IPCC Research Articles

Beyond default estimates: developing system-specific Tier 2 enteric methane emission factors for rangeland cattle in Kenya

Livestock production in Kenya is a significant source of greenhouse gas emissions, particularly methane (CH4) from enteric fermentation. The objective of the study was to estimate enteric methane (CH4) emission factors (EFs, kg CH4/head/year) for rangeland cattle in Kenya. The study utilized the Intergovernmental Panel on Climate Change (IPCC) Tier 2 method, incorporating animal characteristics, performance data, and diet digestibility. Data were obtained from 1,486 cattle across three locations in Kenya’s pastoral areas: Kapiti Research Station and Wildlife Conservancy (815 cattle), Olkirimatian Community Ranch (347 cattle), and Shompole Community Ranch (324 cattle) all located in southern Kenya. Animal activity data were collected for four seasons during 1 year at Kapiti, and one dry and one wet season in Olkirimatian and Shompole. The EFs were estimated for wet and dry seasons, allowing the calculation of mean annual EFs. The EFs were calculated for the different cattle categories: adult females and males (≥3 years), young males and females (1–3 years) and calves (<1 year). The results revealed significant differences in herd composition, live weight (LW), weight gains, milk yield, and digestible energy (DE) of pasture among the locations, all of which influence CH4 emissions. LW varied among the three locations due to differences in breed between sites and varied substantially compared to Tier 1 assumptions, and DE differed significantly across sites (54.5%–66.4%), despite the Tier 1 approach assuming a fixed DE value for pasture (58%). There was a significant difference (p < 0.05) in the herd level EF of all cattle categories: Kapiti (64 ± 0.9 kg CH4/head/year), followed by Olkirimatian (52 ± 1.2 kg CH4/head/year) and Shompole (42 ± 1.0 kg CH4/head/year). A comparison of the estimated herd level Tier 2 EFs with computed herd level Tier 1 values revealed that Kapiti exhibited 18% higher mean Tier 2 EFs, while it was lower by 7% and 28% in Olkirimatian and Shompole, respectively. These findings highlight the need for system-specific national EFs that better capture the diversity of production systems and breed differences. Policymakers and researchers should revise IPCC default values to incorporate breed-specific factors within systems.

Unpacking “Common Sense”

The years of 2023 and 2024 reminded us again of the urgent need to mitigate climate change. Despite the warnings from climate science, narratives of denial continue to spread on social media. This article aims to explore how climate change rejection becomes naturalized through the construction of “common sense”. Engaging with previous literature on critical folkloristics as an approach to contemporary folklore, I introduce Fredric Jameson’s hermeneutic model for allegorical interpretation as a potential framework for understanding such narratives not merely as peripheral expressions, but as manifestations of broader cultural, social, and historical movements. In the empirical material, the figure of Galileo Galilei serves as a symbol embodying the climate skeptic community while framing the Intergovernmental Panel on Climate Change (IPCC) as an authoritarian force driven by religious beliefs. This allegorical construct reveals a collective identity forged through exclusion and a defense of fossil capitalism, thereby reinforcing existing inequalities and injustices.

Improved Storm Surge Prediction and Extreme Sea Level Future Projections in the Indian Ocean using Deep Learning

Abstract Accurate prediction of storm surges and extreme sea level (ESL) is crucial for effective coastal flood monitoring and hazard management. However, dynamical models for the Indian Ocean often exhibit significant biases when compared to historic tide gauge (TG) based sea level records, highlighting the need for improved methods. To address this gap, we applied a Long Short Term Memory (LSTM) deep learning network to reconstruct hourly storm surges across 29 TG locations along the Indian Ocean coastlines for the period 1979 to 2021. Our results demonstrate the robust performance of the LSTM model, which outperforms existing global surge reconstructions by realistically capturing storm surges associated with tropical cyclones and extreme conditions. We extended this approach to generate future projections of ESL for the Indian Ocean, which has been lacking for the densely populated coastline. The ESL projections are generated by integrating storm surges predicted via LSTM with bias-corrected Coupled Model Intercomparison Project (CMIP6) predictors, tide data from hydrodynamic models, and mean sea level (MSL) from the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6). The findings reveal that future ESL changes will be predominantly driven by mean sea level rise, with contributions from tides and storm surges accounting for approximately 10%. Notably, the analysis indicates a rapid emergence of ESL events in the Indian Ocean. By 2030–2040, equatorial islands are projected to experience the one-in-a-hundred-year ESL (ESL100) annually, and the Arabian Sea coastline and the south subtropical regions by 2050 under a high-emission scenario. The findings underscore the urgent need to implement adaptive measures to safeguard vulnerable coastal populations.

