Human contribution to the European heatwave of 2003

Machine learning-based extreme event attribution

The observed increase in extreme weather has prompted recent methodological advances in extreme event attribution. We propose a machine learning-based approach that uses convolutional neural networks to create dynamically consistent counterfactual versions of historical extreme events under different levels of global mean temperature (GMT). We apply this technique to one recent extreme heat event (southcentral North America 2023) and several historical events that have been previously analyzed using established attribution methods. We estimate that temperatures during the southcentral North America event were 1.18° to 1.42°C warmer because of global warming and that similar events will occur 0.14 to 0.60 times per year at 2.0°C above preindustrial levels of GMT. Additionally, we find that the learned relationships between daily temperature and GMT are influenced by the seasonality of the forced temperature response and the daily meteorological conditions. Our results broadly agree with other attribution techniques, suggesting that machine learning can be used to perform rapid, low-cost attribution of extreme events.

Observed flash drought to persist in future over southern Africa

Southern Africa has experienced multiple occurrences of drought episodes, which is projected to persist in the future, considering all climate scenarios. Despite the documented change in a meteorological, agricultural, and hydrological drought situation in the region, few studies are yet to explore the changes in flash drought (hereafter; FD), which is characterized by a rapid reduction in root-zone soil moisture and more substantial intensification in few days to weeks. Here, we analyze the observed FD and related underlying drivers during the past 34 years. Also, we estimate the future changes in FD using the severity-duration magnitude matrix under the middle of the road (SSP2-4.5) and business as usual (SSP5-8.5), scenario. Lastly, the study investigates the role of anthropogenic warming using the fraction of attributable risk (FAR) approach and possible bivariate return periods of FD events. Our results demonstrate that the region has experienced multiple occurrences up to 72 pentads from 1980 to 2014. Underlying mechanisms revealed the compounding influence of Vapor Pressure Deficit (VPD), Potential Evapotranspiration (PET), and precipitation deficit that have a significant impact on the abrupt onset and rapid intensification of FD events and other hot extremes over the SAF region. Under a high emission scenario, the region will experience FD duration lasting for 30 days with >40 % severity projected to impact the region. Anthropogenic climate change and land use and land cover changes remain the most dominant drivers altering the FD events over the SAF region. The return period of FD events under the SSP5-8.5 scenario shows that the SAF region will witness multiple FD events of up to 80 pentads in the far future. These findings reinforce the need to limit the emission of greenhouse gases. Sustained warming of the climate will exacerbate the extreme events and other compounding factors, thus affecting the livelihoods of humans and life-supporting strata.

Land use land cover and land surface temperature changes and their relationship with human modification in Islamabad Capital Territory, Pakistan

Human activities are altering the existing patterns of Land Use Land Cover (LULC) and Land Surface Temperature (LST) on a global scale. However, long-term trends of LULC and LST are largely unknown in many remote mountain areas such as the Karakorum. . The objective of our study therefore was to evaluate the historical changes in land use and land cover (LULC) in an alpine environment located in Islamabad Capital Territory, Pakistan. We used Landsat satellite pictures (namely Landsat 5 TM and Landsat 8 OLI) from the years 1988, 2002, and 2016 and applied the Maximum Likelihood Classification (MLC) approach to categorize land use classes. Land Surface Temperatures (LST) were calculated using the thermal bands (6, 10, and 11) of Landsat series data. The correlation between the Human Modification Index (HMI) and LULC as well as LST was evaluated by utilizing data from Google Earth Engine (GEE). Over the study period, the urbanized area increased by 9.94%, whilst the agricultural and bare soil areas decreased by 3.81% and 3.94%, respectively. The findings revealed a significant change in the LULC with a decrease of 1.99% in vegetation. The highest LST class exhibited a progressive trend, with an increase from 12.27% to 48.48%. Based on the LST analysis, the built-up area shows the highest temperature, followed by the barren, agricultural, and vegetation categories. Similarly, the HMI for different LST categories indicates that higher LST categories have higher levels of human alteration compared to lower LST categories, with a strong correlation (R-value = 0.61) between HMI and LST. The findings can be utilized to promote sustainable urban management and for biodiversity conservation efforts. The work also has the potential of utilizing it to protect delicate ecosystems from human interference and to formulate strategies and regulations for sustainable urban growth, including aspects of land utilization and zoning, reduction of urban heat stress, and urban infrastructure.

Heatwave attribution based on reliable operational weather forecasts

The 2021 Pacific Northwest heatwave was so extreme as to challenge conventional statistical and climate-model-based approaches to extreme weather attribution. However, state-of-the-art operational weather prediction systems are demonstrably able to simulate the detailed physics of the heatwave. Here, we leverage these systems to show that human influence on the climate made this event at least 8 [2-50] times more likely. At the current rate of global warming, the likelihood of such an event is doubling every 20 [10-50] years. Given the multi-decade lower-bound return-time implied by the length of the historical record, this rate of change in likelihood is highly relevant for decision makers. Further, forecast-based attribution can synthesise the conditional event-specific storyline and unconditional event-class probabilistic approaches to attribution. If developed as a routine service in forecasting centres, it could provide reliable estimates of human influence on extreme weather risk, which is critical to supporting effective adaptation planning.

Associations between heat wave during pregnancy and term birth weight outcomes: The PARIS birth cohort

BACKGROUND

Climate change will make extreme weather events more frequent in the 21st century. Extreme ambient temperatures during the prenatal period have been associated with adverse pregnancy outcomes such as preterm birth. It is unclear, however, whether heat waves during pregnancy impact fetal growth in apparently healthy term newborns.

OBJECTIVES

We aimed to investigate associations between heat wave during pregnancy and birth weight outcomes in term newborns from the PARIS birth cohort, and to explore meteorological conditions and air pollution as possible intermediate factors.

METHODS

We examined data on 3,359 newborns born between 37 and 42 weeks in Paris, France, between 2003 and 2006. Associations of maternal exposure to heat wave (during whole pregnancy and each trimester) with birth weight and small for gestational age (SGA) at term were studied using linear and logistic regression models adjusted for potential confounders. Maternal characteristics were investigated as possible modifiers. We explored the mediating role of ambient temperature, relative humidity, and air pollution levels in the relationship between heat wave during the first trimester and term SGA.

RESULTS

Mothers who were pregnant during the 2003 French heat wave (n = 506, 15 %) were more likely to have a term SGA baby (aOR = 2.70; 95 %CI: 1.38, 5.28) compared to mothers who did not experience heat wave during pregnancy. The association was stronger when heat wave occurred during the first trimester (aOR = 4.18; 95 %CI: 1.69, 10.35). Primiparous women were identified as more vulnerable than multiparous women. Average ambient temperature and air quality index explained about 36 % and 56 % of the association between heat wave during the first trimester and term SGA, respectively.

CONCLUSIONS

This study suggests prenatal exposure to heat wave, especially during the first trimester, may adversely affect fetal growth of term newborns, which could be explained by both increasing ambient temperatures and worsening air quality.

