprints are colonial (e.g., ants, social bees, termites) such that effects of heat on individuals may propagate through or be compensated by the colony. For colonial organisms, measuring direct effects on individuals may therefore reveal little about population-level impacts of changing climates. Here, we use bumble bees (genus Bombus) as a case study to highlight how a limited understanding of heat effects below CTmax and of colonial impacts and responses both likely hinder our ability to explain past and predict future climate change impacts. Insights from bumble bees suggest that, for diverse invertebrates, predicting climate change impacts will require a more nuanced understanding of the effects of heat exposure and additional studies of carry-over effects and compensatory responses by colonies. [ABSTRACT FROM AUTHOR]

Abstract Quantitative methods to pinpoint the origin of atmospheric temperature anomalies (T′) associated with heatwaves are pivotal for the construction of physically plausible synoptic storylines of heatwave formation and their evaluation in models. Here, we combine a Lagrangian T′ decomposition with concepts from moisture tracking techniques to identify where and when the principal physical processes generate T′ and to attribute these sources to synoptic weather systems. Applying this framework to near‐surface and free‐tropospheric T′ associated with the record‐shattering 2021 heatwave in the Pacific Northwest shows that ascending, diabatic air streams in North Pacific cyclones contribute more than 50% of free‐tropospheric T′, whereas near‐surface T′ is mainly produced by local subsidence and diabatic heating with only marginal upstream contributions. Since free‐tropospheric T′ facilitates near‐surface accumulation of locally produced T′ by rendering the atmosphere stable to moist convection, our findings corroborate the notion of top‐down induced heatwave formation fueled by upstream diabatic processes.

Terrestrial diatoms are widespread in a large variety of habitats and are regularly recorded in biocrusts. Although diatoms have long been known to live in terrestrial habitats, only a few studies have focused on their diversity of ecophysiology. Here we present a study on the ecophysiological performance of five terrestrial diatom cultures from biocrusts, which were collected in sand dunes of the German coast of the Baltic Sea. The sampling sites were selected along a gradient of human impacts on the dunes. The richness of diatom species, roughly estimated from permanent slides, was around 30 species per sampling site. The species abundance was calculated in the same way revealing a high proportion of broken diatom frustules. All diatom cultures established in the laboratory showed no photoinhibition and high oxygen production along a light gradient. The desiccation tolerance differed among the strains, with high recovery observed for Hantzschia abundans and Achnanthes coarctata and low to no recovery for Pinnularia borealis and Pinnularia intermedia. The maximum growth rate for most strains was between 25 and 30°C. These temperatures can be easily reached in their natural environments. Nevertheless, during short-term exposure to elevated temperatures, oxygen production was recorded up to 35°C. Interestingly, two of five diatom cultures (Hantzschia abundans and Pinnularia borealis) produced mycosporine-like amino acids. These UV-protective substances are known from marine diatoms but not previously reported in terrestrial diatoms.

Studies about the role of urban characteristics in modifying the health effect of temperature extremes are still unclear. This study is aimed at quantifying the morbidity risk of infectious diarrhea attributable to temperature extremes and the modified effect of a range of city-specific indicators. Distributed lag non-linear model and multivariate meta-regression were applied to estimate fractions of infectious diarrhea morbidity attributable to temperature extremes and to explore the effect modification of city-level characteristics. Extreme heat- and extreme cold-related infectious diarrhea amounted to 0.99% (95% CI: 0.57–1.29) and 1.05% (95% CI: 0.64–1.24) of the total cases, respectively. The attributable fraction of temperature extremes on infectious diarrhea varied between southern and northern China. Several city characteristics modified the association of extreme cold with infectious diarrhea, with a higher morbidity impact related to increased water consumption per capita and decreased latitude. Regions with higher levels of latitude or GDP per capita appeared to be more sensitive to extreme hot. In conclusion, exposure to temperature extremes was associated with increased risks of infectious diarrhea and the effect can be modified by urban characteristics. This finding can inform public health interventions to decrease the adverse effects of temperature extremes on infectious diarrhea. [ABSTRACT FROM AUTHOR]