Dynamics of Atmospheric Environment: Key to Understanding Climate Change

Understanding the dynamics of the atmospheric environment is fundamental to comprehending the mechanisms and impacts of climate change at both regional and global scales. This paper provides an in-depth review of key atmospheric processes, including the structural composition and functions of atmospheric layers, global wind and pressure systems, mechanisms of moisture transport, and ozone layer behavior. Particular attention is given to the intricate ways in which anthropogenic activities influence these atmospheric processes. The dynamics of the atmosphere regulate critical climatic variables such as global temperature distribution, rainfall variability, and the frequency and intensity of extreme weather phenomena. Notably, this review explores how modifications in atmospheric circulation patterns—such as the shifting of Hadley Cells, alterations in jet streams, and stratospheric-tropospheric interactions—are reshaping climate behavior across latitudes. The ozone layer, which plays a vital role in maintaining thermal equilibrium and shielding the biosphere from harmful ultraviolet radiation, is also examined in the context of its degradation and its feedback effect on climate systems. Human-induced drivers, including the emission of greenhouse gases, land-use change, deforestation, and industrial emissions, are identified as catalysts of atmospheric instability and climate anomalies. Drawing upon authoritative scientific assessments from bodies such as the Intergovernmental Panel on Climate Change (IPCC), NASA, and the World Meteorological Organization (WMO), the paper underscores the urgent need for integrated climate governance. It concludes that a comprehensive grasp of atmospheric dynamics is indispensable for designing effective climate adaptation and mitigation strategies. The study advocates for enhanced atmospheric research and reinforced global cooperation to mitigate climate risks and foster environmental sustainability.

Development of a Statewide Climate Change Vulnerability Index for Heat and Flood: A Comprehensive Assessment of Connecticut for Resiliency Planning

The vulnerability framework developed by the Intergovernmental Panel on Climate Change (IPCC) defines vulnerability as a function of exposure, sensitivity, and adaptive capacity. Building off this framework, the Connecticut Institute for Resilience and Climate Adaptation (CIRCA) developed a Climate Change Vulnerability Index (CCVI) for the state of Connecticut, designed to integrate flood and extreme heat-related climate exposure with impacted socioeconomic, infrastructure, and ecological variables into a single comprehensive index that can guide resilience planning and prioritization at multiple levels. The index serves as a central component of the Resilient Connecticut project, a statewide initiative to advance climate adaptation and resilience planning through data-driven tools, community engagement, and strategies to address flood and heat risks across vulnerable communities. In this article, we detail the development of the CCVI, including earlier iterations, methodology, stakeholder engagement activities, and lessons learned that can impact resiliency planning in Connecticut. Preliminary statistical analyses, notable regional trends, data limitations, and future areas for research advancement are also discussed. The CCVI framework detailed here can be used in the process of identifying priority areas for intervention and supporting the selection and design of targeted resilience projects, and can also be adapted for other states.

Systematic global stocktake of over 50,000 urban climate change studies

Abstract Taking stock of climate change evidence is essential to helping cities address climate change. However, such efforts face challenges in appraising the growing scholarship in this fast-moving area. Here we use supervised and unsupervised machine learning to identify and classify over 53,000 urban climate studies, creating a dynamic, interactive and searchable evidence database for researchers and policymakers. Nearly 20,000 are city-specific case studies, revealing a rapidly growing yet unevenly distributed knowledge base. Notably, small and fast-growing cities, particularly in Africa and Asia, remain substantially underrepresented, contributing to topical, geographic and disciplinary biases in previous Intergovernmental Panel on Climate Change (IPCC) assessments. We propose three strategies to address this: (1) synthesizing case studies to support IPCC uptake, (2) identifying cross-city learning opportunities and (3) closing evidence gaps in the Global South. Thereby, our systematic stocktake helps inform adaptation and mitigation efforts in cities, guides future research and strengthens the IPCC’s ability to deliver robust, policy-relevant evidence.