Science of forests and floods: The quantum leap forward needed, literally and metaphorically

A century of research has generated considerable disagreement on the effect of forests on floods. Here we call for a causal inference framework to advance the science and management of the effect of any forest or its removal on flood severity and frequency. The causes of floods are multiple and chancy and, hence, can only be investigated via a probabilistic approach. We use the stochastic hydrology literature to infer a blueprint framework which could guide future research on the understanding and prediction of the effects of forests on floods in environments where rain is the dominant form of precipitation. Drawing parallels from other disciplines, we show that the introduction of probability in forest hydrology could stimulate a gestalt switch in the science of forests and floods. In light of increasing flood risk caused by climate change, this probabilistic framework can help policymakers develop robust forest and water management plans based on a defensible and clear understanding of floods.

Twenty-first-century demographic and social inequalities of heat-related deaths in Brazilian urban areas

Population exposure to heat waves (HWs) is increasing worldwide due to climate change, significantly affecting society, including public health. Despite its significant vulnerabilities and limited adaptation resources to rising temperatures, South America, particularly Brazil, lacks research on the health impacts of temperature extremes, especially on the role played by socioeconomic factors in the risk of heat-related illness. Here, we present a comprehensive analysis of the effects of HWs on mortality rates in the 14 most populous urban areas, comprising approximately 35% of the country's population. Excess mortality during HWs was estimated through the observed-to-expected ratio (O/E) for total deaths during the events identified. Moreover, the interplay of intersectionality and vulnerability to heat considering demographics and socioeconomic heterogeneities, using gender, age, race, and educational level as proxies, as well as the leading causes of heat-related excess death, were assessed. A significant increase in the frequency was observed from the 1970s (0-3 HWs year-1) to the 2010s (3-11 HWs year-1), with higher tendencies in the northern, northeastern, and central-western regions. Over the 2000-2018 period, 48,075 (40,448-55,279) excessive deaths were attributed to the growing number of HWs (>20 times the number of landslides-related deaths for the same period). Nevertheless, our event-based surveillance analysis did not detect the HW-mortality nexus, reinforcing that extreme heat events are a neglected disaster in Brazil. Among the leading causes of death, diseases of the circulatory and respiratory systems and neoplasms were the most frequent. Critical regional differences were observed, which can be linked to the sharp North-South inequalities in terms of socioeconomic and health indicators, such as life expectancy. Higher heat-related excess mortality was observed for low-educational level people, blacks and browns, older adults, and females. Such findings highlight that the strengthening of primary health care combined with reducing socioeconomic, racial, and gender inequalities represents a crucial step to reducing heat-related deaths.

Impacts of climate change on the fate of contaminants through extreme weather events

The direct impacts of climate change involve a multitude of phenomena, including rising sea levels, intensified severe weather events such as droughts and flooding, increased temperatures leading to wildfires, and unpredictable fluctuations in rainfall. This comprehensive review intends to examine firstly the probable consequences of climate change on extreme weather events such as drought, flood and wildfire. This review subsequently examines the release and transformation of contaminants in terrestrial, aquatic, and atmospheric environments in response to extreme weather events driven by climate change. While drought and flood influence the dynamics of inorganic and organic contaminants in terrestrial and aquatic environments, thereby influencing their mobility and transport, wildfire results in the release and spread of organic contaminants in the atmosphere. There is a nascent awareness of climate change's influence of climate change-induced extreme weather events on the dynamics of environmental contaminants in the scientific community and decision-making processes. The remediation industry, in particular, lags behind in adopting adaptive measures for managing contaminated environments affected by climate change-induced extreme weather events. However, recognizing the need for assessment measures represents a pivotal first step towards fostering more adaptive practices in the management of contaminated environments. We highlight the urgency of collaboration between environmental chemists and climate change experts, emphasizing the importance of jointly assessing the fate of contaminants and rigorous action to augment risk assessment and remediation strategies to safeguard the health of our environment.

Impacts of compounding drought and heatwave events on child mental health: insights from a spatial clustering analysis

BACKGROUND

Concurrent heatwave and drought events may have larger health impacts than each event separately; however, no US-based studies have examined differential mental health impacts of compound drought and heatwave events in pediatric populations.

OBJECTIVE

To examine the spatial patterns of mood disorders and suicide-related emergency department (ED) visits in children during heatwave, drought, and compound heatwave and drought events. We tested whether the occurrence of compound heatwave and drought events have a synergistic (multiplicative) effect on the risk of mental health related outcomes in children as compared to the additive effect of each individual climate hazard. Lastly, we identified household and community-level determinants of geographic variability of high psychiatric burden.

METHODS

Daily counts of psychiatric ED visits in North Carolina from 2016 to 2019 (May to Sept) for pediatric populations were aggregated at the county scale. Bernoulli cluster analyses identified high-risk spatial clusters of psychiatric morbidity during heatwave, drought, or compound heatwave and drought periods. Multivariate adaptive regression models examined the individual importance of household and community-level determinants in predicting high-risk clustering of mood disorders or suicidality across the three climate threats.

RESULTS

Results showed significant spatial clustering of suicide and mood disorder risks in children during heatwave, drought, and compound event periods. Periods of drought were associated with the highest likelihood of spatial clustering for suicide and mood disorders, where the risk of an ED visit was 4.48 and 6.32 times higher, respectively, compared to non-drought periods. Compounding events were associated with a threefold increase in both suicide and mood disorder-related ED visits. Community and household vulnerability factors that most contributed to spatial clustering varied across climate hazards, but consistent determinants included residential segregation, green space availability, low English proficiency, overcrowding, no broadband access, no vehicle access, housing vacancy, and availability of housing units.

CONCLUSION

Findings advance understanding on the locations of vulnerable pediatric populations who are disproportionately exposed to compounding climate stressors and identify community resilience factors to target in public health adaptation strategies.

Storyline attribution of human influence on a record-breaking spatially compounding flood-heat event

Attribution of compound events informs preparedness for emerging hazards with disproportionate impacts. However, the task remains challenging because space-time interactions among extremes and uncertain dynamic changes are not satisfactorily addressed in the well-established attribution framework. For attributing the 2020 record-breaking spatially compounding flood-heat event in China, we conduct a storyline attribution analysis by designing simulation experiments via a weather forecast model, quantifying component-based attributable changes, and comparing with historical flow analogs. We quantify that given the large-scale circulation, anthropogenic influence to date has exacerbated the extreme Mei-yu rainfall in the mid-lower reaches of the Yangtze River during June-July 2020 by ~6.5% and warmed the co-occurring seasonal extreme heat in South China by ~1°C. Our projections show a further intensification of the compound event by the end of this century, with moderate emissions making the rainfall totals ~14% larger and the season ~2.1°C warmer in South China than the 2020 status.