In this research, the trend of spatial changes in extreme indices of temperature related to the health and agriculture sectors such as the number of frost days, number of summer days, number of icing days, number of tropical nights, growing season length, diurnal temperature range, cold spell duration index, and warm spell duration index were investigated for 54 synoptic stations throughout Iran for observational (1976-2005) and future (2025-2054) periods. Daily maximum and minimum temperature data of three regional climate models namely, CCSM4, MPI-ESM-MR, and NORESM1-ME from the CORDEX project under RCP4.5 and RCP8.5 scenarios were downscaled for each station using a developed multiscale bias correction method. Then, trends and changes of extreme temperature indices were investigated using Mann-Kendall and Sen’s trend line slope methods. The results indicated that the warm indices such as the number of summer days and tropical nights indices have had a positive trend at most stations in both observational and future periods. In contrast, cold indices like the number of frost days have had a decreasing trend in most stations. The results of cold and warm spell duration indices showed that most stations have had no trend for both periods. The growing season length has increased in more than 60% of stations (45% having a significant trend) mainly located in the northern, northwestern, and western regions of the country. Based on the results, it can be concluded that without considering thoughtful climate adaptation measures, some parts of the country may face health risks and limited habitability and agriculture in the future.

Global declines in abundance and diversity of insects are now well-documented and increasingly concerning given the critical and diverse roles insects play in all ecosystems. Habitat loss, invasive species, and anthropogenic chemicals are all clearly detrimental to insect populations, but mounting evidence implicates climate change as a key driver of insect declines globally. Warming temperatures combined with increased variability may expose organisms to extreme heat that exceeds tolerance, potentially driving local extirpations. In this context, heat tolerance limits (e.g., critical thermal maximum, CTmax) have been measured for many invertebrates and are often closely linked to climate regions where animals are found. However, temperatures well below CTmax may also have pronounced effects on insects, but have been relatively less studied. Additionally, many insects with out-sized ecological and economic footprints are colonial (e.g., ants, social bees, termites) such that effects of heat on individuals may propagate through or be compensated by the colony. For colonial organisms, measuring direct effects on individuals may therefore reveal little about population-level impacts of changing climates. Here, we use bumble bees (genus Bombus) as a case study to highlight how a limited understanding of heat effects below CTmax and of colonial impacts and responses both likely hinder our ability to explain past and predict future climate change impacts. Insights from bumble bees suggest that, for diverse invertebrates, predicting climate change impacts will require a more nuanced understanding of the effects of heat exposure and additional studies of carry-over effects and compensatory responses by colonies.

The observation facts of trend and variability are estimated for a century‐long timescale, as well as some possible attributions affecting temperature extremes over Beijing‐Tianjin‐Hebei region. In this paper, the new constructed daily maximum and minimum temperature series during the last 100 years in situ stations of Beijing, Tianjin and Baoding city are used, and two 30‐year baseline climatology of 1961–1990 and 1980–2010 are both used in calculating extreme temperature events. The results indicate that there are long‐lasting, frequent and serious extreme warming over Beijing‐Tianjin‐Hebei region, especially for extreme low temperature, with larger declining trends (at 5% significance) from 1981 to 2010 baseline than those from 1961 to 1990 baseline. And from a statistical perspective, El Niño decay years and surface sea temperature (SST) anomalies at some typical ocean regions of the Arabian Sea and the Bengal Bay on the northern Indian Ocean, the Western Pacific and the Mid Atlantic, Southern Indian Ocean and around 45°–85°E, 68°–82°N on the southwest Arctic Ocean can be used as the warning signals denoting extreme warming over Beijing‐Tianjin‐Hebei region. Additionally, urbanization has a significant (at 5% significance) effect on extreme warming over Beijing‐Tianjin‐Hebei region since 1979, with 24.3% warming contribution for annual minimum temperature. [ABSTRACT FROM AUTHOR]