Disasters in India Context: The Role of Social Work in Disaster Management

Disasters, whether natural or caused by humans, pose serious threats to human life and well-being. Events like cyclones, earthquakes, and heavy rains are often natural, but human activities can make their impacts worse. According to the United Nations Intergovernmental Panel on Climate Change (IPCC), climate change caused by humans has increased the frequency and severity of extreme weather events worldwide. In India, rapid urban growth, deforestation, uncontrolled industrialization, and poor land use have made people more vulnerable to both natural and human-made disasters. Additionally, new threats like chemical, biological, radiological, and nuclear hazards show how complicated modern disaster risks can be. This paper looks at the changing role of social work in disaster management through examples from India. It highlights important types of disasters, including the five deadliest natural and human-made disasters in the country, and examines how social workers take part in response, recovery, and building resilience. Using secondary data, the study points out the need to include social work Keywords Disasters, natural and manmade natural disasters, disaster management and Risks in Disaster Management

Assessing the combined influence of biotic and anthropogenic stressors on polar bears to inform conservation planning

Abstract Developing conservation strategies for species vulnerable to the effects of climate change, like polar bears (Ursus maritimus), can be challenging given the uncertainty of future environmental conditions. Effective conservation planning requires identifying and ranking threats to the persistence of polar bears throughout their circumpolar range and then assessing the ability of mitigative actions to aid in meeting plan objectives. We used a Bayesian network model to (1) characterize the relative importance of multiple biotic and anthropogenic stressors on four ecoregional polar bear populations, at two future decadal time periods, and based on two Intergovernmental Panel on Climate Change (IPCC) greenhouse gas emissions scenarios (Shared Socioeconomic Pathways [SSPs] 2.6 [low] and 8.5 [high]); and (2) identify achievable management actions that may enhance the prospects of long‐term persistence. Normative model runs indicated that populations in all four ecoregions incurred increasing probabilities of being decreased or greatly decreased over time. The probabilities of polar bear populations being decreased or greatly decreased from mid‐ to end of the century ranged from ~55% to 87% for the SSP 2.6 emissions scenario, and 82% to 94% for the SSP 8.5 emissions scenario among ecoregions. Arctic sea ice conditions and marine prey availability had the greatest influences on future polar bear population outcomes and overrode any relative influence from all other stressors. Hunting mortality was the most influential individual anthropogenic stressor in the Archipelago and Seasonal Ice Ecoregions, whereas terrestrial refugia quality grouped with various anthropogenic activities or factors (e.g., resource extraction, oil spill) was most influential for the Polar Basin Divergent Ice and Polar Basin Convergent Ice ecoregions. Our findings indicate that near‐term proactive management of multiple anthropogenic stressors could cumulatively reduce the decline in populations such that if future sea ice habitat loss is eventually curtailed, population abundance would be greater than it would have been otherwise. Additionally, our findings suggest that there is value in tailoring management actions to address ecoregion‐specific threats, which may prove useful in informing the development of future circumpolar conservation plans.

The impact of climate change on the precipitation regime in the Republic of Moldova

Regional climate changes caused by global warming are manifested by the impact on the amount of precipitation. The Republic of Moldova, located in a variable climate zone, is facing regional changes in precipitation. In this study, using the climate scenarios developed by the Intergovernmental Panel on Climate Change (IPCC) and based on data from 17 meteorological stations for the period 1986-2005, maps were modeled for the periods 2021-2040, 2041-2060 and 2081-2100. The results obtained show a decrease in precipitation amounts in the warm season, and an increase in them in the cold season. Thus, climate change will determine a more variable precipitation regime in time and space, increasing the risks of drought during the period of active crop vegetation