Exponential increases in high-temperature extremes in North America

Global warming in the 21st century will alter the frequency of extreme climatic events, such as high-temperature anomalies and "heat waves". Observations of extreme high temperatures during recent decades have detected upward trends in their frequency of occurrence, and recent state-of-the-art Global Climate Models (GCMs), e.g., Climate Model Intercomparison Projects (CMIPs), notably CMIP5 and CMIP6, have predicted acceleration of temperature trends and high-temperature events by 2100 under projected greenhouse-gas emission scenarios. Hence, the 21st century is expected to experience substantial shifts in the occurrence of extreme events, where present-day, extreme-but-rare high-temperature events will become common during the summer months. The increasing frequency of extreme heat may affect the health and resiliency of social, biological, and infrastructure systems in many regions worldwide, underscoring the need for accurate and reliable long-term assessments of climatic change across global and regional scales. So far, many investigations of high-temperature extremes have been carried out under end-point scenarios, e.g., by comparing GCM-projected changes in the frequency of high-temperature extremes expected in the late 21st century to the late 20th century. In this study, we use extreme value theory and decades of observations of high-temperature extremes at thousands of meteorological stations across North America to investigate continuous shifts in the frequency of extreme high-temperature events due to projected local warming trends. We find that the odds of exceedance of 50-year extreme high-temperature events increases exponentially with increases in mean local temperature. At a majority of the stations studied here, a local mean temperature increase of 0.5-1 [Formula: see text]C can double the odds of exceedance of 50-year extreme high-temperature events. Based on time-dependent temperature projections, the odds of exceedance of 50-year extreme high-temperature events doubles approximately every 20 years (or sooner) for [Formula: see text] 96% of the stations. Moreover, we find that, for [Formula: see text] 80% of the stations in North America, investigated here, the 50-year extreme high-temperature events will be exceeded annually before 2100.

Towards a greater engagement of universities in addressing climate change challenges

Many higher education institutions around the world are engaged in efforts to tackle climate change. This takes place by not only reducing their own carbon footprint but also by educating future leaders and contributing valuable research and expertise to the global effort to combat climate change. However, there is a need for studies that identify the nature of their engagement on the topic, and the extent to which they are contributing towards addressing the many problems associated with climate change. Against this background, this paper describes a study that consisted of a review of the literature and the use of case studies, which outline the importance of university engagement in climate change and describe its main features. The study identified the fact that even though climate change is a matter of great relevance to universities, its coverage in university programmes is not as wide as one could expect. Based on the findings, the paper also lists the challenges associated with the inclusion of climate change in university programmes. Finally, it describes some of the measures which may be deployed in order to maximise the contribution of higher education towards handling the challenges associated with a changing climate.

Vulnerability assessment of urban agglomerations to the risk of heat waves in China since the 21st century

In the context of global warming, frequent heat wave disasters have seriously threatened the safety of human life and property. The urban agglomeration, as the main region with a high concentration of population and economy, is susceptible to heat weaves due to the existing urban heat island effect. In this study, we investigated the temporal and spatial characteristics of heat waves (heat index, HI) in China from 2000 to 2020 and assess the vulnerability of 19 urban agglomerations to heat waves from the perspective of exposure, sensitivity and adaptability. The results show that: (1) In the past 20 years, the frequency and intensity of HI (greater than 26.67 °C) both showed an upward trend. (2) Shandong Peninsula, Central Henan, Yangtze River Delta, Middle Reaches of Yangtze River, and Mid-southern Liaoning urban agglomerations always maintain a high vulnerability. (3) From 2000 to 2020, the vulnerability of Beijing-Tianjin-Hebei, Yangtze River Delta, Chengdu-Chongqing, Middle reaches of Yangtze River, Guangdong-Fujian-Zhejiang, Harbin-Changchun and Mid-southern Liaoning urban agglomerations were always dominated by exposure. The vulnerability of Shandong Peninsula, Beibu Gulf and Central Henan urban agglomeration has always been dominated by sensitivity. The vulnerability of North Tianshan Mountain, Lanzhou-Xining, Guanzhong and Hu-Bao-E-Yu urban agglomeration has always been dominated by inadequate adaptability. (4) Recently, the factors that contributed most to exposure, sensitivity and adaptability were population density, the proportion of outdoor workers and water supply, with contribution rates of 38%, 55% and 26%, respectively. This study can provide a scientific basis for the rational allocation of resources among urban agglomerations, effectively formulating policies and guiding population migration from high temperature disasters.

Enhanced causal effect of ecosystem photosynthesis on respiration during heatwaves

Because of global warming, Earth's ecosystems have been experiencing more frequent and severe heatwaves. Heatwaves are expected to tip terrestrial carbon sequestration by elevating ecosystem respiration and suppressing gross primary productivity (GPP). Here, using the convergent cross-mapping technique, this study detected positive bidirectional causal effects between GPP and respiration in two unprecedented European heatwaves. Heatwaves enhanced the causal effect strength of GPP on respiration rather than respiration on GPP across 40 site-years of observations. Further analyses and global simulations revealed spatial heterogeneity in the heatwave response of the causal link strength between GPP and respiration, which was jointly driven by the local climate and vegetation properties. However, the causal effect strength of GPP on respiration showed considerable uncertainties in CMIP6 models. This study reveals an enhanced causal link strength between GPP and respiration during heatwaves, shedding light on improving projections for terrestrial carbon sink dynamics under future climate extremes.

The global costs of extreme weather that are attributable to climate change

Extreme weather events lead to significant adverse societal costs. Extreme Event Attribution (EEA), a methodology that examines how anthropogenic greenhouse gas emissions had changed the occurrence of specific extreme weather events, allows us to quantify the climate change-induced component of these costs. We collect data from all available EEA studies, combine these with data on the socio-economic costs of these events and extrapolate for missing data to arrive at an estimate of the global costs of extreme weather attributable to climate change in the last twenty years. We find that US[Formula: see text] 143 billion per year of the costs of extreme events is attributable to climatic change. The majority (63%), of this is due to human loss of life. Our results suggest that the frequently cited estimates of the economic costs of climate change arrived at by using Integrated Assessment Models may be substantially underestimated.

Climate change amplified the 2009 extreme landslide event in Austria

Landslides are an important natural hazard in mountainous regions. Given the triggering and preconditioning by meteorological conditions, it is known that landslide risk may change in a warming climate, but whether climate change has already affected individual landslide events is still an open question, partly owing to landslide data limitations and methodological challenges in climate impact attribution. Here, we demonstrate the substantial influence of anthropogenic climate change on a severe event in the southeastern Alpine forelands with some estimated 952 individual landslides in June 2009. Our study is based on conditional event attribution complemented by an assessment of changes in atmospheric circulation. Using this approach, we simulate the meteorological event under observed and a range of counterfactual conditions of no climate change and explicitly predict the landslide occurrence probability for these conditions. We find that up to 10%, i.e., 95 landslides, can be attributed to climate change.

Rapid increase in the risk of heat-related mortality

Heat-related mortality has been identified as one of the key climate extremes posing a risk to human health. Current research focuses largely on how heat mortality increases with mean global temperature rise, but it is unclear how much climate change will increase the frequency and severity of extreme summer seasons with high impact on human health. In this probabilistic analysis, we combined empirical heat-mortality relationships for 748 locations from 47 countries with climate model large ensemble data to identify probable past and future highly impactful summer seasons. Across most locations, heat mortality counts of a 1-in-100 year season in the climate of 2000 would be expected once every ten to twenty years in the climate of 2020. These return periods are projected to further shorten under warming levels of 1.5 °C and 2 °C, where heat-mortality extremes of the past climate will eventually become commonplace if no adaptation occurs. Our findings highlight the urgent need for strong mitigation and adaptation to reduce impacts on human lives.

Heatwaves: does global research reflect the growing threat in the light of climate change?

