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        <title>Frontiers in Climate | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/climate</link>
        <description>RSS Feed for Frontiers in Climate | New and Recent Articles</description>
        <language>en-us</language>
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        <pubDate>2026-09-12T05:26:19.588+00:00</pubDate>
        <ttl>60</ttl>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1888855</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1888855</link>
        <title><![CDATA[Cycles of displacement: an initial examination of housed residents and floating populations on postbuyout land]]></title>
        <pubdate>2026-09-11T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Sherri Brokopp Binder</author><author>Elyse Zavar</author><author>Alex Greer</author><author>Jason Martina</author><author>Mary Nelan</author><author>Ayesha Islam</author><author>Prabin Sharma</author><author>Emily Brennan</author><author>Ross Herberger</author><author>Christopher O’Connor</author>
        <description><![CDATA[IntroductionIn the U.S., local governments implement buyout programs to relocate people out of high-risk floodplains. Structures are demolished, and the acquired land is managed as open space. Increasingly, these buyout programs are being discussed as a climate adaptation technique in response to sea level rise and increased hazard exposure. However, as the availability of affordable housing has continued to decline across much of the U.S., these open spaces attract new floating populations who lack access to permanent housing. As a result, buyout open spaces in central Texas are now sites for unsanctioned temporary housing including tent encampments.MethodsDrawing from extensive field observations and semi-structured interviews with government personnel, homeowners in buyout neighborhoods, and residents experiencing homelessness, we describe the experiences of and tensions among these groups, all of which are affected by displacement associated with measures intended to reduce hazard risk.ResultsThis study is the first to examine the interconnection between buyout open space and homelessness. Specifically, we introduce the Resident Engagement Matrix, which describes the range of observed relationships between housed residents and floating populations in buyout areas, ranging from elements of neighboring with acceptance to active removal.DiscussionThis research contributes to our understanding of the dynamics and consequences of housing displacement by examining the little-understood interface between post-disaster relocations, homelessness, and flood risk.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1838033</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1838033</link>
        <title><![CDATA[Guaranteed income as an anticipatory action for climate change and disaster preparedness in the US]]></title>
        <pubdate>2026-09-11T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Sebastian Prandoni</author><author>Stacia West</author><author>Sarah Berger Gonzalez</author>
        <description><![CDATA[This Perspective Article presents the Vulnerability-Stress-Adaptation Model (VSAM) as an analytical framework for assessing Guaranteed Income (GI) as a potential Anticipatory Action (AA) instrument for climate change and disaster intervention in the United States (US). GI is understood here as a recurring, unrestricted cash transfer program, meaning recipients can use the money according to household priorities rather than for a designated category (e.g., food, housing, or utilities). GI programs in the US often target specific at-risk populations and have some form of income eligibility requirement. AA refers to actions taken before a predicted hazardous event to prevent or reduce harm to lives and livelihoods [Active Learning Network for Accountability and Performance]. We examine existing climate relief strategies in the US to understand how pre-existing, policy-shaped economic and political vulnerabilities shape household-level adaptive capabilities in response to stressful situations. As GI is positioned here as a household-level intervention, this Perspective Article focuses on adaptation and disaster relief policies that compound pre-existing household vulnerability.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1965050</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1965050</link>
        <title><![CDATA[Editorial: Receiving communities and climate destinations]]></title>
        <pubdate>2026-09-10T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Kelsea Best</author><author>Eliza Hotchkiss</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1838578</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1838578</link>
        <title><![CDATA[Meteorology, knowledge, and ethics. On modernist and animist perspectives]]></title>
        <pubdate>2026-09-10T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Dan Rosengren</author>
