Changes In Weather Patterns Research Articles

Wastewater treatment, greenhouse gas emissions, and our environment

The reclamation and reuse of wastewater is a vital process that helps to address water pollution and scarcity problems. Nevertheless, wastewater treatment is also a significant source of greenhouse gases (methane, carbon dioxide and nitrous oxide). Methane, the most significant greenhouse gas is majorly emitted during anaerobic process, carbon dioxide from aerobic processes while nitrous oxide is associated with nitrification and denitrification processes. The increase in the level of these greenhouse gases is the main cause of global warming and climate change and has resulted in change in weather patterns, severe weather events, habitat loss and loss of wildlife. The adjusting of operating conditions, conversion of methane to fuel for energy production, carbon dioxide capturing are some highlighted methods to minimize the release of these heat-trapping gases from wastewater treatment plants. Also, methods of monitoring these GHG as well as the direct and indirect effects of climate change on the management of wastewater are also discussed in this review.

Models and observations agree on fewer and milder midlatitude cold extremes even over recent decades of rapid Arctic warming.

An apparent increase in observed cold extremes over recent decades in the northern midlatitudes has been reported, in contrast to robust decreases predicted by climate models. This discrepancy has led to suggestions that models fail to accurately simulate changes in weather patterns caused by Arctic warming. Here, we show that the observed frequency and intensity of midlatitude cold extremes have strongly decreased since 1990 and are consistent with modeled trends. The previously reported increase in cold extremes was overestimated due to an artifact of changing data coverage. We also show that the fraction of land with observed cold extreme increases over recent decades is consistent with model internal variability on top of a near-uniform forced reduction in cold extremes across the midlatitudes. Our results provide strong evidence of a decrease in midlatitude cold extremes over recent decades and consistency between models and observations.

Effect of temperature on seasonal wind power and energy potential estimates in Nordic climates

AbstractA major obstacle standing in the way of full‐scale adoption of renewable energy sources is their intermittency and seasonal variability. To better understand the power generation dynamics, the effect of air density due to temperature on power and energy generation figures was modelled. The model uses historical ERA5 data and considers changes in weather patterns in a subarctic climate where seasonal changes are most pronounced. The power generation figures of using a mean and a dynamic air density value were compared and the results show that power generation estimates may be under‐ and overestimated by on average 5% up to 10% in winter and summer, respectively. This can have implications for the sizing of power transmission infrastructure and energy storage in both on‐grid and off‐grid applications as well as power availability. The topic is highly relevant in the Nordic countries where roughly 10% of new global added wind capacity is installed annually.

Indo-Pacific regional extremes aggravated by changes in tropical weather patterns

The Pacific Walker circulation and the closely connected El Niño/Southern Oscillation influence the climate and weather of the tropical Indo-Pacific region. They specifically exert a strong control on the regional occurrence of weather extremes, such as heatwaves, heavy precipitation and prolonged dry spells, which are becoming increasingly frequent and severe. However, climate models struggle to accurately simulate large-scale circulation changes in the tropics and thus their consequences for regional weather and future climate. Here we use high-resolution ERA5 reanalysis data from 1940 to 2022 to study the occurrence trends of weather patterns in the tropical Indo-Pacific region. We find that new large-scale synoptic situations that were rarely present before the 1990s have emerged in the Indo-Pacific, while some others that were prominent have disappeared. Those new synoptic situations are associated with an unusual proportion of heatwaves and extreme precipitation in the region. These weather patterns are physically consistent with a trend towards a stronger Pacific Walker circulation, wetter and warmer conditions in Southeast Asia and drier conditions in the equatorial Pacific. These changes cannot be fully explained by El Niño/Southern Oscillation and other relevant modes of interannual variability, and other factors such as global warming, aerosol forcing, external forcing mechanisms and nonlinear mode interactions may be contributing.