BACKGROUND

With the increasing impacts of climate change, heatwaves are placing an enormous burden on health and social systems and threatening ecological diversity around the world. Heatwaves are increasing not only in frequency but also in severity and magnitude. They are causing the deaths of thousands of people. Research is needed on a multidisciplinary, supra-regional, and regional level.

METHODS

A detailed evaluation of the research conducted is not yet available. Therefore, this study provides a detailed insight into the publication landscape to identify key players, incentives, and requirements for future scientific efforts that are useful not only for scientists but also to stakeholders and project funders.

RESULTS

The number of publications on heatwaves is increasing, outpacing the trend of research indexed by the Science Citation Index Expanded. However, funding is lagging behind comparatively. Looking at absolute numbers, the USA, Australia, China, and some European countries have been identified as major players in heatwave research. If socio-economic numbers are included, Switzerland and Portugal lead the way. Australia and the UK dominate if the change in heatwave-exposed people is included. Nevertheless, exposure and economic strength of publishing countries were identified as the main drivers of national research interests. Previous heatwaves, in particular, have driven research efforts primarily at the national level.

CONCLUSION

For an efficient monitoring or early detection system that also includes the economically weak regions, internationally networked efforts are necessary to enable preventive measures and damage limitation against heatwaves. Regardless of previous regional extreme heat events, research approaches should be focused to the global level.

Climatic and Economic Background Determine the Disparities in Urbanites' Expressed Happiness during the Summer Heat

Climate-change-induced extreme weather events increase heat-related mortality and health risks for urbanites, which may also affect urbanites' expressed happiness (EH) and well-being. However, the links among EH, climate, and socioeconomic factors remain unclear. Here we collected ∼6 million geotagged tweets from 44 Chinese prefecture-level cities based on Sina Weibo and performed a quadratic regression model to explore the relationships between summer heat and EH. A three-stage analysis was developed to examine spatiotemporal heterogeneity and identify factors contributing to disparities in urbanites' EH. Results show that all cities exhibited a similar hump-shaped relationship, with an overall optimal temperature (OT) of 22.8 °C. The estimated OT varied geographically, with 25.3, 23.8, and 20.0 °C from north to south. Moreover, a 1 standard deviation increase in heatwave intensity was associated with a 0.813 (95% CI: 0.177, 1.449) standard deviation decrease in EH. Notably, within the geographic scope of this study, it was observed that urbanites in northern China and economically underdeveloped cities faced significantly lower heat risks during the summer heat. This research provides insight for future studies and practical applications concerning extreme weather events, urbanites' mental health, and sustainable urban development goal.

Assessing Psychosocial Health Impacts of Climate Adaptation: A Critical Review

The urgency of dealing with risks associated with climate change and the need for effective response measures to their impacts are increasing daily the world over. Literature abounds regarding the impacts of climate change on physical, psychosocial, and other health outcomes. In contrast, little research exists on the health impacts of response measures to climate change. This critical review seeks to contribute towards closing this gap through a synthesis of current literature on the psychosocial health outcomes of climate adaptation actions. Our results found both positive and negative outcomes associated with psychosocial health that may result from climate adaptation actions. We propose the utilization of well-developed conceptual frameworks and evaluation tools in assessment and analysis of these outcomes. Ultimately, there is need to expand similar and related areas of research more broadly and on psychosocial effects, specifically.

Human-induced weakening of the Northern Hemisphere tropical circulation

By accounting for most of the poleward atmospheric heat and moisture transport in the tropics, the Hadley circulation largely affects the latitudinal patterns of precipitation and temperature at low latitudes. To increase our preparednesses for human-induced climate change, it is thus critical to accurately assess the response of the Hadley circulation to anthropogenic emissions^1-3. However, at present, there is a large uncertainty in recent Northern Hemisphere Hadley circulation strength changes⁴. Not only do climate models simulate a weakening of the circulation⁵, whereas atmospheric reanalyses mostly show an intensification of the circulation^4-8, but atmospheric reanalyses were found to have artificial biases in the strength of the circulation⁵, resulting in unknown impacts of human emissions on recent Hadley circulation changes. Here we constrain the recent changes in the Hadley circulation using sea-level pressure measurements and show that, in agreement with the latest suite of climate models, the circulation has considerably weakened over recent decades. We further show that the weakening of the circulation is attributable to anthropogenic emissions, which increases our confidence in human-induced tropical climate change projections. Given the large climate impacts of the circulation at low latitudes, the recent human-induced weakening of the flow suggests wider consequences for the regional tropical-subtropical climate.

Regionally high risk increase for precipitation extreme events under global warming

Daily precipitation extremes are projected to intensify with increasing moisture under global warming following the Clausius-Clapeyron (CC) relationship at about [Formula: see text]. However, this increase is not spatially homogeneous. Projections in individual models exhibit regions with substantially larger increases than expected from the CC scaling. Here, we leverage theory and observations of the form of the precipitation probability distribution to substantially improve intermodel agreement in the medium to high precipitation intensity regime, and to interpret projected changes in frequency in the Coupled Model Intercomparison Project Phase 6. Besides particular regions where models consistently display super-CC behavior, we find substantial occurrence of super-CC behavior within a given latitude band when the multi-model average does not require that the models agree point-wise on location within that band. About 13% of the globe and almost 25% of the tropics (30% for tropical land) display increases exceeding 2CC. Over 40% of tropical land points exceed 1.5CC. Risk-ratio analysis shows that even small increases above CC scaling can have disproportionately large effects in the frequency of the most extreme events. Risk due to regional enhancement of precipitation scale increase by dynamical effects must thus be included in vulnerability assessment even if locations are imprecise.

Overstating the effects of anthropogenic climate change? A critical assessment of attribution methods in climate science

Climate scientists have proposed two methods to link extreme weather events and anthropogenic climate forcing: the probabilistic and the storyline approach. Proponents of the first approach have raised the criticism that the storyline approach could be overstating the role of anthropogenic climate change. This issue has important implications because, in certain contexts, decision-makers might seek to avoid information that overstates the effects of anthropogenic climate change. In this paper, we explore two research questions. First, whether and to what extent the storyline approach overstates the effects of anthropogenic climate change. Second, whether the objections offered against the storyline approach constitute good reasons to prefer the probabilistic approach. Concerning the first question, we show that the storyline approach does not necessarily overstate the effects of climate change, and particularly not for the reasons offered by proponents of the probabilistic approach. Concerning the second question, we show, independently, that the probabilistic approach faces the same or very similar objections to those raised against the storyline approach due to the lack of robustness of climate models and the way events are commonly defined when applying the probabilistic approach. These results suggest that these objections might not constitute good reasons to prefer the probabilistic approach over the storyline approach.

Analysis and intervention of heatwave related economic loss: Comprehensive insights from supply, demand, and public expenditure into the relationship between the influencing factors

Increasing extreme temperatures are producing a serious impact on the economies of cities. However, the importance of social factors is typically neglected by the existing research. In this work, we first establish a supply-demand-public expenditure (SDP) framework for assessing and forecasting heat-related economic loss. Compared with the previous framework, SDP possesses a more comprehensive index system and functions that apply to all types of cities. We selected different economic development and geographical locations (Nanjing, Suzhou, and Yancheng) as case studies to verify the wide applicability of the SDP framework. A qualitative analysis and quantitative prediction of heatwaves and socioeconomic factors on losses were conducted for different cities. The results showed that different loss types displayed obvious regional heterogeneity among the cities. The labor value loss was the most significant type, and health loss was the most vulnerable type. In addition, public expenditure played a neglected critical regulatory role. Apart from these, the current level of public expenditure for heat prevention and control remains insufficient. Based on an assessment of the effects of interventions, policymakers need to make more efforts to increase the proportion of heat-related public spending and ensure stable socio-economic development by utilizing pathways with positive intervention potentials.