The study investigated the impact of temperature extremes on carbon emissions (CE) from crop production. (1) Background: Many scholars have studied climate extremes. However, the research on the relationship between temperature extremes and CE is not extensive, which deserves attention. (2) Methods: The study adopted a fixed-effect model to analyze the impact of temperature extremes on CE from crop production, and the moderating effect was tested using total factor productivity (TFP) in agriculture. (3) Results: Temperature extremes in Hebei Province were mainly reflected in a decline in the cold day index (TX10p) and a rise in the warm spell duration index (WSDI) and the number of summer days (SU25). Additionally, TX10p was positively correlated with CE. For every 1% reduction in TX10p, CE dropped by 0.237%. There was no significant correlation between WSDI and CE. Finally, the agricultural TFP had a significant moderating effect on CE, with each 1% increase resulting in a corresponding 0.081% decrease in CE. (4) Conclusions: The results indicated a warming trend in Hebei Province, which resulted in a decrease in the number of winter days, and reduced CE from crop production. The improvement of input efficiency in agricultural production factors helped moderate the CE. [ABSTRACT FROM AUTHOR]

We examine impacts of the Madden–Julian Oscillation (MJO) on Australian springtime temperatures and extremes, explore the mechanisms behind the teleconnections, and assess their prediction in retrospective forecasts using the Bureau of Meteorology's ACCESS-S1 dynamical forecast system. The MJO incites strong and significant warming across southern Australia in phases 2, 3 and 4 when its active convection propagates over the Indian Ocean and Maritime Continent. The heat signal appears strongest in south-eastern Australia during MJO phases 2 and 3 in the vicinity of a deep anticyclonic anomaly which brings warmer airflow to south-western Australia while promoting shortwave radiative heating in the southeast. This occurs as part of a Rossby wave train that emanates from the Indian Ocean and disperses across the Southern Hemisphere along a great circle route towards South America, in response to MJO convective heating on the equator. Importantly, we show the wave train emerges from the divergent outflow from anomalous MJO convection, rather than from the Rossby waves that exist within the MJO's baroclinic structure. Feedbacks between transient eddies and the low frequency flow to the south of Australia and southeast of South America reinforce the wave train in phases 1–3 but act against it during its demise in phase 4. The MJO is a source of subseasonal predictability of springtime heat and cold events over southern Australia in ACCESS-S1 at lead times of 2–4 weeks, yet there remains room for improvement in the model's depiction of the MJO and its teleconnection to the Southern Hemisphere. [ABSTRACT FROM AUTHOR]

Climate extremes pose threats to lives and properties. It is therefore critical to assess the dynamics of climate extremes in the future. Knowledge of the appropriate models to be used for projection helps reduces uncertainties in model projections. The study assesses the evolution of 8 extreme temperature indices over the Volta Basin for the 1985–2014 period. Consequently, the ability of 40 Coupled Model Intercomparison Project Phase 6 (CMIP6) models in reproducing these extremes is assessed. The biases and the M-scores of the annual spatial distribution of indices are determined. It is observed that the temperature extremes are frequent and profound in the Sahel, indicating that the Sahel is susceptible to extreme temperature changes. The warm indices showed positive trends, while the cold indices mainly showed negative trends. Most of the models had difficulty reproducing the climatologies of the indices. However, the CMCC-ESM2, MPI-ESM-1-2-HAM, MIROC6, and AWI-CM-1-1-MR reproduced the TNN, TNX, TXN, and TXX well while the MIROC6, MRI-ESM2-0, INM-CM4-8, and MIROC6 showed robust performance in reproducing the TN10P, TN90P, TX10P, and TX90P respectively. Poor performance of models may be due to poor simulation of sub-grid features such as vegetation cover, and clouds as a result of coarse grid sizes. Warming of the basin poses a significant impact on agriculture, drought occurrence, and seasonal to annual scale precipitation distribution. Southern sections of the basin may be vulnerable to temperature-related extremes as a result of deforestation and urbanization. [ABSTRACT FROM AUTHOR]