Impacts of changing weather patterns on the dynamics of water pollutants in agricultural catchments: Insights from 11-year high temporal resolution data analysis

Widespread and long-term shifts in weather patterns are contributing to further degradation of surface water quality. This challenge caused by the increasing frequency of extreme weather events requires appropriate adaptation of current mitigation strategies. But to confirm the need to redesign such strategies, an understanding of the impacts of increasing weather extremes on pollutant losses in different catchment types is required. With this in view, this study investigated the impact of changing weather patterns on the inter-seasonal and inter-annual dynamics of nutrient losses in six agricultural catchments in Ireland over 11 years. The high temporal resolution data (10-min) from these intensively managed catchments represented different characteristics and management practices. Mann-Kendall Trend Analysis and Generalised Additive Models were used to study nutrient concentration trends, and to investigate the significance of water discharge, precipitation, potential evapotranspiration, soil moisture deficit, air temperature, and soil temperature on the losses of nutrients, respectively. The analysis of historical data revealed changes in the trends of daily average nitrate (NO3-N), phosphorus (P), and suspended sediment (SS) concentrations in association with significant increasing trends in air temperature, soil temperature, and precipitation across the same month over 11 years of monitoring. While discharge was significantly contributing to the concentrations of NO3-N, P, and SS across different catchments, air and soil temperature were significantly correlated to NO3-N losses, and precipitation was the major contributor to regulating P (total P and total reactive P) concentrations. In short, air temperature, soil temperature, soil moisture deficit, and precipitation were the main climatic drivers regulating the nutrient concentrations while the soil chemistry and drainage status were the non-climatically related drivers. The results revealed that the extent of the impact of climatic drivers depends on catchment characteristics. Therefore, expanding the application of this type of study would facilitate better understanding of current and future challenges to water management and provision of climate-resilient mitigation strategies for different catchment typologies.

Weather Influence on Fall Armyworm Infestation in Maize: A Study in Perambalur District, Tamil Nadu, India

Maize, Zea mays L (Family: Poaceae), is a main cereal crop cultivated across diverse agro-climatic regions worldwide. The Fall Armyworm (FAW), Spodopterafrugiperda (J. E. Smith) (Lepidoptera: Noctuidae), migratory insect is notorious for its economic impact, inflicting severe damage on various crops including maize, rice, sorghum, millet, sugarcane, vegetables, and cotton, and has been documented to affect over 80 other plant species. A roving survey was carried out in four major maize growing blocks of Perambalur district viz., Perambalur, Veppanthattai, Alathur and Veppur during Kharif and Rabi season of 2023-2024. The experiment consisted of sixty standard weeks from 3rd July 2023 to 4th August 2024. The results indicated a positive correlation between the number of fall armyworm larvae/plant with Tmax, relative humidity (Evening), and the negative correlation was observed between the number of fall armyworm larvae/plant with Tmin, relative humidity (Morning), Sunshine and rainfall. The data concluded that the maximum temperature significantly influenced the emergence of the fall armyworm and its infestation on maize. The incidence of FAW started in 46th mean standard week MSW (13 larvae/plant) Alathur, (17.25 larvae/plant) Perambalur, (17.25 larvae/plant) Veppanthattai, (18 larvae/plant) Veppur and the population increased gradually and reached the peak in the 47th mean standard week MSW (26 larvae/plant) Alathur, (32.75 larvae/plant) Perambalur, (33 larvae/plant) Veppanthattai, (42 larvae/plant). Correlation analysis revealed that larval population showed a significant positive correlation with the maximum temperature and relative humidity. At the same time, minimum temperature, sunshine, and rainfall exhibited a negative association with larval incidence of S. frugiperda. Propose adaptation strategies for maize farmers in Perambalur to manage fall armyworm infestations in the context of changing weather patterns. This could include adjustments in planting dates, pest monitoring techniques, or integrated pest management approaches.

The weather today rocks or sucks for my tree: exploring the understanding of climate impacts on forests at high school level through tweets

Abstract. With the progression of global warming, impacts on the human sphere will undoubtedly increase. One prominent example at mid-latitudes is the stress on forests caused by climate change, which the BayTreeNet project (https://baytreenet.de/, last access: 30 July 2024) addresses from an interdisciplinary viewpoint. Scientists from physical climatology, dendroecology, and educational research collaborate to examine how long-term changes in weather patterns affect the state of trees, and how the atmosphere–tree relation can be used to the advantage of improving the communication of climate change effects to, in particular, high school students. This article presents a 1-week case study for the summer of 2021, when a distinct variability in weather patterns induced significant tree responses. The students of seven selected partner schools commented on the measured tree and weather data, which were available in real time, in the form of tweets and in conjunction with their educational geography program. The analyses of the tweets reveal that the students succeed in verbalizing the measured weather and, furthermore, manage to draw links between the stem diameter changes in trees and the weather variability. Problems arise with the use of less perceivable variables like the sap flow in the trees; also, the student posts exhibit shortcomings in establishing causal connections. Hence, the case study points to a discrepancy between describing basic environmental information and appreciating or understanding the underlying mechanistic links. This point will serve to refine future classroom concepts and, moreover, to enhance the communication of climate change effects on forests to the general public.