The fall of the summer truffle: Recurring hot, dry summers result in declining fruitbody production of Tuber aestivum in Central Europe

Global warming is pushing populations outside their range of physiological tolerance. According to the environmental envelope framework, the most vulnerable populations occur near the climatic edge of their species' distributions. In contrast, populations from the climatic center of the species range should be relatively buffered against climate warming. We tested this latter prediction using a combination of linear mixed effects and machine learning algorithms on an extensive, citizen-scientist generated dataset on the fruitbody productivity of the Burgundy (aka summer) truffle (Tuber aestivum Vittad.), a keystone, ectomycorrhizal tree-symbiont occurring on a wide range of temperate climates. T. aestivum's fruitbody productivity was monitored at 3-week resolution over up to 8 continuous years at 20 sites distributed in the climatic center of its European distribution in southwest Germany and Switzerland. We found that T. aestivum fruitbody production is more sensitive to summer drought than would be expected from the breadth of its species' climatic niche. The monitored populations occurring nearly 5°C colder than the edge of their species' climatic distribution. However, interannual fruitbody productivity (truffle mass year^-1 ) fell by a median loss of 22% for every 1°C increase in summer temperature over a site's 30-year mean. Among the most productive monitored populations, the temperature sensitivity was even higher, with single summer temperature anomalies of 3°C sufficient to stop fruitbody production altogether. Interannual truffle productivity was also related to the phenology of host trees, with ~22 g less truffle mass for each 1-day reduction in the length of the tree growing season. Increasing summer drought extremes are therefore likely to reduce fruiting among summer truffle populations throughout Central Europe. Our results suggest that European T. aestivum may be a mosaic of vulnerable populations, sensitive to climate-driven declines at lower thresholds than implied by its species distribution model.

Analysing the relationship between human modification and land surface temperature fluctuation in the Ramganga basin, India

In many regions across the world, including river basins, population growth and land development have enhanced the demand for land and other natural resources. The anthropogenic activities can be detrimental to the vital ecosystems that sustain the river basin region. This work assessed the impact of human modification on land surface temperature (LST) for the Ramganga basin in India. It has been hypothesised that the footprints of anthropogenic activities in the region have been connected to the LST fluctuation for the region, which could indicate environmental degradation. The LST variation between 2000 and 2016 has been estimated to test this hypothesis. The spatio-temporal correlation between human modification and LST has been computed. LST has been calculated with MODIS satellite data in the Google earth engine (GEE) platform, and anthropogenic activities can be visualised using an LU/LC map of the basin created by the Classification and Regression (CART) technique. The statistical parameters (average, maximum and standard deviation) of annual temperature for each pixel in 17 years (2000-2016) have been assessed to establish the links with human modification. The result of this work portrays a positive correlation of 0.705 between maximum LST and human modification. The forest class in the basin region has the lowest average human modification value (0.37), and it also possesses the lowest mean LST of 26.72 °C. Similarly, the settlement class has the highest average human modification value (0.85), and the mean LST temperature of this class has been on the higher side, having a value of 31.07 °C.

Globally unequal effect of extreme heat on economic growth

Increased extreme heat is among the clearest impacts of global warming, but the economic effects of heat waves are poorly understood. Using subnational economic data, extreme heat metrics measuring the temperature of the hottest several days in each year, and an ensemble of climate models, we quantify the effect of extreme heat intensity on economic growth globally. We find that human-caused increases in heat waves have depressed economic output most in the poor tropical regions least culpable for warming. Cumulative 1992-2013 losses from anthropogenic extreme heat likely fall between $5 trillion and $29.3 trillion globally. Losses amount to 6.7% of Gross Domestic Product per capita per year for regions in the bottom income decile, but only 1.5% for regions in the top income decile. Our results have the potential to inform adaptation investments and demonstrate how global inequality is both a cause and consequence of the unequal burden of climate change.

Attributions for extreme weather events: science and the people

Both climate scientists and non-scientists (laypeople) attribute extreme weather events to various influences. Laypeople's attributions for these events are important as these attributions likely influence their views and actions about climate change and extreme events. Research has examined laypeople's attribution scepticism about climate change in general; however, few climate scientists are familiar with the processes underpinning laypeople's attributions for individual extreme events. Understanding these lay attributions is important for scientists to communicate their findings to the public. Following a brief summary of the way climate scientists calculate attributions for extreme weather events, we focus on cognitive and motivational processes that underlie laypeople's attributions for specific events. These include a tendency to prefer single-cause rather than multiple-cause explanations, a discounting of whether possible causes covary with extreme events, a preference for sufficient causes over probabilities, applying prevailing causal narratives, and the influence of motivational factors. For climate scientists and communicators who wish to inform the public about the role of climate change in extreme weather events, these patterns suggest several strategies to explain scientists' attributions for these events and enhance public engagement with climate change. These strategies include showing more explicitly that extreme weather events reflect multiple causal influences, that climate change is a mechanism that covaries with these events and increases the probability and intensity of many of these events, that human emissions contributing to climate change are controllable, and that misleading communications about weather attributions reflect motivated interests rather than good evidence.

Emission Characteristics of Air Pollutants and CO2 from 11 Cities with Different Economic Development around the Bohai Sea in China from 2008-2017

Cities around the Bohai Sea are one of the main population cluster areas in China, which are characterized by high levels of sustainability performance and human capital, as well as resource-intensive industries. In this study, levels of economic development metrics and emissions of air pollutants (BC, CO, NH₃, NO_x, OC, PM_2.5, PM₁₀, and SO₂) and CO₂ across eleven cities around the Bohai Sea from 2008 to 2017 were compared to illustrate the potential relationships between air pollutants/carbon emissions and socioeconomic developments. Meanwhile, the associations between the levels of economic development metrics (GDP per capita), emissions, and energy use per GDP have also been examined. Large differences across these 11 cities presenting different economic development levels and energy consumption characteristics have been observed. Cities with development dependable on the consumption of fossil fuels and the development of resource-intensive industries have emitted large amounts of air pollutants and CO₂. Furthermore, the emissions and energy use per GDP for all the cities follow environmental Kuznets curves. The comparison results suggested that the developing cities dependable on resource-intensive industries around the Bohai Sea would obtain greater socioeconomic benefits owing to the interregional cooperation policies under top-down socioeconomic development plans and bottom-up technology development, accompanied by reduced emissions of air pollutants and CO₂.