Variability of extreme temperatures has an important influence on sensitive ecosystem and human activities on the Tibetan Plateau (TP). Nevertheless, the uncertainties of different El Niño-Southern Oscillation (ENSO) effects on extreme temperatures over the TP are poorly understood. Thus, this study focuses on variations in temperature extremes across the TP during 1980–2020 based on the daily maximum temperature and minimum temperature. We quantitatively examine the effects of different ENSO phases and related large-scale atmospheric circulation anomalies on the changes in temperature extremes according to different ENSO phases. The results show that the number of extreme cold events decreased significantly on the TP, while the number of extreme warm events increased significantly from 1980 to 2020. Moreover, our results suggest that the response of temperature extremes differs between the Eastern Pacific (EP) and Central Pacific (CP) ENSO. In particular, EP El Niño episodes result in more extreme cold events (r = 0.36, P < 0.01), whereas the influence of the CP El Niño episodes on the temperature extreme over the TP is weak. The correlation coefficients between the CP ENSO index and daily minimum temperature (daily maximum temperature) are 0.46 (0.49). In addition, the developing and decaying phases of ENSO had an essential influence on temperature extreme variability on the TP through the modulation of large-scale atmospheric circulation anomalies. Sea surface temperature during the different ENSO phases induced a Walker circulation anomaly in the tropical Pacific and ascending motion over the tropical Indian Ocean, which contributes to the generation of the anomalies of wind and geopotential height around the TP, inducing non-uniform responses of temperature extremes over the TP. In conclusion, ENSO is a critical factor that influences temperature extremes on the TP. This study provides some insight into understanding the dynamics of regional extreme temperatures during different ENSO episodes. [ABSTRACT FROM AUTHOR]

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In the mid‐latitudes, the strongly meandering jet stream has contributed to worldwide weather patterns and climate variations. However, the shape variations of the jet and its climatic impacts remain unclear. In this study, we introduced an ellipse‐fitting technique to fit the high‐value wind speeds and identified the location, shape, and strength variations of the winter‐averaged North Pacific jet (NPJ). Particularly, this method has the advantage of objectively detecting the shape variations of the NPJ, including the area and orientation. Focused on the NPJ shape, the area and orientation variations are generally out‐of‐phase, leading to a large‐straight jet and a small‐tilted jet. The shape variation of the NPJ is highly linked to the variations in both mean and extreme temperatures in winter over East Asia and North America. Associated with the small‐tilted NPJ, northern East Asia and northern North America frequently suffer from warm and cold events in winter, respectively, while associated with the large‐straight NPJ, the patterns are almost opposite but with an asymmetric distribution to the small‐tilted NPJ. The distribution of the 300 hPa wind speed anomalies shows a spatial‐asymmetric feature at the exit and entrance of the NPJ. Large positive (negative) anomalies and the poleward (equatorward) shift at the NPJ exit and locations downstream (170°E−140°W) act in combination on the formation and maintenance of the large‐straight (small‐tilted) jet, which may be strongly connected with the sea surface temperature variations and synoptic‐scale transient eddy activities there. Our findings would be helpful in providing potential indicators of temperature variations. Plain Language Summary: The shape of the upper‐level jet stream is closely associated with weather and climate variations, which is not clearly understood yet. In this study, we introduced an ellipse‐fitting technique to fit high‐value wind speeds and identify the location, shape, and strength variations of the North Pacific jet (NPJ). This method has the advantage of objectively detecting characteristics of the jet stream, particularly for shape variations. The shape variations of the NPJ are closely linked to the variations both in winter mean and extreme temperature, particularly over East Asia and North America. Associated with the small‐tilted NPJ, warm events would more frequently occur in the northern part of East Asia, while cold events would easily affect northern North America. Sea surface temperature anomalies and the increased presence of surface high and low‐pressure systems around the jet exit region may have a strong connection with the different structures of the NPJ. Our findings would be helpful in providing a potential indicator of temperature variations. Key Points: An ellipse‐fitting technique has been introduced to detect the jet stream automatically and objectivelyPrimary combinations of the North Pacific jet's (NPJ's) shape include a large‐straight and small‐tilted jetVariations in the NPJ's shape are highly linked to out‐of‐phase variations in temperature extremes over East Asia and North America [ABSTRACT FROM AUTHOR]