Effects of Changing Weather Patterns on Household Food Availability in Bukiro Sub County Mbarara District

Changing weather patterns and their variables are already negatively impacting food security by damaging crops, reducing yields, and increasing the prevalence of pests and diseases. These pests and diseases contend with crops for sunlight, water, and nutrients, further diminishing agricultural yields and creating issues for crops that were previously unexposed to these threats. Climate-related disruptions in food distribution and transportation, both internationally and domestically, have a substantial impact on not just safety and quality but also access to food. Prolonged dry spells followed by heavy and stormy rains cause interruptions in food production and transportation, reducing farmers' ability to get their grains to market and potentially affecting food prices. This study assessed farmers’ perceptions of effects of changing weather patterns on food security and their coping strategies towards effects of weather changing patterns in smallholder households in Bukiro Sub County, Mbarara District. A sample of 100 smallholder farmers were randomly selected from four parishes of Bukiro sub county and studied using questionnaire and observations. Key informants Interviews were also conducted with nine technical workers and three opinion leaders. Software STAT 26 and Ms excel version 2016 were used to do data analysis. The study found out that changing weather patterns through its variables specifically heavy and stormy rains, late of set of rains, and prolonged dry spells had significant effects on food security. The perceived effects of changing weather patterns established were drying up of water sources (83.8%), decreased land for crop growing (82.4%), reduction in crop yields (77.7%), drying of pastures for animals (67.4%), drying of crops (58.1%), and occurrence of crop and livestock pests and diseases at (56.6%). Also, the perceived weather changing variabilities were late onset of rains (60.1%), prolonged dry spells were responded at 17.6%, and heavy and stormy rains 22.3%. From the study finding farmers clearly perceived that changing weather patterns had negative effects smallholders’ agricultural production systems impacting negatively on food security

The ripple effects of climate change on agricultural sustainability and food security in Africa

AbstractClimate change results in lower agricultural outputs, disruption of food supply chains, and widening of the social gap between poor and rich in developing countries, with more vulnerable groups being pushed into untold poverty. This review aims to investigate the consequences of climate change on food insecurity in Africa in the context of environmental degradation. This review emphasizes the complexity of demands on food security systems due to changing climatic conditions under the four pillars (availability, accessibility, utilization, and stability). This review demonstrated the susceptibility of farm production to changes in temperature, precipitation, and weather patterns generated by climate change. In addition, this review investigated the factors shaping food insecurity, such as increasing population growth, poverty, inadequate early warning systems, and weak agricultural infrastructure. Furthermore, the review points out how climate change affects food prices and availability and the widening income gap, potentially leading to social unrest and political instability in Africa. Vulnerable populations, including impoverished, elderly, and physically challenged individuals, are at increased risk due to climate‐related health impacts. Women who face gender inequalities and socioeconomic limitations are particularly susceptible. We posit that there is a need for comprehensive strategies that address health disparities and consider vulnerable subgroups within society alongside broader measures to enhance food security in the face of climate change.

A Multi-Year Study of Mycotoxin Co-Occurrence in Wheat and Corn Grown in Ontario, Canada.

Mycotoxin emergence and co-occurrence trends in Canadian grains are dynamic and evolving in response to changing weather patterns within each growing season. The mycotoxins deoxynivalenol and zearalenone are the dominant mycotoxins detected in grains grown in Eastern Canada. Two potential emerging mycotoxins of concern are sterigmatocystin, produced by Aspergillus versicolor, and diacetoxyscirpenol, a type A trichothecene produced by a number of Fusarium species. In response to a call from the 83rd Joint Expert Committee on Food Additives and Contaminants, we conducted a comprehensive survey of samples from cereal production areas in Ontario, Canada. Some 159 wheat and 160 corn samples were collected from farms over a three-year period. Samples were extracted and analyzed by LC-MS/MS for 33 mycotoxins and secondary metabolites. Ergosterol was analyzed as an estimate of the overall fungal biomass in the samples. In wheat, the ratio of DON to its glucoside, deoxynivalenol-3-glucoside (DON-3G), exhibited high variability, likely attributable to differences among cultivars. In corn, the ratio was more consistent across the samples. Sterigmatocystin was detected in some wheat that had higher concentrations of ergosterol. Diacetoxyscirpenol was not detected in either corn or wheat over the three years, demonstrating a low risk to Ontario grain. Overall, there was some change to the mycotoxin profiles over the three years for wheat and corn. Ongoing surveys are required to reassess trends and ensure the safety of the food value chain, especially for emerging mycotoxins.

