Effects Of Extreme Weather Events Research Articles

The interactive effect of extreme weather events and PM2.5 on respiratory health among the elderly: a case-crossover study in a high-altitude city.

With climate change posing increasing threats and aging populations, understanding the complex relationship between extreme temperatures, PM2.5 pollution, and respiratory health among the elderly is crucial. While some research exists, there remains a significant gap in studying the combined effects of heat waves, cold spells, and PM2.5 on elderly respiratory health in high-altitude regions. We collected data from Xining (2016-2021), including respiratory disease outpatient visits, meteorological, and pollutant data. Employing a case-crossover design and conditional Poisson regression analysis, we investigated the individual and interactive impacts of heat wave, cold spell, and PM2.5 on outpatient visits for respiratory disease among the elderly. We used the relative excess odds due to interaction (REOI), proportion attributable to interaction (AP), and synergy index (S) as quantitative indicators of interaction. Our analysis revealed significant associations between heat wave, cold spell, PM2.5 exposure, and outpatient visits for respiratory disease among the elderly, with odds ratios of 1.10 (95%CI: 1.06, 1.15) and 1.16 (95%CI: 1.13, 1.20), respectively. Moreover, a synergistic effect between cold spell and PM2.5 was observed, particularly affecting vulnerable groups such as female and those aged ≥ 80. The combined exposure to cold spell and elevated PM2.5 levels was estimated to contribute to up to 0.18 (95%CI: 0.17, 0.27) of respiratory outpatient visits. This study underscores the need for urgent interventions, such as reducing PM2.5 exposure and enhancing extreme weather warning systems, to protect the respiratory health of the elderly, especially in high-altitude regions.

Decision Support Framework for Water Quality Management in Reservoirs Integrating Artificial Intelligence and Statistical Approaches

Planning, managing and optimising surface water quality is a complex and multifaceted process, influenced by the effects of both climate uncertainties and anthropogenic activities. Developing an innovative and robust decision support framework (DSF) is essential for effective and efficient water quality management, so it can provide essential information on water quality and assist policy makers and water resource managers to identify potential causes of water quality deterioration. This framework is crucial for implementing actions such as infrastructure development, legislative compliance and environmental initiatives. Recent advancements in computational domains have created opportunities for employing artificial intelligence (AI), advanced statistics and mathematical methods for use in improved water quality management. This study proposed a comprehensive conceptual DSF to minimise the adverse effects of extreme weather events and climate change on water quality. The framework utilises machine learning (ML), deep learning (DL), geographical information system (GIS) and advanced statistical and mathematical techniques for water quality management. The foundation of this framework is the outcomes from our three studies, where we examined the application of ML and DL models for predicting water quality index (WQI) in reservoirs, utilising statistical and mathematical methods to find the seasonal trend of rainfall and water quality, exploring the potential connection between streamflow, rainfall and water quality, and employing GIS to show the spatial and temporal variability of hydrological parameters and WQI. Three potable water supply reservoirs in the Toowoomba region of Australia were taken as the study area for practical implementation of the proposed DSF. This framework can serve as a comprehensive mechanism to identify distinct seasonal characteristics and understand correlations between rainfall, streamflow and water quality. This will enable policy makers and water resource managers to enhance their decision making processes by selecting the management priorities to safeguard water quality in the face of future climate variability, including prolonged droughts and flooding.

Climate change impacts on maternal health and pregnancy outcomes in Africa

ABSTRACT The review examines how climate change adversely affects maternal health and pregnancy outcomes in Africa, a region particularly vulnerable to climate-related disasters. It highlights the increased incidence of tropical and waterborne illnesses due to climate change, disproportionately impacting expectant mothers. The study thoroughly evaluates the effects of extreme weather events like heatwaves and floods on maternal health, both directly and indirectly. It underscores significant gaps in policy and research within African health sectors regarding these issues. Key findings reveal that maternal death rates remain alarmingly high, with risks like preterm birth, stillbirth, and maternal hypertension exacerbated by climate change. The review calls for urgent action, including enhanced research, increased funding for climate adaptation, and the integration of maternal health into broader climate resilience strategies. Additionally, it emphasizes the need for greater awareness and international collaboration to strengthen health systems in Africa, particularly addressing the vulnerabilities of pregnant women. This work aims to enhance understanding among policymakers and researchers about the critical health impacts of climate change on pregnant women in Africa.