From Crisis to Policy Action: Tackling Climate Change Through SDG 13

This article investigates the critical barriers hindering progress on Sustainable Development Goal 13 (SDG 13) and identifies enabling strategies to support collaborative, transformative responses essential for achieving sustainable development by 2030. Drawing on recent research and global frameworks, it discusses major challenges/gaps relating to climate change mitigation and adaptation measures. Climate change represents one of the most pressing global challenges of the twenty-first century, with visible impacts that include intensifying extreme weather events, ecosystem disruption and threats to human health and livelihoods. The scientific consensus, notably supported by the Intergovernmental Panel on Climate Change (IPCC), affirms that human activities are the dominant drivers of global warming. These changes have led to more frequent and severe disasters, such as floods, droughts and wildfires, which disproportionately affect vulnerable populations in regions with low adaptive capacity. Beyond environmental effects, climate change also poses deep social and economic risks by exacerbating resource scarcity, undermining food systems and potentially fuelling conflict. In response, the United Nations established SDG 13, which calls for urgent action to combat climate change by integrating climate measures into national policies, enhancing adaptive capacities and improving education and awareness. While international frameworks like the Paris Agreement offer a foundational road map, translating global ambitions into local action remains a significant challenge. Thus, it calls for a shift from incremental changes to systemic transformation and a just transition.

Implications of low-carbon policies on the agricultural sector: a systematic review

Abstract The Intergovernmental Panel on Climate Change (IPCC) scientists has warned that human activities have already caused a temperature increase of at least 0.8 °C above preindustrial levels, pushing global climate conditions toward a critical threshold with potentially severe and irreversible consequences. The agricultural sector significantly contributes to greenhouse gas (GHG) emissions, primarily through the release of potent non-CO2 gases like methane and nitrous oxide, which accelerate atmospheric warming and threaten ecosystem stability, highlighting the need for immediate and effective policy interventions. This review evaluates the impact of GHG emissions from agricultural sector by employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to analyse 49 peer-reviewed articles published between 2019 and 2024. The studies were classified into six categories of low-carbon policies: carbon pricing, demand-side measures, incentives, energy policy, land policy and national policy. These policies were quantitatively assessed across four key dimensions: environmental, economic, energy, and social impacts. The analysis reveals distinct gaps in research, particularly regarding: (1) limited geographic coverage in Asia, Africa, and Oceania, (2) underexplored demand-side and incentive-based policies, (3) insufficient analysis of the social and energy-related dimensions of these policies. This review introduces a comprehensive six-category policy framework and offers an integrated assessment of low carbon agricultural policies to support effective decarbonisation in the sector.

Floods from above and below: insights beyond increases in daily precipitation extremes over flat agricultural plains

ABSTRACT While increasing flood occurrence due to climate change is typically linked to increases in extreme daily precipitation, as in the Intergovernmental Panel on Climate Change (IPCC)’s Sixth Assessment Report, stagnant hydrological plains can have flood regimes that respond to longer term water balance shifts rather than extreme events. We use observational data on precipitation, water table height, and flooded area as well as reports from local agencies to study flooding over the stagnant agricultural plains of the Argentinean Pampas, where the precipitation regime has not changed during the last several decades. Increases in daily extreme precipitation therefore cannot explain the observed increase of flooding. Furthermore, our results show that, during the period 1986–2020, monthly precipitation extremes are not significantly associated with floods and water table height. However, we show that floods and water tables have become more reactive to seasonally accumulated precipitation during the last two decades.

Assessment and Prediction of Carbon Sink Resource Potential in Arbor Forests: A Case Study of Mentougou District, Beijing, China