Deciphering climate change impacts on resource extraction supply chain: a systematic review

AbstractMining is becoming increasingly vulnerable to the effects of climate change (CC). The vulnerability stems from changing weather patterns, leading to extreme weather events that can cause damage to equipment, infrastructure, and mining facilities and disrupt operations. The new demand from governments and international agreements has placed additional pressure on mining industries to update their policies in order to reduce greenhouse gas emissions and adapt to CC. This includes implementing carbon pricing systems, utilizing renewable energy, and focusing on sustainable development. Most mining and exploration industries prioritize reducing mining’s impact on climate change rather than adapting to extreme weather events. Therefore, it is important to study and investigate the impacts of climate change on the mining sector. This paper aims to investigate the challenges and strategies for adapting to and mitigating the impacts of climate change on mining through a systematic literature review. The results indicate that the majority of proposed models and strategies in the mining field are still in the conceptual phase, with fewer practical implementations. It has been identified that there is a requirement for long-term planning, improved risk management plans, and increased awareness and education within the industry. Practical strategies such as integrating renewable energy, enhancing operational safety, and improving water and tailings management have been recognized as crucial for effective climate change adaptation and mitigation.

Optimizing Rain Prediction Model Using Random Forest and Grid Search Cross-Validation for Agriculture Sector

Agriculture, as a sector that is highly influenced by weather conditions, faces challenges due to increasingly unpredictable changes in weather patterns. The aim of this research is to create an optimal rainfall prediction model to help farmers create irrigation schedules, use fertilizer, and planting schedules, and protect plants from extreme weather events. The method used in this research to obtain the best rain prediction model is to use the random forest algorithm and the grid search cross-validation algorithm. Random Forest, known for its robustness and accuracy, emerged as a suitable algorithm for predicting rain. utilizing a substantial dataset from the West Nusa Tenggara Meteorology, Climatology, and Geophysics Agency covering the period 2000 to 2023. The data is then processed first to ensure its readiness for use. This process involves removing outlier data points, empty data entries, and unused features. After the preprocessing stage, the data underwent training using the Random Forest algorithm, resulting in an R-squared value of 0.1334. To obtain the optimal model, Grid Search Cross Validation is used. The results of this research obtained the best rain prediction model with an R-squared value of 0.0268. This model will be used to predict rain in the agricultural sector. This research concludes that we can get the best rain prediction model by combining Random Forest and Gird Search Cross-Validation. For further research, we can compare other rain prediction methods, add features, and combine datasets from a wider area.

Vulnerability assessment of aerosol and climate variability for rice and maize yield using EO datasets for sustainable agriculture over India.

Human-generated aerosol pollution gradually modifies the atmospheric chemical and physical attributes, resulting in significant changes in weather patterns and detrimental effects on agricultural yields. The current study assesses the loss in agricultural productivity due to weather and anthropogenic aerosol variations for rice and maize crops through the analysis of time series data of India spanning from 1998 to 2019. The average values of meteorological variables like maximum temperature (TMAX), minimum temperature (TMIN), rainfall, and relative humidity, as well as aerosol optical depth (AOD), have also shown an increasing tendency, while the average values of soil moisture and fraction of absorbed photosynthetically active radiation (FAPAR) have followed a decreasing trend over that period. This study's primary finding is that unusual variations in weather variables like maximum and minimum temperature, rainfall, relative humidity, soil moisture, and FAPAR resulted in a reduction in rice and maize yield of approximately (2.55%, 2.92%, 2.778%, 4.84%, 2.90%, and 2.82%) and (5.12%, 6.57%, 6.93%, 6.54%, 4.97%, and 5.84%), respectively. However, the increase in aerosol pollution is also responsible for the reduction of rice and maize yield by 7.9% and 8.8%, respectively. In summary, the study presents definitive proof of the detrimental effect of weather, FAPAR, and AOD variability on the yield of rice and maize in India during the study period. Meanwhile, a time series analysis of rice and maize yields revealed an increasing trend, with rates of 0.888 million tons/year and 0.561 million tons/year, respectively, due to the adoption of increasingly advanced agricultural techniques, the best fertilizer and irrigation, climate-resilient varieties, and other factors. Looking ahead, the ongoing challenge is to devise effective long-term strategies to combat air pollution caused by aerosols and to address its adverse effects on agricultural production and food security.