Mitigating the Negative Financial Effects of Extreme Weather Events Through Supply Chain Analytics

Despite extensive discussions on the value of integrating big data analytics into supply chains, or supply chain analytics (SCA) for short, it remains unclear whether SCA can effectively help firms mitigate the negative financial impacts of extreme weather events. To address this important research question, we first employed the event study methodology to quantify extreme weather events’ financial effects in terms of abnormal stock returns. Then, we compared the difference in abnormal stock returns between firms that have adopted SCA and matched control firms without SCA adoption. Our event study results indicate that, although these events affected firms’ stock returns negatively, the effects were less severe for firms with (rather than without) SCA adoption. Furthermore, our results suggest that firms having more stable innovation outputs will reap greater benefits from SCA in the extreme weather context. Conversely, firms facing more unstable market demands will benefit more from SCA in the extreme weather context. Overall, our research demonstrates the mitigating role played by SCA during extreme weather events but also reveals how this mitigating role is contingent on the firm’s internal and external operating uncertainties.

Extreme weather events and disruptions to HIV services: a systematic review.

Extreme weather events pose a risk to health and disproportionately affect vulnerable groups, such as people living with HIV. We aimed to investigate the effects of extreme weather events on HIV testing uptake, HIV treatment and care, and HIV transmission. For this systematic review, we searched PubMed, Web of Science, and PsycINFO for peer-reviewed studies published between database inception and Aug 31, 2023. Eligible studies were English-language qualitative, quantitative observational (retrospective, prospective, cross-sectional, longitudinal, case-control, and cohort), and mixed-method studies, and randomised controlled trials related to HIV and extreme weather events. We excluded reviews, mathematical models, and case reports. After exporting the search results, two authors independently screened the titles and abstracts of identified articles, reviewing the full text of those that met the inclusion criteria. We used systems thinking to develop a framework linking extreme weather events and HIV and summarised the results using thematic narrative synthesis. Of the 6126 studies identified by the search, 27 met the inclusion criteria and were eligible for analysis, of which 19 were quantitative, six were qualitative, and two were mixed-method studies. We identified five main themes linking extreme weather events to HIV: economic and livelihood conditions (12 studies), psychosocial factors (19 studies), infrastructure damage and operational challenges (17 studies), migration and displacement (ten studies), and associated medical conditions and health-care needs (12 studies). We showed how these themes interact in complex ways, resulting in a reduction in uptake of HIV testing, interruption of HIV care and subsequent disease progression, altered risk behaviours, and an increased prevalence of HIV. Extreme weather events are associated with disruptions to HIV services. Owing to the design of the included studies, we could not establish a causal relationship between extreme weather events and HIV incidence, highlighting a research gap. Appropriate adaptations and mitigation policies that protect the health and wellbeing of people living with HIV during and after extreme weather events are warranted. Such actions will be crucial to achieving the UNAIDS goal of ending HIV as a public health threat by 2030. None.

The effect of extreme weather events on the frequency of child marriage: A systematic review of the evidence

AbstractChild marriage is considered a human rights violation, and its elimination is an explicit target of the United Nations Sustainable Development Goals. However, there is growing concern that climate change may be threatening efforts to eliminate child marriage. We conducted a systematic review to synthesise quantitative research on the relationship between climate change and child marriage and assess the risk of bias across these studies. We identified 18 studies from an interdisciplinary range of databases. Several studies found that child marriage was correlated with droughts and floods. However, because of the high risk of bias across studies, differences in the vulnerability of the populations studied, and differences in the definitions of extreme weather used, we are unable to draw broad conclusions about whether extreme weather events increase or decrease the rate of child marriage. We discuss common biases across studies and provide suggestions for improving the strength of evidence on this topic.

