Climatic Change最新文献

The urban heat island (UHI) phenomenon is concurrently influenced by urban expansion and climate change. However, the individual impacts of land use/land cover (LULC) changes and climate change remain unclear. In the present study, a high-resolution numerical Weather Research and Forecasting (WRF) model coupled with a single-layer urban canopy model (UCM) is implemented for Hefei to assess the influences of LULC and climate change simultaneously. The comprehensive increase in UHI intensity (UHII) was 0.76 K from 2003 to 2019 in the study area. The overall influence of LULC changes on the UHI effect was a 0.33 K increase in intensity and a 190 km² expansion in coverage. The results also show that the emergence of new high-intensity urban areas developed from farmlands had the strongest impact on UHI development compared to other types of LULC changes. The overall contribution of climate change to the UHII increased by 0.27 K from 2003 to 2019. The change in the storage heat flux was found to be responsible for the nocturnal UHII variation and long-term increase in the UHII, while the sensible heat flux was responsible for the diurnal UHII.

Prominent multidecadal rainfall trends and trend reversal points in the Indian summer monsoon rainfall during 1901–2020 across the four homogeneous regions of India have been examined beginning at the district level. Employing a robust rainfall pattern identification methodology, three significant rainfall trend reversal events have been identified during 1930s, 1960s, and 1980s. During the 1930s, central and northeast India witnessed a shift from increasing to decreasing rainfall trends, while the south peninsula experienced the reverse, resulting in a pronounced north-south asymmetry in rainfall pattern over India. In the 1960s, south peninsula and northwest India exhibited a reversal in rainfall trend from increasing to decreasing, with an opposite trend in northeast India, resulting in an east-west asymmetry in the rainfall pattern. Unlike the 1930s and 1960s, the rainfall trend reversal during the 1980s occurred over all four rainfall homogeneous regions. The three regions (south peninsula, central, and northwest) in India experienced rainfall trend reversal from decreasing to increasing trends, while the northeast experienced the opposite trend reversal, establishing an east-west asymmetry in the rainfall pattern. In terms of geographical extent, the rainfall trend reversal in the 1980s is the most prominent event during the last 120 years of Indian rainfall history as the maximum geographical area (~ 50%) experienced the rainfall trend reversal during this period. In terms of magnitude of rainfall amount variation, the rainfall trend reversal during the 1930s is the most prominent as more than 30% of the area had significantly higher (or lower) rainfall than the long-term average. Temporal changes are observed in the identified spatial asymmetry of rainfall pattern indicating that rainfall homogeneous regions in India must have changed over time.

Although the social and spatial dimensions of climate impacts are increasingly recognized, livelihood vulnerability studies combining gender and agro-ecology have received less attention. Moreover, to the best of our knowledge, these studies have not employed stepwise Principal Component Analysis (PCA).This study examines livelihood vulnerability to climate change and variability from gender and agro-ecological perspectives in Bako-Tibe District, Ethiopia. Rural livelihood analysis was used to measure the adaptive capacity of households. Two-stage PCA was employed to index vulnerability dimensions: sensitivity and exposure in the first stage, and adaptive capacity in the second stage. The results show that disparity in adaptive capacity largely mediates vulnerability levels. Further, for agro-ecological factors, households residing within more climate exposure have better adaptive capacity; hence, they are less vulnerable than those in lower exposure agro-ecology. In all comparisons, female-headed households are significantly more vulnerable than male-headed households, but do not necessarily possess lower adaptive capacities. While agro-ecological and gender-specific factors differentiate vulnerability of male-and female-headed household across agro-ecologies, only gender-specific factors set such variations at district level and within agro-ecology. The results imply that scrutinizing the potential sensitivity of vulnerability level to study context is crucial. Results also suggest that, managing agro-ecological and/or gender-specific factors that hamper livelihood assets is vital for reducing climate-induced vulnerability.

The concrete damages of climate change are intensifying, and adaptation efforts of actors around the world are increasing, especially in coastal regions. Recommending adaptation measures for specific regions and sectors and determining long-term strategies for mitigating global climate change is essential for reducing vulnerability to climate change. This research aims to estimate the changes in climatic parameters and thermal comfort zones to determine concrete targets and offer suggestions for sectors affected by possible changes. The changes that will occur until 2100 in the Antalya basin, which is located in the southernmost part of Türkiye and is a significant hub for agricultural production and tourism, were monitored spatially using Discomfort Index (DI) and Effective Temperature taking wind velocity (ETv). The Shared Socioeconomic Pathways (SSP): SSP 245 and SSP 585 predict that the quite cool areas prevailing in the area, according to ETv, will shrink by 24% and 46%, respectively, and the prevailing cold areas, according to DI, will shrink by 45% and 56%, respectively. By 2100, 5% of the area, according to SSP 245, and 25%, according to SSP 585, will turn into hot areas and move away from the comfort level. The fact that critical regions are areas with high vitality in terms of coastal tourism shows the need to prioritize adaptation policies. These discoveries are discussed in the context of critical issues such as water scarcity and food security, contributing to policy-making for effective management by suggesting specific adaptation measures.