Enhancing Groundwater Quality Evaluation Using Associative Rule Mining Technique with Random Forest Split Gini Indexing Algorithm for Nitrate Concentration Analysis

Human actions and changing weather patterns are contributing to the growing demand for groundwater resources. Nevertheless, evaluating the quality of groundwater is crucial. Nitrate is a significant water contaminant that can lead to blue-baby syndrome or methemoglobinemia. Therefore, it is necessary to assess the level of nitrate in groundwater. Current methods involve evaluating the quality of groundwater and integrating it into the models. The inappropriate datasets, lack of performance, and other constraints are limitations of current methods. Ground water dataset is used and pre-processed the data’s. Selected data’s are feature extracted and associated with the rule ranking. In the suggested model, the use of associative rule mining technique has been implemented to address these challenges and assess nitrate levels in groundwater. The method of rule ranking is carried out using association rule mining technique to divide the datasets. The split gini indexing algorithm is introduced in the proposed model for data classification. The Split Gini Indexing algorithm is a decision tree induction algorithm that is used to build decision trees for classification tasks. It is based on the Gini impurity measure, which measures the heterogeneity of a dataset. The quality of groundwater has been classified using Naïve Bayes, SVM, and KNN algorithms. The proposed approach's efficiency is evaluated by calculating performance metrics such as precision, accuracy, F1-score, and recall values. The suggested method in the current research attains an improved accuracy of 0.99, demonstrating enhanced performance.

Biosocial environmental faces of climate variability in health care: A systematic review

Introduction: Human health is directly impacted by climate variations, leading to changes in weather patterns (e.g., heat waves, droughts, floods, storms), as well as indirectly affecting water, air, and food quality. This research aims to explore key strategies for addressing environmental risks resulting from climate variations in the healthcare sector. Methods: A systematic analytical approach was employed in this investigation, examining studies on climate change adaptation from 2022 to 2023. English publications were sought in renowned databases like Elsevier, PubMed, Web of Science, and Scopus. The search process consisted of two phases. Initially, articles focusing on climate change, climate variability, and global warming were identified using keywords like "Climate change," "Climate variability," and "Global warming." Subsequently, relevant articles were chosen for examination and analysis, using terms such as "Health," "Exposure," "Infectious disease," "Mental health," "Adaptation," and "Mitigation." Results: Primary healthcare systems are essential for enhancing resilience at both individual and community levels, acting as a critical framework for safeguarding global populations through accessible, cost-efficient, responsive, and dependable healthcare services. The evaluation of selected studies underscores the necessity of establishing resilient healthcare systems to counter climate change through adaptive or resilience-focused and mitigative strategies. Recommendations include bolstering the capacity of these systems, enhancing efficient and iterative risk management across all tiers, fostering collaboration across various sectors, formulating action plans, and making short- and long-term investments to enhance adaptability. Conclusion: Pivotal in safeguarding global populations, healthcare systems should prioritize the reinforcement of social resilience by implementing adaptive and mitigative measures in response to climate change.

Update on liver fluke in sheep and cattle

Fasciola hepatica, the common liver fluke, affects the health and welfare of grazing animals worldwide. Liver fluke infection has a significant economic cost to the UK agriculture industry through sheep deaths, reduced growth rates, fertility and milk production in sheep and cattle and condemned livers at the abattoir. Changing weather patterns in the UK over recent years have often resulted in milder winters and summers that may be hot or wet but are above all unpredictable, affecting the epidemiology of liver fluke. This poses a risk for farmers relying on traditional calendar-based treatment routines, who may be caught out by liver fluke risk periods that are longer and extend beyond what would traditionally have been expected. Triclabendazole resistance is an increasing problem in many parts of the country and with no new flukicides on the horizon, existing products need to be used responsibly to ensure they remain useful for as long as possible.