Climate change mitigation and women’s economic empowerment

In Pakistan, a country acutely vulnerable to climate change, this study delved into the gendered dynamics of climate sensitivity. It analyzed the correlation between gender and climate vulnerability, with a particular focus on the disproportionate influences on women and the efficacy of adaptation policies. The results showed stark gender disparities in health outcomes, with women more susceptible to the harmful effects of extreme weather events. Women in rural areas struggle to maintain their livelihoods due to water and pasture scarcity, affecting the cattle industry. Additionally, women in agriculture face economic hardships, resource constraints, and societal barriers that compound the adverse effects of climate change on their livelihoods. The paucity of food and water presents significant concerns, resulting in malnutrition and health hazards for women. Women in rural locations are compelled to depend on detrimental fuel sources due to energy shortages, which adversely affect their respiratory health. Conversely, in metropolitan settings, women have limitations in accessing vital services. The study highlights the importance of implementing policies that are sensitive to gender issues and include women in the decision-making processes related to climate change in order to establish communities that are able to withstand and recover from adverse conditions. The policy implications encompass several measures such as adapting to climate change, ensuring women's participation, investing in assistance for rural livelihoods, managing disasters, and promoting gender equality in climate governance. It is crucial to raise awareness and educate people about the gender-specific impacts of climate change in order to strengthen resilience.

Site characteristics determine the prevalence of extreme weather events affecting freshwater macroinvertebrate communities

Understanding the impacts of extreme weather events on freshwater ecosystems is imperative during a time when a multitude of challenges compromises these environments' health. Exploring how such events affect macroinvertebrate communities in rivers sheds light on the resilience of freshwater ecosystems, which is essential for human well-being and biodiversity conservation. In this study, long-term time series of benthic macroinvertebrate communities from four sites along three freshwater streams within the Rhine-Main-Observatory Long-Term Ecological Research site in Germany were analyzed. Each of them was sampled annually over a span of ~20 years to assess the impacts of extreme weather events (floods, droughts, and extreme heat) on macroinvertebrate communities. The findings reveal that the effects of extreme events are site-specific, suggesting that the impacts of an extreme event can vary based on several potential factors, including the life history traits of the organisms within the community and, among others, the hydrography of the site. Moreover, the analysis highlights that the cumulative impact of these events over time is more significant than the impact of a single event's magnitude, while following distinct temporal dynamics. This underscores the importance of considering both the temporal dynamics and the biological characteristics of communities when evaluating the consequences of extreme weather events on biodiversity, illustrating that the resilience of freshwater ecosystems and their biodiversity under such conditions depends on a complex interplay of factors rather than the severity of individual events.

Detecting Vegetation Stress in Mixed Forest Ecosystems Through the Joint Use of Tree‐Water Monitoring and Land Surface Modeling

AbstractRecent European heatwaves have significantly impacted forest ecosystems, leading to increased plant water stress. Advances in land surface models aim to improve the representation of vegetation drought responses by incorporating plant hydraulics into the plant functional type (PFT) classification system. However, reliance on PFTs may inadequately capture the diverse plant hydraulic traits (PHTs), potentially biasing transpiration and vegetation water stress representations. The detection of vegetation drought stress is further complicated by the mixing of different tree species and forest patches. This study uses the Community Land Model version 5.0 to simulate an experimental mixed‐forest catchment with configurations representing standalone, patched mixed, and fully‐mixed forests. Biome‐generic, PFT‐specific, or species‐specific PHTs are employed. Results emphasize the crucial role of accurately representing mixed forests in reproducing observed vegetation water stress and transpiration fluxes for both broadleaf and needleleaf tree species. The dominant vegetation fraction is a key determinant, influencing aggregated vegetation response patterns. Segregation level in PHT parameterizations shapes differences between observed and simulated transpiration fluxes. Simulated root water potential emerges as a potential metric for detecting vegetation stress periods. However, the model's plant hydraulic system has limitations in reproducing the long‐term effects of extreme weather events on needleleaf tree species. These findings highlight the complexity of modeling mixed forests and underscore the need for improved representation of plant diversity in land surface models to enhance the understanding of vegetation water stress under changing climate conditions.