        <description><![CDATA[Following from local social and cultural conditions, meteorological events are perceived differently which influence how such phenomena as weather and climate are understood. Since certain understandings can be considered obvious, it can be hard to accept the validity of different understandings. In this essay I explore how Matsigenka people in the Peruvian Amazon view atmospheric events and how their comprehensions form part of their overall understandings of the world and the various forces therein and how their knowledge serves them in their engagement with the environment. Matsigenka people’s notion of the world is then compared to notions central to modernist science and, given the differences, the two modes of seeing the world are obviously incompatible. Despite the radical differences they both provide what are considered relevant explanations to occurrences in the environment by their respective advocates. The dominance of modernism in most aspects is however taken to justify the imposition of modernism’s perspective on that of others and thus alternative realities are colonialized creating an ethical problem that modernism’s complacency leads it to ignore.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1928659</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1928659</link>
        <title><![CDATA[Evaluating climate-driven agricultural suitability models for adaptation planning: stakeholder insights from British Columbia]]></title>
        <pubdate>2026-09-10T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Vali Vakhshoori</author><author>Robert Newell</author><author>Alesandros Glaros</author>
        <description><![CDATA[IntroductionThis study examines stakeholder perspectives on the strengths, limitations, and potential uses of a climate-driven agricultural land-suitability model developed to assess future crop suitability across British Columbia. The study contributes to understanding how such models can be used to support long-term agricultural planning and climate-change adaptation.MethodsThe model integrates climate, land-classification, and property-value data. Two online focus groups involving 19 participants from farming, government, academia, community organizations, consulting, and private-sector settings were conducted in October 2025. Participants explored the model outputs using the Agrilyze spatial-data platform and discussed the advantages and shortcomings of using them to inform agricultural practice, policy, and planning. Transcripts were checked and analyzed in NVivo using an iterative combination of deductive and inductive thematic coding.ResultsThe analysis produced three main findings. First, projected climatic suitability is meaningful for practice only when interpreted alongside crop requirements, water availability, infrastructure, market access, and production economics. Second, the capacity to respond to emerging opportunities or declining suitability is uneven and shaped by land values, institutional support, local knowledge, and access to appropriate technologies. Third, the model is most useful for regional exploration, communication, and long-term planning rather than site-specific prescription. Participants also identified risks of misuse, particularly where projected declines could be mobilized to justify agricultural land conversion.DiscussionThis study advances understanding of end-user perspectives on the usefulness of spatially explicit models for climate-change adaptation, planning, and policy in the agricultural sector. The findings reveal that the usefulness of such models depends not only on predictive performance but also on interpretability, governance, and the systems through which model information is translated into decisions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1837284</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1837284</link>
        <title><![CDATA[Understanding climate emotions in relation to mental health and pro-environmental behavior: a systematic review and meta-analysis]]></title>
        <pubdate>2026-09-10T00:00:00Z</pubdate>
        <category>Systematic Review</category>
        <author>Thomas Treesa Alisha</author><author>John Romate</author><author>Eslavath Rajkumar</author><author>K. S. Sruthi</author><author>Jose Mariya Lipsa</author><author>Mahesh Manjima</author>
        <description><![CDATA[IntroductionHuman behavior is fundamentally influenced by emotions, while in the anthropogenic era, climate emotions have been observed to function as a significant driver influencing mental health (MH) and pro-environmental behaviors. Yet existing reviews emphasize the segment of fear in climate emotions. This review assessed the relationship between the emotions in the climate emotion wheel (sadness, positivity, fear, anger) on mental health outcomes, as well as pro-environmental behavioral intentions (PEBI).MethodsA systematic search in Scopus, Science Direct, Web of Science, PubMed, APA PsycNet, Wiley yielded 3,313 records and after screening, 253 studies were chosen for narrative synthesis, with 56 included in the meta-analysis. The quality of the included studies is assessed using Joanna Briggs Institute (JBI) Critical appraisal checklists and Mixed Methods Appraisal Tool (MMAT).Key findingsIn our meta-analysis, climate emotions (hope, empathy, anxiety, worry, and guilt) were positively associated with PEBI. Specifically, climate anxiety (r = 0.25, 95% CI [0.15, 0.36], p < 0.001), climate worry (r = 0.48, 95% CI [0.40, 0.56], p < 0.001), and climate guilt (r = 0.21, 95% CI [0.06, 0.35], p = 0.01) predicted stronger PEBI, whereas emotions in the segment of fear resulted in poorer mental health outcomes, including climate anxiety (r = 0.39, 95% CI [0.30, 0.48], p < 0.001), highlighting the dual motivational and psychological burden of climate emotions.RecommendationsFuture research should prioritize experimental and longitudinal designs in climate emotion and should emphasize on the underexplored constructs such as gratitude, betrayal, inspiration, apathy, outrage and loneliness. The prime concern is the paucity of exploration in lower middle-income countries and how positive emotions influence PEBI and mental health outcomes.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/view/CRD420251145857.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1887595</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1887595</link>