Mitigating Extreme Summer Heat Waves with the Optimal Water-Cooling Island Effect Based on Remote Sensing Data from Shanghai, China

Due to the progress in global warming, the frequency, duration and intensity of climate extremes are increasing. As one of these extremes, heat waves influence the well-being of human beings and increase societies’ energy consumption. The Water-Cooling Island (WCI) effect of urban water bodies (UWBs) is important in urban heat wave mitigation. In this paper, the impact of WCI, especially the landscape pattern of the surrounding area, was explored. The results indicate that water bodies with a larger total area and simpler shape have a longer cooling effect. In the areas surrounding UWBs, a lower percentage or discrete distribution of impervious surfaces or green land provide a longer cooling effect. The amplitude of WCI is mainly decided by the impervious surface in the surrounding areas. A lower percentage or discrete distribution of impervious surfaces or green land leads to a smaller-amplitude WCI. The gradient is impacted by the shape of the UWB and surrounding green land. A complex shape and discrete distribution of green land lead to a higher gradient of WCI. The linear regress model was significant in terms of WCI range and gradient, while the model of WCI amplitude was not significant. This indicates that WCI is directly decided by impact factors through gradient and range. The conclusions provide a methodology for WCI prediction and optimization, which is important when mitigating summer heat waves.

The Extreme Heat Wave of Summer 2021 in Athens (Greece): Cumulative Heat and Exposure to Heat Stress

The Mediterranean has been identified as a ‘climate change hot spot’, already experiencing faster warming rates than the global average, along with an increased occurrence of heat waves (HWs), prolonged droughts, and forest fires. During summer 2021, the Mediterranean faced prolonged and severe HWs, triggering hundreds of wildfires across the region. Greece, in particular, was hit by one of the most intense HWs in its modern history, with national all-time record temperatures being observed from 28 July to 6 August 2021. The HW was associated with extreme wildfires in many parts of the country, with catastrophic environmental and societal consequences. The study accentuated the rarity and special characteristics of this HW (HW2021) through the analysis of the historical climate record of the National Observatory of Athens (NOA) on a centennial time scale and comparison with previous HWs. The findings showed that HW2021 was ranked first in terms of persistence (with a total duration of 10 days) and highest observed nighttime temperatures, as well as ‘cumulative heat’, accounting for both the duration and intensity of the event. Exceptionally hot conditions during nighttime were intensified by the urban heat island effect in the city of Athens. Human exposure to heat-related stress during the event was further assessed by the use of bioclimatic indices such as the Universal Thermal Climate Index (UTCI). The study points to the interconnected climate risks in the area and especially to the increased exposure of urban populations to conditions of heat stress, due to the additive urban effect.

Anatomy of the atmospheric emissions from the transport sector in Greece: trends and challenges

Emissions of atmospheric pollutants are well-known for their adverse effects on air quality and public health. Additionally, GHG emissions are responsible for the so called "Radiating Forcing" leading to climate change and degradation of ecosystem services. In this work, we analyze the annual emission trends of various air pollutants, including GHGs, from all 4 sectors of transport (roads, aviation, navigation, and railway) in Greece during the 28-year period between 1990 and 2017, in order to examine the confounding dynamics among external forces, such as the major fiscal recession of 2008, and the GHG/pollutant emissions in the country. The analysis is performed with a suite of statistical tools consisting of bivariate correlation analysis, Mann-Kendall test, Sen's slope estimation, and Joinpoint regression analysis, in order to thoroughly study the trends of emissions. It is found that all transport sectors (except for the railway) show a significant increase in their emissions, despite the fiscal recession of 2008 that temporarily decelerated all aspects of economic activity in the country. Given the major share of transport in GHG emissions (37%) and air pollution in urban centers, it is essential that the road sector adapts to the new challenges, by means of switching to low-emission technologies and electromobilization. The same applies for the navigation and aviation sectors, which are known pillars of the tourist industry in the country.

The exceptional heatwaves of 2017 and all-cause mortality: An assessment of nationwide health and economic impacts in China

Heatwaves with unprecedented conditions have devastating health impacts. The summer of 2017 saw unusual heat in China and other regions on earth. Although epidemiologic evidence is clear for elevated mortality risks of heatwaves, the economic impacts due to heatwave-associated mortality remain poorly characterized. Hence, this study systematically assessed the mortality and economic impacts of the 2017 exceptional heatwaves in China. We first used the generalized linear mixed-effect model with Poisson distribution to examine the mortality risks of the 2017 heatwaves in 91 Chinese counties. Further, we calculated the excess deaths attributable to heatwaves in 2852 counties. Finally, we evaluated the city- and province-level death-related economic burden of the 2017 heatwaves based on the value of statistical life (VSL). We found that the 2017 exceptional heatwaves had a statistically significant association (relative risk was 1.23, 95% confidence interval 1.14-1.32) with all-cause mortality across 91 Chinese counties. Nationwide, a total of 16,299 all-cause deaths that occurred in 2017 were attributable to the exceptional heatwaves, resulting in an overall death-related economic loss of 61,304 million RMB as valued by VSL. Given that extraordinary heatwaves are projected to be more frequent under global climate change, our findings could enhance the current understanding of heatwaves' health and economic impacts and add valuable insights in projection studies of estimating the future health burden of heatwaves.

Understanding human influence on climate change in China

China's climate has been warming since the 1950s, with surface air temperature increasing at a rate higher than the global average. Changes in climate have exerted substantial impacts on water resources, agriculture, ecosystems and human health. Attributing past changes to causes provides a scientific foundation for national and international climate policies. Here, we review recent progress in attributing the observed climate changes over past decades in China. Anthropogenic forcings, dominated by greenhouse gas emissions, are the main drivers for observed increases in mean and extreme temperatures. Evidence of the effect of anthropogenic forcings on precipitation is emerging. Human influence has increased the probability of extreme heat events, and has likely changed the occurrence probabilities for some heavy precipitation events. The way a specific attribution question is posed and the conditions under which the question is addressed present persistent challenges for appropriately communicating attribution results to non-specialists.

Analyzing the Environment Characteristics of Heat Exposure Spaces from the Humanistic Perspective and Spatial Improvement Approaches in Central Beijing, China

Global warming, high temperatures, and heatwave weather are some of the factors affecting human settlement environment health. In high-temperature weather, human production and life are seriously threatened, as long-term exposure to high temperatures causes a variety of diseases, and children and elderly, who have poor tolerance, require strengthened protection. From a human perspective, this study calculated the thermal duration distribution of high temperatures based on maximum temperature data in a central urban area of Beijing combined with the results of the sixth population census of Beijing, investigated the population distribution of individuals under 15 years old and over 65 years old, and analyzed the spatial distribution of a thermal exposure space in a central urban area of Beijing with the help of the ArcGIS platform. Based on 130 district districts, streets with high-risk heat exposure spaces in the central urban area of Beijing were reddened to determine the distribution of high-risk grades. Using the semantic segmentation method and a street view map, the high-risk thermal exposure space environment from the humanistic perspective was restored, and the typical characteristics were summarized and analyzed. Finally, the environmental characteristics of the high-risk thermal exposure space were analyzed from the humanistic perspective, and an improvement strategy for thermal exposure spaces was proposed based on the perspective of emotional relief.