Temporal patterns of carbon-water coupling of a subalpine peatland in subtropics: Insights from a seven-year eddy covariance monitoring

Study regionA well-preserved subalpine peatland in the subtropics, the Dajiuhu peatland, in Shennongjia, Hubei Province, China. Study focusOver a seven-year period, constant in-situ carbon flux monitoring was conducted using the eddy covariance method. The patterns of CO2 and H2O fluxes were analyzed, encompassing both daytime and nocturnal period observations, spanning both growing and non-growing seasons, and the interconnection between carbon and water within the Dajiuhu peatland. Furthermore, this investigation identified meteorological parameters shaping these flux dynamics. New hydrological insights for the regionThe water source function was more resilient to the effects of extreme weather events and showed higher stability when compared to the carbon sink function. Daytime carbon-water coupling presented a pronounced negative correlation during the growing season, contrasting with a more complex trinomial relationship evident during the non-growing season; however, nocturnal periods did not reveal any apparent correlation. Relative humidity (RH), water table depth (WTD), and evapotranspiration (ET) emerged as key variables impacting jointly on both CO2 and H2O fluxes. Furthermore, net radiation (Rn) magnifies the hysteresis loops associated with net ecosystem exchanges of CO2 (NEE) during the growing season, with WTD being the prime determinant influencing seasonal fluctuations in hysteresis related to H2O fluxes. These findings exemplify the complexities inherent in the management of carbon and water resources within subalpine peatlands, underscored by their intricately intertwined and inseparable relationship.

Extreme Weather and Firm Market Value: Roles of Corporate Social Responsibility and Stock Analyst Attention

ABSTRACT The outbreak of extreme weather events is increasing in frequency for the last decade, resulting in tremendous human and industrial losses worldwide. Evaluating and managing the effects of such events are highly urgent matters for firms, but the literature on this topic is limited. In this study, the effects of extreme weather events on the stock market performance of firms were estimated to provide a foundation for exploring how to manage such effects. From the perspective of the shareholder view, the heterogeneous effect of corporate social responsibility (CSR) on stock performance associated with extreme weather events were examined. Data on natural disasters that were caused by six types of extreme weather and occurred between 2001 and 2021 in China were used to construct a database of 2,718 Chinese listed manufacturing firms and 23,529 observations regarding the potential effects by extreme weather events. An event analysis indicated that the extreme weather events bring an average of 0.97% drop in the stock performance of potentially affected firms for the month that the event starts and the next month. A subsequent cross-sectional analysis revealed that a high CSR level is associated with low market value during extreme weather events, while a high level of stock analyst attention alleviates the negative effect of CSR on the stock performance of extreme weather events. This study enriches the existing literature and offers practical insights for managers in the fields of CSR and operations management, highlighting the complex dynamics between CSR activities, analyst attention, and stock market performance during extreme weather events.