        <title><![CDATA[Supervised and unsupervised machine learning methods for modeling current and future habitat of Peruvian anchovy]]></title>
        <pubdate>2026-09-09T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Mariana Hill</author><author>Tianfei Xue</author><author>Jaard Hauschildt</author><author>Mariano Gutiérrez</author><author>Tronje Kemena</author>
        <description><![CDATA[Understanding the drivers and potential impacts of environmental variability on the distribution of Peruvian anchovies, the largest single-species fishery on the planet, is essential for their proper management in a changing world. However, the intricate interactions of these organisms and environmental variability require the use of complex models such as machine learning methods. In this study, we compared three methods for producing habitat maps of anchovies: the traditional Generalized Additive Models, the XGBoost, which is a form of supervised machine learning, and a new method based on clustering water types as a form of unsupervised machine learning. We optimized the three methods with a parameter grid search algorithm and compared their capability to replicate the mean state of anchovies by comparing them with presence-absence observations along the Peruvian coastline between 1990 and 2010. We used the output of a physical-biogeochemical model as input for the habitat models to produce distribution maps of anchovy. All models successfully simulated the distribution of anchovies along the Peruvian coastline. Anchovies distribution was concentrated in the southern part of the region during year 1998, characterized by the impact of a canonical El Niño, while their distribution extended until the north of Peru and south of Ecuador in the other years of the study period. We then applied the models to predict potential changes in the distribution of anchovies under projected temperature and wind patterns by the end of the century. We observed a reduction in the probability of anchovy occurrence under conditions of higher temperature and weaker winds. Two of the three habitat models predicted a severe maximum decline by 75% (GAM) and 60% (XGBoost) whereby the clustering model predicted a smaller maximum decline in anchovy occurrence by less than 15%.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1830449</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1830449</link>
        <title><![CDATA[Revisiting ENSO teleconnections in the boreal winter]]></title>
        <pubdate>2026-09-09T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Carolyn Emerson</author><author>Vasubandhu Misra</author><author>C. B. Jayasankar</author>
        <description><![CDATA[The El Niño–Southern Oscillation (ENSO) is the dominant mode of interannual climate variability and a cornerstone for climate model evaluation. Yet, the sensitivity of diagnosed ENSO teleconnections to the choice of observational datasets, reanalyses, and ENSO indices has received little attention. This study systematically evaluates boreal winter ENSO teleconnections using multiple atmospheric reanalyses, surface observational datasets, and three widely used ENSO indices: the Oceanic Niño Index, Multivariate ENSO Index, and Southern Oscillation Index. Statistical significance is assessed using Benjamini–Hochberg false discovery rate procedure to account for multiple spatially dependent hypothesis testing, providing a more rigorous assessment of teleconnection robustness than conventional approaches. Although the ENSO indices are highly correlated, the associated atmospheric and surface climate teleconnections differ substantially. ENSO teleconnections in upper-tropospheric (200 hPa) geopotential height are remarkably consistent across reanalyses. In contrast, teleconnections in mid-tropospheric (500 hPa) circulation, precipitation, and surface temperature are considerably more sensitive to the choice of reanalysis or observational dataset than to the choice of ENSO index. To examine the role of temporal variability, empirical orthogonal function and ensemble empirical mode decomposition analyses were applied to ERA5 geopotential height, CHIRPSv2 precipitation, and CRU land surface temperature to isolate variability at different temporal scales. For ERA5 upper-tropospheric geopotential height, ENSO teleconnections become markedly more robust after isolating the interannual component. Likewise, removing variability outside the interannual band generally strengthens teleconnections in precipitation and surface temperature, demonstrating that variability at other temporal scales can obscure ENSO-related signals. Conversely, restricting the analysis to the common temporal coverage shared by all datasets (1980–2018 for reanalyses and 1981–2022 for observational datasets) substantially reduces the statistical significance of ENSO teleconnections for nearly all variables, indicating that the overlapping observational record is too short for robust diagnosis. These results demonstrate that ENSO teleconnections are not uniquely defined climate features but depend strongly on dataset characteristics, like temporal scales represented and record length. Overall, the choice of observational or reanalysis dataset is more consequential than the choice of ENSO index. These findings underscore the need for longer, higher-quality observational records and caution against using surface ENSO teleconnections as unambiguous benchmarks for climate model validation.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1868024</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1868024</link>