Achieving fairness in the food system

AbstractThe challenge of feeding an additional 2 billion people by 2050 is one of the most pressing issues of our generation. The required changes in the current food system must be achieved while reducing the negative environmental impacts of current farming practices on our climate and biodiversity and avoiding deforestation. This formidable challenge must be overcome in a projected climate that is more variable and where extreme weather events are increasingly common. While the green revolution, agricultural land expansion and agrotechnological innovations have significantly increased crop productivity over the last 50 years, the gains in the yields of most major crops have reached a plateau. Moreover, global hunger remains at a record high. Climate change‐associated changes in weather patterns have decreased the yields of major crops. Further land expansion is impossible without severe trade‐offs with biodiversity and climate change mitigation. Wars and pandemics are currently severely disrupting the global agri‐food system, increasing prices and exacerbating food insecurity, with the world's poorest suffering the most. The climate change–social instability nexus will continue to cause additional stress to the agri‐food system. Here, we consider the inequities in the current food system, highlighting the weak interconnection among research, policy and societal action that is hindering mitigation and adaptation efforts. We argue that improved interconnections among research, policy, governance and societal action will unlock the potential to achieve food security while supporting climate change mitigation targets. Our analysis includes specific strategies such as strengthening small‐scale farmers, promoting fair trade practices and reducing food waste to achieve these goals.

Climate and Kidney Injury: A Look at the Impact of Meteorological Factors on Kidney Function within Colorado

Abstract Acute kidney injury (AKI) and chronic kidney disease (CKD) are serious health conditions with an enormous global health burden. There is evidence to suggest that CKD rates are increasing within the United States despite declines in traditional risk factors for kidney injury and disease, disproportionately impacting certain populations. Changes in meteorological factors because of climate change may be partially responsible for this increase in kidney injury. This study evaluated the association between AKI and meteorological factors controlling for demographic and health factors among adults within the San Luis Valley, Colorado, a rural, biethnic agrarian community at increased risk for health impacts from climate change, over a 15-yr period. Relative humidity was a significant predictor of AKI controlling for age, sex, history of hypertension, and history of diabetes. Changing weather patterns may increase the risk of AKI and the subsequent development of CKD within the United States. These findings may help public health practitioners and medical professionals to identify populations at risk of incurring acute or chronic kidney injury as seasonal weather patterns change. Further research should investigate the role of heat, heat stress, and dehydration in developing CKD in the United States.

Influence of Temperature on the Viscoelastic Behavior and Durability of Flexible Pavements

This study meticulously examines the impact of temperature variations on the viscoelastic characteristics of flexible pavements composed of mineral aggregates and bituminous binders. The primary objective is to understand how temperature fluctuations affect the structure and durability of these pavements, designed to withstand traffic loads while absorbing stresses induced by weather conditions. The methodology involves a thorough analysis of a range of temperatures from T1 to T4, assessing their effects on road rutting and the longevity of pavement infrastructure. Through a detailed analytical approach, the research investigates the viscoelastic behavior of bituminous mixes, which display viscous and elastic properties that change with temperature. The findings reveal significant correlations between temperature variations and the performance of flexible pavements, offering insights into their structural resilience and durability under different climatic conditions. This research introduces a novel approach to managing flexible pavement infrastructure by enhancing our understanding of the temperature-induced viscoelastic response. The improvement lies in the precise quantification of temperature impacts, which can inform better maintenance and design strategies for flexible pavements. Ultimately, this leads to more resilient and long-lasting road surfaces, addressing the critical need for durable infrastructure in changing weather patterns. Doi: 10.28991/CEJ-2024-010-07-06 Full Text: PDF

Emerging Risk to Dengue in Asian Metropolitan Areas Under Global Warming

AbstractAedes sp. mosquitoes are changing their geographic range in response to climate change. This is of concern because these mosquitoes can carry dengue fever and other viral diseases. Changing weather patterns can also increase the numbers of Aedes mosquitoes, leading to greater human exposure and enhancing population health risks. We project the geographic distribution of Aedes and associated changes in populations exposed to dengue in Asian metropolitan areas under warming scenarios from 1.5°C to 5.0°C above pre‐industrial temperatures, using multi‐model ensembles. With global warming, the southern part of the Arabian Peninsula, the coast of the Arabian Sea in southern Iran, southern Pakistan in West Asia, the Korean Peninsula, most of the Japanese islands, and parts of North China in East Asia are projected to become suitable for dengue transmission. The numbers of metropolitan areas exposed to dengue is projected to change from 142 (48%) in the reference period (1995–2014) to 211 (71%) at 5.0°C warming. With the combined impact of socioeconomic and climate change, population exposure to dengue in Asian metropolitan areas is projected to increase from 263 (multi‐model range 252–268) million in 1995–2014 to 411 (394–432) million, 446 (420–490) million, 509 (475–601), 558 (493–685) and 587 (529–773) million, respectively, at 1.5°C, 2.0°C, 3.0°C, 4.0°C and 5°C warming, with an average of 2.9 million new people exposed to dengue fever in metropolitan areas each year.