Changes in the frequency of temperature extremes are often attributed to global warming. The recent availability of near‐surface temperature data records from reference networks, such as the U.S. Climate Reference Network (USCRN), enables the quantification of measurement uncertainties. Within an activity of the Copernicus Climate Change Service, the estimation of the measurement uncertainty has been provided for USCRN temperature data, using metadata made available by the National Oceanic and Atmospheric Administration (NOAA). In this paper, four climate extreme indices (Frost Days, Summer Days, Ice Days, Tropical Nights) and the related uncertainties are calculated for the period 2006–2020 from the USCRN data set and compared with traditional indices. Moreover, the asymmetric USCRN measurement uncertainties are propagated to estimate the uncertainties of climate indices. The comparison shows expanded uncertainties homogeneously distributed with the latitude and typically within 15 days per year for Frost Days and within 10 days for Ice Days, while smaller uncertainties are estimated for Summer Days and Tropical Nights, with values typically within six to seven days per year. Positive uncertainties are typically larger than negative ones for all the indices. The values of Frost and Ice Days with the related uncertainties for USCRN have also been compared with the corresponding values calculated from reanalyses data, showing differences typically within 60 days for median values, quite often smaller than USCRN and inconsistent within the related uncertainties, Overall, the results show that USCRN measurement uncertainties increase confidence in the estimation of climate extreme indices and decisions for adaptation. Plain Language Summary: The relationship between the intensity and frequency of extremes and climate change as well as their attribution to human activities is fundamental for improving the assessment of risk and the elaboration of adaptation strategies. Temperature extremes are often reported and estimated using observations or model data using indices, which are widely adopted in the research community and by decision‐makers. However, the number of temperature extremes is quantified assuming input observations as perfect, whereas these are always affected by uncertainties due to instrumental noise and systematic effects that cannot be always properly accounted for. This also implies that climate extreme indices may under or over‐represent the number of temperature extremes. The advent of reference measurement networks, as well as the overall increase in observational data quality due to recent technological improvements, allows us to quantify measurement uncertainties in detail. In this paper, temperature extremes over the US are estimated from near‐surface temperature measurements provided by the USCRN network in the period 2006–2020 with related uncertainties. The use of uncertainty illustrates the range of values that climate extreme indices may assume. Possible sources of uncertainties and comparisons with data from atmospheric reanalysis are also discussed. Key Points: An extensive assessment of uncertainties for four climate extreme indices is provided using reference near‐surface temperaturesEstimate uncertainties of climate indices for reanalysis validation and quantification of extremes by propagating measurement uncertaintiesUSCRN traceable measurements with quantified uncertainties increase confidence in estimating extreme indices and decisions for adaptation [ABSTRACT FROM AUTHOR]