        <title><![CDATA[Rethinking climate vulnerability in livestock systems: evidence from exposure, adaptation, and within-system heterogeneity in West Africa]]></title>
        <pubdate>2026-09-09T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Soulé Akinhola Adéchian</author><author>Janvier Egah</author><author>V. F. Grâce Nadège Dedehou</author><author>Traoré Kabirou Bio Comada</author><author>Mahugnon Néhémie Kotobiodjo</author><author>Gountante Dansoip</author><author>Taïba Germaine Ainyakou</author><author>Kokou Tchalla</author><author>Adja Ferdinand Vanga</author><author>Claude Codjia</author><author>Mohamed Nasser Baco</author>
        <description><![CDATA[Climate vulnerability in livestock systems is often assumed to be intrinsically linked to production system characteristics. This study challenges this assumption by examining the relative roles of exposure, adaptive capacity, and production systems in shaping vulnerability outcomes in West Africa. Using household-level data from 1,126 livestock producers in Benin, Togo, and Côte d’Ivoire, we construct a Climate Vulnerability Index (CVI) combining exposure, sensitivity, and adaptive capacity. We employ a stepwise econometric approach based on Ordinary Least Squares (OLS) models, complemented by variance decomposition analysis, to assess the determinants of vulnerability. The results show that while semi-intensive and transhumant systems initially appear more vulnerable than sedentary systems, these differences diminish once exposure and adaptive capacity are accounted for. Exposure significantly increases vulnerability, whereas adaptive capacity exerts a strong mitigating effect. Contrary to common assumptions, no significant interaction or non-linear effects are found, suggesting that vulnerability is driven by additive and linear processes. Furthermore, the analysis reveals substantial heterogeneity within production systems, with more than 97% of the variation in vulnerability occurring within systems rather than between them. These findings provide strong evidence that climate vulnerability is not system-driven but process-driven, shaped primarily by the balance between environmental stress and adaptive capacity. The study contributes to the literature by highlighting the limits of system-based classifications and emphasizing the importance of household-level conditions. From a policy perspective, the results suggest that reducing vulnerability requires strengthening adaptive capacity and addressing exposure, rather than promoting specific livestock production systems. This calls for more context-sensitive and targeted adaptation strategies in West African livestock systems.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1889436</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1889436</link>
        <title><![CDATA[Interrogating the conceptualisation and use of ‘agency’ in environmental relocation]]></title>
        <pubdate>2026-09-09T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Chloe ten Brink</author><author>Ronan McDermott</author><author>Mick Lennon</author>
        <description><![CDATA[Environmental relocation, the organised movement of individuals or communities from at-risk areas to perceived safer locations, raises complex questions about people’s agency in shaping their futures amidst a rapidly changing climate risk landscape. In climate mobility research, policy, and advocacy, the notion of ‘agency’ is invoked alongside other value-laden terms such as empowerment and resilience. Yet, the term is often used inconsistently or without clear definition, creating an ambiguity that limits the capacity of both research and policy to operationalise agency substantively rather than simply rhetorically. This paper addresses this gap by undertaking a scoping review of the literature on environmental relocation, a field that repeatedly grapples with the tension between voluntary and forced movement. A total of 163 articles were reviewed. This paper examines the dominant framings of agency, alongside an exploration of its scalar and temporal dimension, and its orientation, the sphere or direction in which agency is being exercised. Identified literature gaps include the need to explore temporal dimensions of agency within environmental relocation, adopt intersectional approaches, to explore intra-household dynamics, and further theorise the role of coercion and possible operationalisation of enabling or enhancing agency to name a few.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1934023</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1934023</link>
        <title><![CDATA[Regulatory quality and the EU circularity gap: forecasting the circular material use rate to 2035]]></title>
        <pubdate>2026-09-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Aftab Haider</author><author>Cecile Abi Tayeh</author><author>András Szeberényi</author>