As the largest terrestrial carbon pool, forest ecosystems play a pivotal role in climate change mitigation through greenhouse gas regulation. This study estimated the carbon sequestration potential of arbor forests at the county-level scale in Mentougou District, Beijing, based on subcompartment vector data from forest surveys and employed the Intergovernmental Panel on Climate Change (IPCC) carbon stock–biomass difference methodology. Additionally, using 2020 as the baseline year, the research projected carbon sink potential and carbon sequestration–oxygen release values for 2030 and 2060 by applying the carbon stock change methodology and the carbon sequestration–oxygen release value methodology. The results showed that there is a total carbon stock of 2.198 million tonnes (Mt) C in Mentougou, with an average storage density of 33.4 t C/ha. Natural broadleaf forests constituted the dominant carbon pool (79.2%), followed by planted coniferous stands (11.9%), collectively accounting for 91.1% of the regional arboreal carbon storage. In the future, the district’s arboreal carbon stock is projected to reach 3.17 Mt C in 2030 and 4.82 Mt C in 2060, with cumulative sequestration reaching 0.97 Mt C and 2.63 Mt C, respectively. It is evident that the carbon storage dynamics in Mentougou were governed by three principal determinants: (1) natural broadleaf forests dominate carbon storage (1.559 Mt C) in Mentougou, exceeding planted coniferous stands by 6.7-fold; (2) carbon storage decreases progressively with younger age classes, while carbon density increases steadily with stand maturity; (3) mid-elevation slopes (600–1200 m) concentrate 48% of regional stocks, with shaded slopes being optimal carbon sinks, and slope position gradients reveal topography-driven carbon accumulation patterns, confirming scale-dependent material transport effects. The value of carbon fixation and oxygen release of existing arbor forests in Mentougou District was CNY 6.12 billion, and this is predicted to reach CNY 8.84 billion by 2030, with a further anticipated increase to CNY 13.45 billion by 2060. Our analysis provides empirical evidence and quantitative support for forestry carbon sink initiatives at the regional scale and thus promotes the achievement of dual-carbon goals proposed by the Chinese government.

Science-policy: UNFCCC policymakers’ perspective of scientific scenarios and their policy relevance

Scenarios play a pivotal role in linking climate science to policy action, informing the Intergovernmental Panel on Climate Change (IPCC) reports and international negotiations within the United Nations Framework Convention on Climate Change (UNFCCC) and its annual Conferences of the Parties (COPs)1, 2–3. However, policymakers’ (PMs) perspectives remain understudied. Here, we surveyed UNFCCC National Focal Points (N = 278/n = 57), assessing the knowledge base of international-national PMs, perceptions of scenarios’ policy relevance, and plausible improvements. Results highlight a significant regional knowledge gap, with lower scenario familiarity for PMs representing low- and middle-income countries. Furthermore, policymakers request more straightforward scenario communication and more detail. To improve scenario relevance (credibility and legitimacy)4, we recommend more actively disseminating scenario knowledge (enhancing institutional capacity) in the Global South and providing more policy-relevant detail into global scenarios and national extensions (linking scenarios to on-the-ground policy action). This also means reassessing the IPCC’s cautiousness concerning being policy-neutral.

Uncertainty Analysis of Provincial Carbon Emission Inventories: A Comparative Assessment of Emission Factors Sources

Enhancing the precision of carbon accounting not only improves climate policy design, but also contributes directly to sustainability goals by enabling more targeted and accountable emission reduction strategies. Therefore, accurate carbon inventories are foundational to evidence-based climate action and sustainable development planning. This study estimates the carbon emissions of Hunan Province from 2016 to 2020 using the sectoral approach and energy activity data across four major sectors—industrial production, thermal power generation, transportation, and residential life. Emission factors (EFs) were drawn from three different sources: direct measurements, IPCC (Intergovernmental Panel on Climate Change) default values, and published literature. An improved Monte Carlo simulation method was employed to assess the uncertainty of carbon emission accounting associated with different EF sources. The experimental results indicated that carbon emissions calculated based on the literature and default EFs were systematically higher than those derived from empirical measurements, primarily due to discrepancies in the industrial and power generation sectors. In a representative year (2017), the carbon emission estimated based on measured EFs produced the narrowest confidence intervals, reflecting lower uncertainty (−5.31–8.17%), while the uncertainties of carbon emissions calculated using the literature and default EFs were −6.88–9.03% and −5.77–9.94%, respectively. The industrial carbon emissions were the dominant source of overall uncertainty, while the transportation carbon emission had a comparatively minor impact. Importantly, across all departments, the use of measured EFs significantly reduced the uncertainty of carbon inventories, reinforcing the value of locally calibrated data. These findings underscore the urgent need for improved EF measurement systems and standardized accounting practices to support the reliability of subnational carbon inventories.