Land transpiration-evaporation partitioning errors responsible for modeled summertime warm bias in the central United States

Earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) experiment exhibit a well-known summertime warm bias in mid-latitude land regions - most notably in the central contiguous United States (CUS). The dominant source of this bias is still under debate. Using validated datasets and both coupled and off-line modeling, we find that the CUS summertime warm bias is driven by the incorrect partitioning of evapotranspiration (ET) into its canopy transpiration and soil evaporation components. Specifically, CMIP6 ESMs do not effectively use available rootzone soil moisture for summertime transpiration and instead rely excessively on shallow soil and canopy-intercepted water storage to supply ET. As such, expected summertime precipitation deficits in CUS induce a negative ET bias into CMIP6 ESMs and a corresponding positive temperature bias via local land-atmosphere coupling. This tendency potentially biases CMIP6 projections of regional water stress and summertime air temperature variability under elevated CO2 conditions.

Using a climate attribution statistic to inform judgments about changing fisheries sustainability

Sustainability-maintaining catches within the historical range of socially and ecologically acceptable values-is key to fisheries success. Climate change may rapidly threaten sustainability, and recognizing these instances is important for effective climate adaptation. Here, we present one approach for evaluating changing sustainability under a changing climate. We use Bayesian regression models to compare fish population processes under historical climate norms and emerging anthropogenic extremes. To define anthropogenic extremes we use the Fraction of Attributable Risk (FAR), which estimates the proportion of risk for extreme ocean temperatures that can be attributed to human influence. We illustrate our approach with estimates of recruitment (production of young fish, a key determinant of sustainability) for two exploited fishes (Pacific cod Gadus macrocephalus and walleye pollock G. chalcogrammus) in a rapidly warming ecosystem, the Gulf of Alaska. We show that recruitment distributions for both species have shifted towards zero during anthropogenic climate extremes. Predictions based on the projected incidence of anthropogenic temperature extremes indicate that expected recruitment, and therefore fisheries sustainability, is markedly lower in the current climate than during recent decades. Using FAR to analyze changing population processes may help fisheries managers and stakeholders to recognize situations when historical sustainability expectations should be reevaluated.

Forecast-based attribution of a winter heatwave within the limit of predictability

Attribution of extreme weather events has expanded rapidly as a field over the past decade. However, deficiencies in climate model representation of key dynamical drivers of extreme events have led to some concerns over the robustness of climate model-based attribution studies. It has also been suggested that the unconditioned risk-based approach to event attribution may result in false negative results due to dynamical noise overwhelming any climate change signal. The "storyline" attribution framework, in which the impact of climate change on individual drivers of an extreme event is examined, aims to mitigate these concerns. Here we propose a methodology for attribution of extreme weather events using the operational European Centre for Medium-Range Weather Forecasts (ECMWF) medium-range forecast model that successfully predicted the event. The use of a successful forecast ensures not only that the model is able to accurately represent the event in question, but also that the analysis is unequivocally an attribution of this specific event, rather than a mixture of multiple different events that share some characteristic. Since this attribution methodology is conditioned on the component of the event that was predictable at forecast initialization, we show how adjusting the lead time of the forecast can flexibly set the level of conditioning desired. This flexible adjustment of the conditioning allows us to synthesize between a storyline (highly conditioned) and a risk-based (relatively unconditioned) approach. We demonstrate this forecast-based methodology through a partial attribution of the direct radiative effect of increased CO2 concentrations on the exceptional European winter heatwave of February 2019.

Current and projected regional economic impacts of heatwaves in Europe

Extreme heat undermines the working capacity of individuals, resulting in lower productivity, and thus economic output. Here we analyse the present and future economic damages due to reduced labour productivity caused by extreme heat in Europe. For the analysis of current impacts, we focused on heatwaves occurring in four recent anomalously hot years (2003, 2010, 2015, and 2018) and compared our findings to the historical period 1981–2010. In the selected years, the total estimated damages attributed to heatwaves amounted to 0.3–0.5% of European gross domestic product (GDP). However, the identified losses were largely heterogeneous across space, consistently showing GDP impacts beyond 1% in more vulnerable regions. Future projections indicate that by 2060 impacts might increase in Europe by a factor of almost five compared to the historical period 1981–2010 if no further mitigation or adaptation actions are taken, suggesting the presence of more pronounced effects in the regions where these damages are already acute.

Heatwaves are becoming increasingly frequent and more intense, causing severe economic impacts through reduced labour productivity. Here, the authors show that economic damages in Europe exceed 1% of the GDP in vulnerable areas, which might increase by a factor of almost five in the medium term without climate action.

Climate change and neurodegenerative diseases

The climate change induced global warming, and in particular the increased frequency and intensity of heat waves, have been linked to health problems. Among them, scientific works have been reporting an increased incidence of neurological diseases, encompassing also neurodegenerative ones, such as Dementia of Alzheimer's type, Parkinson's Disease, and Motor Neuron Diseases. Although the increase in prevalence of neurodegenerative diseases is well documented by literature reports, the link between global warming and the enhanced prevalence of such diseases remains elusive. This is the main theme of our work, which aims to examine the connection between high temperature exposure and neurodegenerative diseases. Firstly, we evaluate the influence of high temperatures exposure on the pathophysiology of these disorders. Secondly, we discuss its effects on the thermoregulation, already compromised in affected patients, and its interference with processes of excitotoxicity, oxidative stress and neuroinflammation, all of them related with neurodegeneration. Finally, we investigate chronic versus acute stressors on body warming, and put forward a possible interpretation of the beneficial or detrimental effects on the brain, which is responsible for the incidence or progression of neurological disorders.

Climate change and extreme weather: A review focusing on the continental United States

Anthropogenic emissions of greenhouse gases are warming the Earth. It is likely that the greatest impacts of climate change on human and natural systems will come from increasingly frequent and severe extreme weather and climate events. Some increases in such extremes are already being detected, and this trend is projected to continue as Earth warms. Here we review the overarching climate drivers of increases in extreme weather and address the context in which extremes occur and the challenges of projecting future changes. The observational evidence for climate-driven increases in extremes and the implications of model projections are reviewed for heat and drought and several types of storms: tropical cyclones, midlatitude storms, and severe local weather, focusing on those changes most relevant to the continental United States. We emphasize the overall observed and modeled trends in extreme weather in which we have the greatest confidence, because they are consistent with our fundamental understanding of weather and climate. Despite remaining uncertainty about many details, especially in model-based projections, the signal of increasing extremes is sufficiently clear that it demands a robust human response, in limiting future emissions of greenhouse gases and in making our human systems more resilient to further changes that are inevitable as Earth continues to warm.Implications: By placing observed and projected changes in extreme weather in the context of our fundamental understanding of physics and statistics, this review makes it clear that these are significant and impactful changes that demand a robust human response.

How to make value-driven climate science for policy more ethical

In previous works, I examine inferential methods employed in Probabilistic Weather Event Attribution studies (PEAs), and explored various ways they can be used to aid in climate policy decisions and decision-making about climate justice issues. This paper evaluates limitations of PEAs and considers how PEA researchers' attributions of "liability" to specific countries for specific extreme weather events could be made more ethical. In sum, I show that it is routinely presupposed that PEA methods are not prone to inductive risks and presuppose that PEA researchers thus have no epistemic consequences or responsibilities for their attributions of liability. I argue that although PEAs are nevertheless crucially useful for practical decision-making, the attributions of liability made by PEA researchers are in fact prone to indicative risks and are influenced by non-epistemic values that PEA researchers should make transparent to make such studies more ethical. Finally, I outline possible normative approaches for making sciences, including PEAs, more ethical; and discuss implications of my arguments for the ongoing debate about how PEAs should guide climate policy and relevant legal decisions.