The Integrating Impacts of Extreme Weather Events and Shrimp Farming Practices on Coastal Water Resource Quality in Ninh Thuan Province, Vietnam

Ninh Thuan is a coastal province in the central region of Vietnam and is characterized by a climate that is the hottest and driest in the country. Vietnam is also one of the top five countries most vulnerable to the effects of climate change worldwide. The objective of this study was a thorough evaluation of the quality of water supply sources and the impacts of water effluents from shrimp farms in Ninh Thuan province. The comprehensive evaluation was based on an understanding of the water–wastewater cycle employed in coastal shrimp cultivation. We combined qualitative and quantitative analyses in undertaking this study. Secondary data of groundwater and coastal water from the local periodic water quality monitoring program and national technical regulations were collected in the qualitative approach. We also integrated participatory rural appraisal techniques and field observations to understanding shrimp cultivation and the environmental and social impacts of shrimp farm effluents. The quantitative assessment consisted of measuring groundwater and wastewater contamination from shrimp ponds. As a result, four main reasons for water pollution issues were determined including extreme weather events, shrimp cultivation practices, degraded infrastructure, and mismanagement by local governance. Shrimp cultivation practices (feeding, using chemicals) have resulted in elevated levels of suspended solid (TSS, total Coliform), organic and carbon matter (BOD5, COD), and excessive nutrients (total Nitrogen, NO2-N, NO3-N, PO4-P). According to a local monitoring program, the coastal water and groundwater have experienced nutrient pollution. Groundwater sampling near the shrimp farms identified salinization elevated levels of Coliform from local domestic sewage sources. This study resulted in an integrated approach that evaluated the combined effects of extreme weather events and shrimp farming practices on the quality of coastal water. Also, the finding can be useful in recommending remedial water treatment technologies as a follow-on phase.

ANALYSE DE L’INFLUENCE DES PARAMETRES METEOROLOGIQUES SUR LA PLUVIOMETRIE A KINSHASA

The understanding of meteorological parameters influencing rainfall is essential to effectively address environmental challenges and anticipate the consequences of extreme weather events. In this study, we analyze meteorological data provided by the Airways Authority of Kinshasa (RVA), covering the period from 1992 to 2019. This in-depth statistical analysis aims to better understand the factors that influence precipitation in the region and to identify relevant climate trends for anticipating future environmental changes. We used logistic regression to assess the impact of various climatic factors such as temperature (daily extremes), relative humidity, and atmospheric pressure on precipitation. The results indicate that minimum temperature, relative humidity, and atmospheric pressure show a strong correlation with rainfall in Kinshasa, highlighting their significant influence on the likelihood of precipitation. In contrast, maximum temperature has a limited impact, making it a less reliable indicator of rainfall in the city. The conclusions of this study provide valuable tools for local authorities in developing effective strategies for managing climate variations and predicting weather phenomena. These insights enable precise modeling of the impacts of meteorological fluctuations on ecosystems and urban infrastructure. Furthermore, the results of this research can guide local farmers in optimizing their agricultural practices by adjusting planting and harvesting schedules based on detailed weather forecasts, thereby minimizing economic losses and enhancing crop resilience to climate variations. Finally, this study provides climatologists with robust data for in-depth analysis of the effects of climate change on meteorological phenomena in Kinshasa. This knowledge is crucial for refining regional climate models and developing specific adaptation strategies for other urban areas in sub-Saharan Africa.

Bivariate extreme value analysis of extreme temperature and mortality in Canada, 2000-2020.

Climate change increases the risk of illness through rising temperature, severe precipitation and worst air pollution. This paper investigates how monthly excess mortality rate is associated with the increasing frequency and severity of extreme temperature in Canada during 2000-2020. The extreme associations were compared among four age groups across five sub-blocks of Canada based on the datasets of monthly T90 and T10, the two most representative indices of severe weather monitoring measures developed by the actuarial associations in Canada and US. We utilize a combined seasonal Auto-regressive Integrated Moving Average (ARIMA) and bivariate Peaks-Over-Threshold (POT) method to investigate the extreme association via the extreme tail index and Pickands dependence function plots. It turns out that it is likely (more than 10%) to occur with excess mortality if there are unusual low temperature with extreme intensity (all except Northeast Atlantic (NEA), Northern Plains (NPL) and Northwest Pacific (NWP) for age group 0-44), while extreme frequent high temperature seems not to affect health significantly (all except NWP). Particular attention should be paid to NWP and Central Arctic (CAR) since population health therein is highly associated with both extreme frequent high and low temperatures (both for all age groups). The revealed extreme dependence is expected to help stakeholders avoid significant ramifications with targeted health protection strategies from unexpected consequences of extreme weather events. The novel extremal dependence methodology is promisingly applied in further studies of the interplay between extreme meteorological exposures, social-economic factors and health outcomes.