Gendered Dimensions of Climate Change Impacts: Challenges and Adaptive Strategies

Climate change poses a significant global challenge that exacerbates existing social, economic, and cultural inequalities, particularly through the lens of gender. This review systematically investigates the gendered dimensions of climate change impacts, focusing on the unique challenges faced by women and men in rural areas, as well as the adaptive strategies employed to mitigate these effects. This study employed a systematic literature review approach following established protocols. A structured search strategy was implemented across various academic databases (Web of Science, Scopus, Google Scholar, ScienceDirect) and trusted sources (United Nations Women, the Intergovernmental Panel on Climate Change (IPCC). Women, often responsible for critical tasks such as water collection, fuel gathering, and food production, experience heightened burdens due to limited access to land, financial resources, and decision-making platforms. Conversely, men are disproportionately affected by job losses in climate-sensitive sectors, leading to economic insecurity and shifts in traditional family roles. The central hypothesis guiding this review posits that addressing gender disparities in climate adaptation and mitigation is essential for achieving social justice and enhancing the effectiveness of climate action. This review underscores the critical need for inclusive and equitable strategies that foster resilience and sustainability in vulnerable communities while highlighting the intersectionality of gender and climate change. Strategies identified include capacity-building initiatives, inclusive policies, gender-responsive financing mechanisms, and participatory governance. Integrating indigenous knowledge and promoting cross-sectoral collaboration are pivotal for fostering equitable resilience. Achieving these goals necessitates collective action to dismantle structural barriers, ensuring that climate policies address the needs of all stakeholders. This study contributes to the growing recognition that sustainable communities cannot be achieved without addressing gendered impacts and fostering inclusive solutions for a more equitable future.

Mapping socio-environmentally vulnerable hotspots in the Volta Delta of Ghana.

Many Delta residents are dependent on climate-sensitive resources for their survival. Nonetheless, these resources are susceptible to climatic change and variability. The Volta delta of Ghana is severely impacted by sea-level rise resulting in flooding, salinisation and permanent loss of lands, with relentless social and economic consequences. However, vulnerability assessments in the Volta Delta have primarily focused on sea level rise, with limited attention to communities' susceptibility to adverse socio-environmental impacts. This study maps socio-environmentally vulnerable hotspots in the Volta Delta, employing methods incorporating residents, stakeholders and experts' opinions. Vulnerability is conceptualised based on the Intergovernmental Panel on Climate Change (IPCC) climate risk and socioeconomic vulnerability framework. The framework defines vulnerability as a function of sensitivity and adaptive capacity. Through stakeholder engagements, community support systems sensitive to climate-driven stressors, referred to as sensitivity dimensions, were identified. Those that enhance local communities' ability to adjust and mitigate the impacts of climate stressors, termed adaptive capacity dimensions, were also identified. Indicators for quantifying the dimensions were also identified through stakeholder engagements. Data for the analysis were extracted from multiple sources including Census, Landsat imagery, national land surveillance and Google Earth. Geospatial statistical techniques were used to analyse and map socio-environmental vulnerability hotspots. The findings show that vulnerable communities were predominantly agrarian communities clustered along the intersections of the South Tongu, North Tongu, and Akatsi districts as well as the Dangbe West and North Tongu districts. Communities along the eastern coastline of Keta and Ketu South Municipalities and the Dangbe West District were the least vulnerable. The results also show, that although communities along the coastal lines of the Keta, Ada East and Ada West districts were highly vulnerable to sea-level rise, access to vibrant cross-country economic and industrial activities at the Ghana-Togo border and the capital city of Accra and the port city of Tema contribute to their low socio-environmental vulnerability. Socioeconomic ability, particularly access to alternative economic activities has the potential to mitigate vulnerability to environmental stressors. The findings direct the need for area-specific targeted and concerted interventions for strengthening the socioeconomic ability and adaptation capacity of the Volta Delta residents.