Capacity of an ecologically key urchin to recover from extreme events: Physiological impacts of heatwaves and the road to recovery

Heatwaves are increasing in frequency and intensity, with substantial impacts on ecosystems and species which maintain their function. Whether or not species are harmed by heatwave conditions by being pushed beyond their physiological bounds can depend on whether energy replacement is sufficient to enable recovery from acute stress. We exposed an ecologically important sea urchin, Heliocidaris erythrogramma, to experimental marine heatwave scenarios in context with recent summer heat anomalies in moderate (25 °C), and strong heatwave (26 °C) conditions for 10 days, followed by a 10-day recovery period at normal summer temperature (23 °C). Greater heatwave intensity drove higher metabolic rates which were not matched with a concurrent increase in food consumption or faecal production. However, food consumption increased during the post-heatwave recovery period, likely to replenish an energy deficit. Despite this, mortality increased into the recovery period and seemed to be caused by latent effects, manifesting as a decline in health index as individuals progressed from spine and pedicellariae loss, through to loss of tube foot rigor, bald patch disease, culminating in mortality. We show for the first time that the acute thermal stress of heatwaves can have latent physiological effects that cause mortality even when conditions return to normal. Our results show that the negative effects of heatwaves can manifest after relief from stressful conditions and highlight the importance of understanding the latent effects on physiology and health. This understanding will offer insights into the long-term potential for stress recovery following seemingly sublethal effects and whether the restoration of ambient conditions post-heatwave is sufficient to ensure population stability.

Evidence of anthropogenic impacts on global drought frequency, duration, and intensity

Most climate change detection and attribution studies have focused on mean or extreme temperature or precipitation, neglecting to explore long-term changes in drought characteristics. Here we provide evidence that anthropogenic forcing has impacted interrelated meteorological drought characteristics. Using SPI and SPEI indices generated from an ensemble of 9 CMIP6 models (using 3 realizations per model), we show that the presence of anthropogenic forcing has increased the drought frequency, maximum drought duration, and maximum drought intensity experienced in large parts of the Americas, Africa, and Asia. Using individual greenhouse gas and anthropogenic aerosol forcings, we also highlight that regional balances between the two major forcings have contributed to the drying patterns detected in our results. Overall, we provide a comprehensive characterization of the influence of anthropogenic forcing on drought characteristics, providing important perspectives on the role of forcings in driving changes in drought events.

Trends of temperature variability: Which variability and what health implications?

A large majority of climate change studies carried out to date are on changes in mean climate, which have comparatively downplayed variability. In terms of trend analysis or forecast, the scientific output and common knowledge for global warming are much more robust than for changes in temperature variability. Quantification of temperature variability adds another dimension of temporal scale, requiring immense labor and presenting great uncertainty. Regardless, this endeavor is necessary since changes in ambient temperature variabilities could also contribute to current and future human health burden besides changes in mean quantities. Here, we review the current literature on trends of surface air temperature variability defined at a range of timescales, aiming to tease out the welter of evidence and thus improving the scientific recognition of changes in air temperature variability in the context of climate change. The findings of reviewed studies from numerous regions differ substantially over various temporal scales. In general, the ambient temperature variability on short time scales (e.g., diurnal or inter-day) shows a downward trend, while it is increasing on longer time scales (e.g., inter-annual). We then move beyond the review and deliver an extended discussion of potential implications for future research related to ambient temperature variability. We highlight the need to consider the methodological choices, especially timescales of interest, in the trend analysis as well as health impact studies. Continued research focusing on temperature variability at multiple timescales, with concerted efforts from scientists of all relevant stripes, is meaningful in synthesizing knowledge and reducing uncertainties surrounding air temperature variability.

The Short-term Effects of Temperature on Infectious Diarrhea among Children under 5 Years Old in Jiangsu, China: A Time-series Study (2015-2019)

The association between meteorological factors and infectious diarrhea has been widely studied in many countries. However, investigation among children under 5 years old in Jiangsu, China remains quite limited. Data including infectious diarrhea cases among children under five years old and daily meteorological indexes in Jiangsu, China from 2015 to 2019 were collected. The lag-effects up to 21 days of daily maximum temperature (Tmax) on infectious diarrhea were explored using a quasi-Poisson regression with a distributed lag non-linear model (DLNM) approach. The cases number of infectious diarrhea was significantly associated with seasonal variation of meteorological factors, and the burden of disease mainly occurred among children aged 0–2 years old. Moreover, when the reference value was set at 16.7°C, Tmax had a significant lag-effect on cases of infectious diarrhea among children under 5 years old in Jiangsu Province, which was increased remarkably in cold weather with the highest risk at 8°C. The results of DLNM analysis implicated that the lag-effect of Tmax varied among the 13 cities in Jiangsu and had significant differences in 8 cities. The highest risk of Tmax was presented at 5 lag days in Huaian with a maximum RR of 1.18 (95% CI: 1.09, 1.29). Suzhou which had the highest number of diarrhea cases (15830 cases), had a maximum RR of 1.04 (95% CI:1.03, 1.05) on lag 15 days. Tmax is a considerable indicator to predict the epidemic of infectious diarrhea among 13 cities in Jiangsu, which reminds us that in cold seasons, more preventive strategies and measures should be done to prevent infectious diarrhea.

Climate scientists set the bar of proof too high

Standards of proof for attributing real world events/damage to global warming should be the same as in clinical or environmental lawsuits, argue Lloyd et al. The central question that we raise is effective communication. How can climate scientists best and effectively communicate their findings to crucial non-expert audiences, including public policy makers and civil society? To address this question, we look at the mismatch between what courts require and what climate scientists are setting as a bar of proof. Our first point is that scientists typically demand too much of themselves in terms of evidence, in comparison with the level of evidence required in a legal, regulatory, or public policy context. Our second point is to recommend that the Intergovernmental Panel on Climate Change recommend more prominently the use of the category "more likely than not" as a level of proof in their reports, as this corresponds to the standard of proof most frequently required in civil court rooms. This has also implications for public policy and the public communication of climate evidence.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10584-021-03061-9.

Attribution and projections of temperature extreme trends in South America based on CMIP5 models

Temperature extreme indices were analyzed for five continental regions of southern South America defined according to their climatic characteristics. Gridded observations, reanalysis, and global-coupled climate models from CMIP5 were used with the approach of temperature extreme trend attribution analysis on fixed-threshold and percentile-based temperature extremes indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The largest positive trends are exhibited in the tropical nights index, and a clear anthropogenic signal is evident in the subtropical region. In the subtropical central Andes, there is a decrease in the frost days index and increases in the tropical nights and summer days indices, and an anthropogenic signal is evident. In the Patagonian region, all trends from the historical runs were significant, while the ones from the natural experiment were nonsignificant, showing the marked effect of anthropogenic forcing in this region in the extreme temperature events. Projected changes in extreme indices for the 21st century are consistent with a warming climate, and larger changes are expected in the warm nights index.