        <description><![CDATA[Circular water and waste infrastructure is central to climate mitigation and resource security, and evidence-based tools increasingly shape how such systems are planned and regulated. This study asks whether regulatory quality is associated with circular performance across the European Union and what current trends imply for circularity targets. Using Eurostat, World Bank and OECD data, we forecast the EU circular material use rate to 2035 with linear trend, exponential smoothing and ARIMA models, and test that relationship across all 27 member states. The rate rose from 10.7% in 2010 to 12.2% in 2024, or 0.11 percentage points a year. Forecasts place it near 12.4% in 2030 and 12.8% in 2035, about 10–11 points below the doubling target, with the published target band (22.4–24%) lying outside the 95% prediction interval of every model at the 2030 horizon. Across member states, the simple correlation between regulatory quality and the headline rate is positive but weak. Because that rate is a ratio whose denominator contains domestic material consumption, we also test circular material use per capita, which does not condition on the denominator: regulatory quality is positively but modestly associated with it. In the primary specification, a log-linear regression of that measure on regulatory quality yields a slope of +0.49 log points per unit (heteroskedasticity-consistent 95% confidence interval −0.06 to 1.05; robust p = 0.079, classical p = 0.048; r = 0.38), rising to +0.66 (robust p = 0.005) once material throughput is held constant. Finland and Ireland remain below their predicted values and are not explained by material throughput alone. The findings are compatible with an institutional reading of the circularity gap, but the design cannot identify a mechanism or distinguish it from analytical or technological explanations. We therefore outline legal and procedural reforms, including circular procurement law, water reuse regulation, extended producer responsibility and accountable algorithmic evidence, as a prospective agenda for testing that reading.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1835304</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1835304</link>
        <title><![CDATA[MRV financing under EU carbon farming governance: a review]]></title>
        <pubdate>2026-09-04T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Jana Poláková</author><author>Martin Hvarregaard Thorsøe</author><author>Adam Svoboda</author><author>Silvia Coderoni</author><author>Laure Bamière</author><author>Kamel Louhichi</author><author>Katarina Elofsson</author><author>Paolo Sckokai</author><author>Berit Hasler</author><author>Greet Ruysschaert</author>
        <description><![CDATA[This study reviews and compares the financial mechanisms required to support verifiable agricultural soil carbon stocks under the European Green Deal. It examines monitoring, reporting, and verification (MRV) systems for soil carbon removals and emission reduction through carbon farming (CF) projects, exploring how financial mechanisms can be designed to support rigorous measurement while ensuring economic viability for land managers. The review identifies a central accuracy–cost paradox: while result-based MRV systems require high-precision monitoring for credibility, they increase implementation costs that create barriers to farmer participation. Upfront financial burdens and deferred rewards make result-based mechanisms alone insufficient to drive adoption. A policy mix involving public, private, and civic resources is essential for mitigating CF project implementation costs and managing risks related to regulatory additionality. For example, the findings indicate that result-based CF projects will likely need complementary support, including publicly funded CF advisory services that reduce participation barriers by addressing farmers’ information gaps associated with MRV. Collective monitoring arrangements distribute fixed MRV costs and improve economic viability for small-scale farmers, though institutional conditions for equitable aggregation require clarification. Blended financing combining public budgets, private markets, advisory support, and cost pooling addresses the accuracy–cost paradox more effectively than single-instrument policies. The findings demonstrate that effective soil carbon sequestration requires realigned governance structures that explicitly integrate MRV financing into CF project design. This enables the agricultural sector to scale up carbon removal and advance SDG13 (Climate Action) and European climate neutrality targets.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1827024</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1827024</link>
        <title><![CDATA[Unsupervised NLP for quantifying sentiment deviation and framing in global climate discourse]]></title>
        <pubdate>2026-09-03T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Aditya Vasudev K</author><author>Srisakthi Saravanan</author><author>Ananya Vinay</author>
        <description><![CDATA[Climate change news coverage varies by region and media organization. These differences show in the way news is framed, the themes chosen, and communication priorities. This study suggests a scalable and unsupervised natural language processing (NLP) framework to measure sentiment changes and framing patterns in global climate discussions across major news outlets. The proposed system uses Zero-Shot BART-large-MNLI as the main sentiment classification model, while VADER serves as a comparative baseline during model validation. Key themes are identified using BERTopic. We detect changes in climate narratives over time with the Pruned Exact Linear Time (PELT) changepoint detection algorithm. We introduce a dual-baseline framework to calculate relative sentiment changes. This combines regional consensus with a scientific baseline. It allows comparison of framing patterns without hiding systematic regional differences. The BART-MNLI model was tested against a manually annotated sample of articles. It achieved an accuracy of 98.0%, an F1-score of 0.98, and Cohen’s κ of 0.96, showing strong agreement with human annotations. It significantly outperformed lexicon-based sentiment analysis for professional news text. We also assessed statistical robustness with the Kruskal-Wallis H-test, bootstrap confidence intervals, and PELT sensitivity analysis. The framework reveals regional sentiment differences, outlet-level framing patterns, thematic trends, and notable shifts in response to major climate events. It offers a clear, reproducible, and flexible method for analyzing global climate communication.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1871208</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1871208</link>