Addressing the impacts of climate change has become a global public crisis and challenge. China is characterized by a complex and diverse topography and vast territory, which makes it worthwhile to explore the differential impacts of climate change on urban electricity consumption in different zones and economic development conditions. This study examines the differential impact of climate factors on urban electricity consumption in China based on monthly panel data for 282 prefectures from 2011 to 2019 and projects the potential demand for future urban electricity consumption under different climate change scenarios. The results show that (1) temperature changes significantly alter urban electricity consumption, with cooling degree days (CDD) and heating degree days (HDD) contributing positively to urban electricity consumption in areas with different regional and economic development statuses, with elasticity coefficients of 0.1015–0.1525 and 0.0029–0.0077, respectively. (2) The temperature-electricity relationship curve shows an irregular U-shape. Each additional day of extreme weather above 30 °C and below −12 °C increases urban electricity consumption by 0.52% and 1.52% in the north and by 2.67% and 1.32% in the south. Poor cities are significantly more sensitive to extremely low temperatures than rich cities. (3) Suppose the impacts of climate degradation on urban electricity consumption are not halted. In that case, the possible Shared Socioeconomic Pathways 1-1.9 (SSP1-1.9), SSP1-2.6, and SSP2-4.5 will increase China's urban electricity consumption by 1621.96 billion kWh, 2960.87 billion kWh, and 6145.65 billion kWh, respectively, by 2090. Finally, this study makes some policy recommendations and expectations for follow-up studies. [ABSTRACT FROM AUTHOR]

Atmospheric reanalysis products offer high-resolution and long-term gridded datasets that can often be used as an alternative or a supplement to observational data. Although more accessible than typical observational data and deemed fit for climate change studies, reanalysis data can show biases resulting from data assimilation approaches. Thus, a thorough evaluation of the reanalysis product over the region and metric of study is critical. Here, we evaluate the performance of the latest generation of ECMWF reanalysis, ERA5, in simulating mean and extreme temperatures over Australia for 1979–2020 versus high-quality gridded observations. We find ERA5 generally simulates maximum and minimum temperatures reasonably well (mean bias ~1.5 °C), even though it underestimates/overestimates the daily maximum/minimum temperatures, leading to a cold bias for Tmax and a warm bias for Tmin. ERA5 also underestimates the decadal warming trend in both Tmax and Tmin compared to the observations. Furthermore, ERA5 struggles to simulate the temporal variability of Tmin, leading to a markedly worse skill in Tmin than Tmax. In terms of extreme indices, ERA5 is skilled at capturing the spatial and temporal patterns and trends of extremes, albeit with the presence of biases in each index. This can partially be attributed to the warm bias in the minimum temperature. Overall, ERA5 captures the mean and extreme temperature indices over the Australian continent reasonably well, warranting its potential to supplement observations in aiding climate change-related studies, downscaling for boundary conditions, and climate model evaluation. [ABSTRACT FROM AUTHOR]

Rice is currently benefiting from climate warming in Northeast China, but whether such positive effect will continue in the future remains unknown. Here, we evaluate the impacts of individual and combined climate variables on rice yields in Northeast China during 1980–2015. Results show that there is 10% yield increase induced by climate change in Northeast China since 1980. At present, the reduced chilling results in 5.4% yield increase (approximately 28,000 tons) and the higher growing degree-day contributes to 4.6% yield increase (approximately 24,000 tons), while the high-temperature extreme reduced yield by 0.054% (approximately 280 tons). However, with continuous warming, the harmful impact of such high-temperature extreme will outweigh other positive climate effects when the temperature increases by 3.36 °C. Therefore, high-temperature extremes cannot be ignored despite their influence on rice yield being quite limited at present in Northeast China. Climate change mitigation and heat tolerance breeding are thus necessary for rice production in Northeast China. [ABSTRACT FROM AUTHOR]