The study examined the behavioural intention to adopt climate-smart agricultural practices (CSA) and its impact on the food-nutrition security (FNS) of farming households in South Africa. We employed a multistage sampling procedure to select rural maize farmers across the selected villages. To determine the impacts of behavioural adoption of CSA on the FNS of farming households, endogenous switching regression model (ESRM) was employed, while household dietary diversity score (HDDS) and household food insecurity access score (HFIAS) were used to determine the FNS status of the households. The findings emphasized the significance of the behavioural intentions of rural maize farmers, assessed through their attitudinal dimensions (measured in terms of perceived social norms, behavioural intentions, and control) in influencing the adoption decision of CSA practices, hence CSA adoption positively impacts FNS in South Africa. The result indicates that households that adopt CSA observe a 27% and 23% increase in HDDS and a decrease in HFIAS compared to those who do not adopt CSA practices, respectively. Thus, the outcome illustrates that the adoption of CSA practices substantially enhances the HDDS and HFIAS of rural maize farming households in South Africa. Following this backdrop, a concerted effort to raise knowledge of CSA practices through disseminating pertinent information will exert influence on the farmers' adoption behaviour towards CSA practices, which is capable of improving the FNS of rural maize farmers.

In a world of increasing pressures from climate change, water utilities need to maintain—or even improve—their ability to continue provision safe and secure water supply. To ensure capacity in service delivery, some providers have embraced different forms of interlocal collaboration. Yet, such interdependence engenders risk, thus driving some collaborating providers to enter into contractual agreements. While these agreements can reduce risk, but new complexities may still arise, especially when the agreement is capital intense and physically constrained. This study asks: i) How does perceived risk of from external climate-related pressures to public service provision affect preferences for the future of current contractual agreements? and ii) how do local efforts to offset need for collaboration shape these future preferences? This study examines how beliefs and local strategies (i.e., technical, managerial, or programmatic advances) affect contract preferences among community water systems linked through interlocal agreements. The paper discusses insights about ways ontological beliefs may shape operational decisions specific to interlocal collaboration and the potential for consolidation of water service operations.

Based on the historical (period of 1990–2014) spatial and temporal ranking, a future projection of four extreme precipitation indices over Iran is conducted. A multi-model ensemble approach and a rank-based weighting method with ten models from the CMIP6 dataset are used for this projection. The weight of each model is calculated based on its historical simulation skill, and weighted models are employed for future projections across three periods (2026–2050, 2051–2075, and 2076–2100), under four Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The results show that an increase in total extreme precipitation (R95p) and the absolute intensity of extreme precipitation (AEPI) in Iran is almost certain in all periods, under all scenarios. The maximum increase of the R95p index is 10%, and the probability of its increase in all periods and scenarios (except for SSP1-2.6 scenario in the 2076–2100 period) exceeds 50%. This probability of increase is particularly high in the first period, ranging from 70 to 90%. In all periods and scenarios, the median of the number of days with extreme precipitation (R95d) is close to zero or negative. This index exhibits a decrease compared to the historical period, with a probability of over 60%, except for the 2026–2050 period under SSP1-2.6 and SSP5-8.5 scenarios. Furthermore, the probability of an increase in the AEPI compared to the historical period is more than 75%. This study finds no significant increase or decrease in the fraction of total rainfall from events exceeding the extreme precipitation threshold (R95pT).

Climate change is expected to increase the frequency of severe droughts. As water scarcity can destroy vital resources such as crops and livestock, droughts pose major challenges to affected societies. Concerns arise that the resulting hardship and suffering could exacerbate social tensions. Trust in the political system, defined as citizens’ overall confidence in the state to deliver satisfactory outcomes, is an integral foundation of stable state-society relations. To illuminate under what conditions droughts might exert a destabilizing effect, investigating their impact on trust in the political system is paramount. Our study is the first to investigate how drought exposure influences citizens´ overall confidence in the political system. Previous research shows that citizens tend to lose trust when dissatisfied with the living conditions and output that a system provides. While droughts emerge gradually and, thus, give states multiple opportunities to intervene, states in the Global South often struggle to master the challenging task of drought management, thereby demonstrating inadequate, dissatisfactory state performance. We argue that failures in successful drought management showcase what goes wrong in a political system, which in turn leads to an erosion of trust in the political system. Using individual-level survey data from Afrobarometer round five, matched with high-resolution water scarcity data, our analysis reveals that recently drought-exposed individuals exhibit significantly lower levels of trust in the political system compared to their unaffected counterparts. This effect is most pronounced in sub-national regions with low state capacity, where the implementation of successful drought relief measures might be particularly difficult.

This paper examines how rising temperatures impact the agricultural production value of Thai farmers, compares potential adaptation strategies like agricultural diversification, and analyzes future projections based on IPCC AR6 scenarios. We analyze nationally representative socioeconomic survey data from farm households alongside ERA5 weather data, utilizing econometric regression analysis. Our analysis reveals that higher temperatures lead to a reduction in agricultural output value, with the situation expected to worsen as global warming progresses. Furthermore, we find that households with diversified production practices, such as a variety of agricultural activities or multicropping, exhibit a greater capacity to adapt to rising temperatures. These findings substantiate the importance of the country’s policies promoting integrated farming and diversified crop-mix strategies.

Water resources managers face decisions related to building new infrastructure to increase water system resilience to climate and demand changes. To inform this adaptation planning process, current decision-making methods commonly use scenario approaches to estimate the benefit of adaptation options. While effective, these new analyses require communication of complicated findings to often nontechnical audiences. This paper introduces a pragmatic approach that uses the results from a bottom-up assessment of vulnerability of the water system with future climate projection-based probabilities of climate change to select a single planning scenario that encapsulates the decision-makers’ chosen level of robustness for their system. Contrary to typical implementation of option analysis under deep climate uncertainty, the proposed pragmatic approach does not require the analyst to evaluate each portfolio of adaptation options against all possible states of the world, significantly reducing the required computational costs and communication challenges. It also aligns with the planning scenario approach used in practice by water utilities. The modeling framework is illustrated for the regional water system operated by the San Francisco Public Utilities Commission (California, United States) for which changes in average temperature, precipitation and urban demand are considered.