        <title><![CDATA[Promoting synergies and mitigating trade-offs: governance conditions in climate action and SDG interactions]]></title>
        <pubdate>2026-09-03T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Yoko Takimoto</author><author>Norichika Kanie</author><author>Yatong Yang</author>
        <description><![CDATA[The Sustainable Development Goals (SDGs) represent an indivisible agenda in which interactions among goals—synergies and trade-offs—must be managed. While substantial progress has been made in quantitative modeling and network analysis of SDG interactions, systematic evidence drawn from empirical policy cases remains limited, leaving a persistent knowledge gap between theoretical analysis and on-the-ground practice. This study screened 128 empirical case study papers cited in Chapter 3.4 of the IPCC Sixth Assessment Report (AR6) Synthesis Report (SYR), which addresses long-term interactions among adaptation, mitigation, and sustainable development. Papers were classified into five domains—energy and power; land use, forests, and agriculture; urban, transport, waste, and local governance; industry, supply chains, and circular economy; and governance—and systematically analyzed for synergies, trade-offs, enabling factors, and remaining challenges. Findings indicate that synergies consistently arise not from single measures but from cross-sectoral policy integration, long-term institutional frameworks, multi-criteria assessment, inclusive stakeholder engagement, and aligned incentive structures. Trade-offs, by contrast, were consistently associated with institutional fragmentation, asymmetric power and resource distribution, short-termism, and incoherent policy mixes rather than appearing as inevitable outcomes. Five key driving forces for synergy promotion and trade-off mitigation were identified: policy objective integration, inclusive governance and redistribution of agency, long-term vision and time horizon reorientation, incentive structure redesign, and institutional capacity for learning and adaptation. This study advances the literature by moving beyond descriptive mapping of SDG interactions to a mechanism-oriented analysis that explains how policy design and governance arrangements shape or mitigate these interactions in practice. These findings suggest that the most impactful leverage points reside in deep systemic properties—governance structures, decision-making rules, and dominant development paradigms—rather than in isolated technical or policy interventions, and that strategic combinations of shallow and deep interventions are required to enhance both effectiveness and political feasibility in SDG implementation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1893768</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1893768</link>
        <title><![CDATA[Multiscale analysis of satellite-derived climatic parameters over Himalayan foothills in view of climate change scenarios]]></title>
        <pubdate>2026-09-03T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Sameer Rawat</author><author>Sanjeev Kimothi</author><author>Asha Thapliyal</author><author>Pradeep Kumar</author><author>Salem Ali</author>
        <description><![CDATA[The high mountain areas have seen a significant increase in air temperature and altered precipitation patterns over the last few decades. There is an urgent need for comprehensive analysis of climatic parameters at the regional level to address the parameter linkages. In this research work, the Multi-Scale Event Synchronization (MSES), the Hurst exponent (H), the fractal dimension (FD), entropy analysis, Monte Carlo simulation, and ordinary least squares (OLS) regression were used to examine long-term climatic parameters. The different reanalyzed data platform (GEE) provides precipitation (PPT), land surface temperature (LST), and normalized difference of vegetation index (NDVI) variability during the period 2001–2022 over the foothills of the Himalayan region (Doon Valley), which has been analyzed. The MSES were able to effectively capture multi-scale climatic patterns, whereas FD reveals persistent behavior in the NDVI-PPT, LST-NDVI, LST-PPT, and PPT-NDVI and anti-persistence in NDVI–LST and PPT–LST. The statistical significance of each variable was confirmed by Monte Carlo simulations, with values of 0.856 for NDVI, 0.653 for PPT, and 0.585 for LST. A spatial and temporal positive trend in LST and PPT reveals that there is an interlinkage in the climatic variables, which have significant seasonal differences and exhibit a significant climatic gradient during summer. Entropy and MSES analyses provide an understanding of the interactions between climatic variables at various time scales. The findings highlighted the need for long-term local climate monitoring in mountain ecosystems to assess local climate change impacts and to understand the linkages among the various climatic parameters that are vital for environmental management and ecosystem sustainability in the view of climate change scenarios.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1807731</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1807731</link>