Extreme climate events can pose huge threats to human safety and industrial and agricultural production. Therefore, investigating the time of emergence (TOE) of climate extremes is essential to policymakers, especially residents suffering from related climate disasters. However, there is still a lack of work focused on the TOE of climate extremes over the whole global land and aggregated climate subtypes. Here, we employed phase 5 of the Coupled Model Intercomparison Project (CMIP5) multi-models to calculate the TOE of 27 widely used Expert Team for Climate Change Detection and Indices (ETCCDI) indices for the sake of analyzing the intensity, frequency, and duration of extreme temperature and extreme precipitation characteristics comprehensively based on Köppen-Geiger climate classification. We found the temperature indices change prior to the precipitation indices in general, and are more uniformly in spatial distributions of TOE. Regionally, the warming and wetting trends are obvious in Tropical areas. Arid areas are likely to witness tiny changes for most precipitation indices. Temperate areas are the most similar climate subtype to the mean state of the global land. The substantially earlier TOE of precipitation indices in Continental and Polar areas highlights the need for an early warning system. The findings of this study will help policymakers take targeted preventive measures to deal with specific extreme events in an adaptation to local conditions.

This study focuses on potential impacts of climate change on the early spring (March-April) temperature and its extremes in the mid-latitudes of North America, discriminated between the 1.5 °C and 2 °C levels of global warming, as projected by a suit of numerical experiments. The results suggest relatively mild seasonal average warming (0.25 °C-1.5 °C), but also an intensification of both warm and cold temperature extremes. The derived changes feature much stronger warming over the West of the United States and weak to no warming to the East, which is congruent with the ventilating effect of the intensified northerly wind over central Canada and the East of the United States. The intensified northerly component of the mid-latitude jet is likely a contributing factor to the derived increased seasonal variability of March-April temperatures over parts of Manitoba and Ontario in Canada, and the Midwest of the United States. The projected changes in temperature extremes agree to some extent with the previous studies: Warm extremes intensify especially over southern mid-latitudes, while cold extremes are weakening over the north mid-to high-latitudes. However, high-resolution simulations with the Community Atmospheric Model 5 (CAM5) indicate much sharper spatial gradients, which translate into higher magnitudes and also more complex patterns of changes. Particularly, cold extremes feature not only reductions north of ∼45°N latitudes, but also a very strong intensification of cold extremes (by-4 °C for 20 year return values) in the band 25°-45°N, centered in the Midwest of the United States. While general warming and intensification of the warm extremes may accelerate the arrival of early spring, the intensifying cold extremes may increase the risk of early spring frost damage, and hence may yield a profound impact on the regional agriculture of North America. Combined with reliable information on expected temperature variability at interannual-to-decadal timescales, the background longer-term projections can help inform decision makers in the food security sector.

The cold regions of China (CRC) are important and vulnerable freshwater recharge areas on land, and any changes in them are related to the survival of millions of people in East Asia. However, for nearly half a century, in cold regions, the extreme temperature response to global warming is still poorly understood. In this study, we systematically studied the temperature extreme changes in cold regions of China since 1961 and discussed the possible circulation factors in detail. The results showed that 1) the warming magnitudes in cold nights and warm nights are greater than those in cold days and warm days, and decreases in cold nights and cold days and increases in warm days and warm nights appeared in almost all of cold regions of China. Most of the temperature indices displayed the largest magnitudes of warming in winter. 2) Spatially, for most of the temperature extremes, the stations located at Qinghai–Tibet Plateau (TPC) and Northwest China (NWC) showed a larger warming trend than that shown by the station at Northeast China (NEC). 3) The responses of temperature extremes at different cold regions to each circulation index are variable. Atlantic Multidecadal Oscillation (AMO) has a significant relationship with almost all the indices in cold regions of China. Almost all the temperature extremes of TPC and NWC showed closely relationship with the North Atlantic Oscillation (NAO), especially for diurnal temperature range (DTR), daily maximum temperature, and the cold extremes. Multivariate ENSO Index (MEI) is significantly related to most the temperature indices of Northwest China and Northeast China. However, MEI has a significant impact on only TPC’s diurnal temperature range and warmest night (TNx). 4) Atlantic Multidecadal Oscillation displayed significant relationships with most the temperature extremes in every season in cold regions of China. However, the summer and winter MEI and the summer and winter North Atlantic Oscillation showed significant impacts on only diurnal temperature range, daily minimum temperatures (TNm), and TNx.