Comprehensive Modeling of Climate Risk in the Dominican Republic Using a Multivariate Simulator

This study introduces a multivariate simulation framework for assessing climate risks in the Dominican Republic. The simulator operates in two modes—climate risk evaluation and disaster management—using a unified database. This database integrates codified variables associated with global warming, hazards, vulnerabilities (including their interdependencies), and adaptive capacities, facilitating risk assessments across diverse scenarios. Simulations are initiated using predefined variable combinations, interconnected via Boolean algebra, to generate risk levels aligned with the Intergovernmental Panel on Climate Change (IPCC) scales. The key findings underscore the influence of specific variables within the modeled scenarios. For instance, inadequate energy management and insufficient mitigation measures significantly amplify climate risks, particularly in regions with vulnerable infrastructure. Validation against established models, including EN-ROADS and PRECIS, confirms the simulator’s predictive accuracy and reliability. This study highlights the critical role of regionalized risk assessments in developing targeted adaptation and mitigation strategies that address localized vulnerabilities. The proposed simulator provides an innovative tool for real-time climate risk assessment, enabling policymakers to model potential outcomes and optimize decision-making processes. Future improvements should focus on enhancing spatial resolution, integrating real-time data, and refining models of infrastructure interdependencies. This research advances the development of evidence-based climate risk assessment tools, supporting informed policymaking and effective disaster risk management in the Dominican Republic.

Confronting the uncertainty: Vulnerability to climate change among smallholder farmers in the Sidaama region, Ethiopia.

Smallholder farmers' vulnerability to climate change varies due to socio-economic and biophysical factors, requiring a context-specific assessment. This study examines livelihood vulnerability in the face of climate change in the Sidaama Region, Ethiopia. A mixed-methods approach with a descriptive and explanatory sequential design was employed. Data from 391 systematically sampled households were analyzed using the Livelihood Vulnerability Index (LVI) and the Intergovernmental Panel on Climate Change (IPCC) framework (LVI_IPCC), alongside Kruskal-Wallis and Dunn's tests. Results of LVI analysis indicate that the Lowland agroecological zone (AEZ) is the most vulnerable (0.466), followed by the Highland (0.412), while the Midland is least vulnerable (0.376). The Highland AEZ showed greater sensitivity to climate change, whereas the Lowland had the weakest adaptive capacity. The Kruskal-Wallis H test confirmed significant differences in vulnerability across AEZs (H = 49.083, p < 0.001), with Dunn's test revealing that the Lowland AEZ is significantly more vulnerable than both the Highland and Midland. LVI_IPCC results similarly ranked the Lowland as the most vulnerable (-0.0041), followed by the Midland (-0.072), with the Highland being the least vulnerable (-0.096). Boxplot analysis further confirmed that the lowland had the highest median LVI_IPCC, indicating greater livelihood vulnerability, while the Highland and Midland had lower median values. To reduce vulnerability, targeted interventions such as climate-smart agriculture, diversified income sources, improved microfinance access, and tailored climate adaptation strategies are needed. Local, regional, and national governments should prioritize disaster prevention and mitigation in the Lowland while leveraging the Midland's higher adaptability for piloting innovative adaptation strategies.

Past socio-political transitions away from coal and gas show challenges and opportunities ahead

Abstract Transitioning away from fossil fuels presents substantial challenges, given the growing mismatch between pledges submitted to international climate negotiations and the mitigation strategies that limit warming to below 1.5 °C or 2 °C presented in the Intergovernmental Panel on Climate Change Sixth Assessment Report. The scientific case for phasing out coal-fired electricity is clear, and many countries are progressing towards this. However, despite widespread concerns about risks and trade-offs, natural gas is often considered a bridge fuel, and there is currently no progress towards phasing down its capacity. Previous work on the political feasibility of coal phase-out only considered limited socio-political factors, missing the importance of governance quality and policies supporting the energy transition. There is even more limited understanding of factors associated with gas phase-down, while Europe and North America fall behind trajectories required to limit warming below 1.5 °C. We use multivariate regression and clustering analyses on over four decades of data to investigate the drivers and synergies of coal and gas transitions. This reveals opportunities to overcome fossil fuel lock-in through renewable energy expansion, energy policy reforms, and power market restructuring. Countries with greater reliance on fossil fuel infrastructure and workforce face additional difficulties in phase out. Social factors such as higher belief in climate change are positively linked with more ambitious coal phase-out efforts. However, disentangling these links for gas remains difficult given the limited historical evidence of phase-down progress. We identify four archetypes (Coal Reliance, Gas Reliance, Limited Policy, and Transition Underway) that illustrate different ways countries have transitioned from coal and gas over time. These provide blueprints for potential future transitions in other countries. Recognizing the diverse social, political, and institutional factors that shape transitions can inform the design of politically relevant future scenarios.