The effect of different extreme weather events on attitudes toward climate change.

Can exposure to extreme weather change political opinion and preferences about climate change? There is a growing literature on both the effects of extreme weather events and the factors explaining attitudes toward global warming, though there remains no clear consensus about whether being exposed to extreme weather influences public opinion about climate change. We contribute to this literature by studying the impact of a variety of extreme weather events associated with climate variability, including severe storms, floods, fires, and hurricanes, on attitudes toward climate change. Specifically, we use a three-wave panel survey and a dynamic difference-in-differences design to analyze public opinion data at the individual level in the US. We find that exposure to only one extreme weather type-fires-has a small but significant effect on acknowledging the existence of climate change and supporting the need for action. However, that impact quickly vanishes, and other types of extreme weather do not appear to have any effect on opinion.

CLIMATE CHANGE AND IT’s EFFECTS ON MANUFACTURING SECTOR

This research examines the complex link between the industrial sector and climate change, evaluating the effects of extreme weather events and rising global temperatures. It seeks to understand the many ways that environmental changes impact industrial operations, with a focus on how resource constraints, weather patterns, and environmental laws affect production sustainability and efficiency. By employing case studies, statistical analysis, and sophisticated modelling, the study pinpoints the industries, regions, and production processes that are susceptible to disruptions caused by climate change. Potential disadvantages are discussed along with chances for innovation and broad adoption of green technology. The research highlights the need for collaboration among politicians, business stakeholders, and environmental activists in achieving significant change. The paper advocates for collaborative efforts to enhance manufacturing sustainability and resilience by emphasizing the links between environmental effects and industrial innovation. The intention is to give policymakers and business leaders a road map for creating strategies that reduce risks and promote long-term development. This research offers comprehensive insights into possibilities, problems, and strategies related to manufacturing's sustainable growth and adaptation to climate change, which makes a substantial contribution to the worldwide discourse on these topics. To support educated decision-making and positive change for an environmentally conscious industrial landscape, it offers legislators, business partners, and environmentalists an invaluable resource for understanding, navigating, and addressing the profound effects of climate change on the manufacturing sector.

U.S. military installations and extreme weather: an Oklahoma case study on preparation

ABSTRACT The readiness and execution of national security missions by The United States Department of Defense (DoD) hinges on military installations being equipped with infrastructure that can support the actions needed to protect the U.S., including extreme weather responses. Extreme weather threatens human lives, property, and military operations nationally. Thus, it is paramount to mitigate these impacts and improve preparedness. Oklahoma is home to five federal military installations, all of which are susceptible to hazardous weather, such as severe thunderstorms, tornadoes, and flooding. At a local level, hazardous weather events can be quite costly in a variety of ways, including disrupting operations, causing economic losses, and leading to injuries. This case study examines the preparedness and impacts of extreme weather events as well as climate change considerations at two Oklahoma military installations (Tinker Air Force Base and Fort Sill). Interviews and a focus group revealed weather-related decisions at these installations were unit-specific and dependent on the weather event. These installations have both short- and long-term preparedness plans for different weather scenarios. The impacts of these weather events ranged from delays/cancellations of training to installation closures. Lastly, climate considerations from DoD have been, and continue to be, included in planning. This study highlights the nuances across different military installations as a function of their differing roles; there is not a ‘one size fits all’ preparedness plan that will work across the board. Further, there is much room to improve military-civilian collaboration to mitigate the effects of extreme weather events and climate change on military installations and their operations.

Extreme weather, climate risk, and the lead–lag role of carbon

This study employs the thermal optimal path method to establish a framework for dynamic nonlinear connections between Chinese carbon and foreign exchange markets. Subsequently, it examines the effects of extreme weather events on the lead–lag role played by carbon. The empirical results indicate that China's carbon market typically lags behind its currency exchange market. Compared to the Hubei carbon market, the Guangdong carbon market experiences synchronized price movements between carbon and foreign exchange due to high pricing efficiency. Furthermore, shocks from extreme weather events can attract public attention to the carbon market and cause the typical lead–lag structure to reverse, whereupon the carbon market leads the foreign exchange market under such shocks, especially during heat waves. Our findings have implications for investors aiming for positive cumulative returns on hedging portfolios and policymakers wishing to bolster the financial market's ability to withstand exogenous shocks.

The weather as a determinant of farmer's mental health: A dependent, interacting, cumulative and escalating model (DICE) of the effects of extreme weather events.

This perspective paper presents a conceptual, theoretical framework of the weather as a determinant of mental health for farmers. This model proposes that the effects of extreme weather events have interacting and cumulative effects for farmers, who are dependent on the land.

Spatiotemporal variations of extreme weather events and climate drivers in the Three Gorges Reservoir Area and its surrounding regions from 1960 to 2020

The Three Gorges Reservoir Area and its Surrounding Region (TGRASR) play a crucial role in the Yangtze River Basin. Over the past years, there has been growing concern about the effects of extreme weather events in this area, mainly attributed to climate change. To effectively address the implications of climate change, a thorough understanding of the temporal and spatial variability of these events is necessary. However, some of the previous studies have been limited to analyzing trend changes in events and have not sufficiently considered the connection with atmospheric circulation indices. In this study, we analyzed the spatio-temporal variations of extreme weather events using the Mann-Kendall and Sen's slope trend methods. Then, the correlation between extreme weather events and climate factors is explored using the Mantel test, Geo-Detector method (GDM), and Partial wavelet coherency (PWC) in terms of linear, hierarchical heterogeneity, and nonlinear, respectively. Finally, we investigated the potential climate factors that affect the temporal and spatial variability of extreme weather occurrences. The results showed that(1) among the 12 extreme indices analyzed in the TGRASR region from 1960 to 2020, there was a decreasing trend observed in Consecutive dry days (CDD), Consecutive wet days (CWD), and Annual count of days when precipitation is ≥10 mm (R10), while the remaining indices exhibited an increasing trend. Subsequent analysis employing the M-K mutation revealed that the mutation point for CWD occurred around 1975, resulting in a significant decrease in its trend. Additionally, the Simple daily intensity index (SDII), Annual count of days when the daily maximum temperature (TX) is >25 °C (SU25), and R10 displayed a decreasing trend. Mutations in the trends SU25, Annual count of days when the daily minimum temperature (TN) is >20 °C (TR20), and Annual count of days with at least 6 consecutive days when TX > 90th percentile (WSDI) were observed in 1997, 1999, 2003, and 2005, respectively. Following these mutations, all four indices displayed a substantial increase. (2) CDD, CWD, and R10 exhibit a decreasing trend across most stations, whereas the remaining indices demonstrate an increasing trend. Regarding spatial distribution, indices characterizing precipitation frequency and intensity exhibit higher mean values in the southeastern part of the TGRASR. (3) Mantel test: North Pacific pattern (NP), North Tropical Atlantic (NTA), and Global Mean Land/Ocean Temperature (GMLOT) have significant linear correlations with extreme precipitation and extreme temperature events; GDM: GMLOT and NTA are the main contributors to extreme precipitation and extreme temperature; PWC: 12 extreme indices have some nonlinear associations with all five climate factors. The study's findings can assist decision-makers in formulating sustainable water resource management strategies and measures for mitigating drought and flood risks. Additionally, the study contributes to uncovering climatic factors that influence changes in extreme weather events.