        <title><![CDATA[Assessing the environmental impact of Chinese outward FDI, tourism growth, and technological advancements in BRI countries]]></title>
        <pubdate>2026-09-03T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Waqar Ahmad</author><author>Saif Ullah</author><author>Valentin Marian Antohi</author><author>Pardaev Jamshid</author><author>Costinela Fortea</author><author>Monica Laura Zlati</author><author>Teodora Odett Breaz</author><author>Feruzbek Jumaniyozov</author>
        <description><![CDATA[Belt and Road Initiative (BRI) economies are rapidly expanding infrastructure, tourism, and investment connectivity, yet these developments may also increase energy demand and carbon emissions. This study assesses the environmental impact of Chinese outward foreign direct investment (FDI), tourism growth, and technological advancement on carbon emissions in 60 BRI countries during 2000–2024. The study contributes by examining Chinese outward FDI rather than aggregate FDI, incorporating the interaction between Chinese outward FDI and tourism development, and comparing environmental effects across major BRI regions. Using the Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) approach, supported by Common Correlated Effects Mean Group robustness estimates and Dumitrescu–Hurlin causality analysis, the results show that Chinese outward FDI and technological innovation reduce carbon emissions in the full BRI sample over the long run. In contrast, tourism development, industrial value added, and the interaction between Chinese outward FDI and tourism development increase carbon emissions, indicating that tourism-intensive and infrastructure-led development can intensify environmental pressure. The regional results reveal that Chinese outward FDI increases emissions in South Asia and the MENA, whereas it reduces emissions in Southeast Asia, Central Asia, Central and Eastern Europe, Western Europe, and the Commonwealth of Independent States countries. The findings also support the Environmental Kuznets Curve hypothesis in the full sample and regional subsamples. The results highlight the need to direct Chinese investment toward renewable energy, clean transport, and energy-efficient infrastructure; embed low-carbon standards in tourism mobility and accommodation; accelerate technological upgrading; and adopt region-specific industrial and environmental policies. This study advances understanding of how Chinese outward FDI, tourism growth, and technological advancement jointly shape environmental sustainability across BRI economies.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1873994</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1873994</link>
        <title><![CDATA[Assessing ethical aspects of heat adaptation in informal settlements in LMIC urban areas using a disaster justice informed theory: a rapid review]]></title>
        <pubdate>2026-09-03T00:00:00Z</pubdate>
        <category>Systematic Review</category>
        <author>Lira Ramadani</author><author>Juliana Lenz</author><author>Katharina Förster</author><author>Melanie Boeckmann</author><author>Fatema Kashfi</author><author>Tamima Ahmed</author><author>Rumana Huque</author><author>Deepa Barua</author>
        <description><![CDATA[IntroductionClimate change poses critical risks to urban areas due to their dense populations and infrastructures that are sensitive to climatic conditions. As cities grow rapidly, their exposure to climate and disaster risks increases, highlighting their critical role in climate change adaptation. Urban heat disproportionately impacts informal settlements in low- and middle-income countries (LMICs). These communities often lack essential infrastructure, adequate housing, and green spaces, further increasing their vulnerability during extreme heat events. Despite their heightened risk, the voices and needs of at-risk populations are frequently excluded from urban heat adaptation strategies. This rapid review investigates the current state of knowledge about ethical considerations regarding the participation of at-risk groups in urban heat adaptation in LMIC, with a particular focus on informal settlements.MethodsA rapid review was conducted to synthesize evidence from peer-reviewed studies on urban heat adaptation in LMICs. Cochrane rapid review guidelines were followed, with searches performed in Web of Science, PubMed, and SCOPUS. Out of 227 studies screened, 30 were included in this review. The included studies address heat adaptation in LMICs and are published in English between January 1, 2000, and the search date. Non-peer-reviewed and non-English articles are excluded. Thematic analysis guided by a disaster justice theory framework was applied to identify key findings related to ethical considerations and the inclusion of vulnerable groups in adaptation planning.ResultsThe dimensions Accountability, Representation, Knowledge, Platform, and Agents of Change of the disaster justice framework were scarcely addressed in the included studies. Only Conviction was mentioned in most cases. Our findings indicate that the equitable distribution of heat adaptation resources is insufficient and accountability mechanisms are nearly absent. Moreover, marginalized groups and their knowledge are rarely recognized in official decision-making processes. There is a lack of spaces in which various stakeholders and dwellers of informal settlements can engage in dialog and participate in joint decision-making. However, the included studies advocate with ethical conviction for prioritizing the needs of vulnerable groups.DiscussionStudies consistently report weak or absent accountability mechanisms and limited representation of marginalized groups, particularly women, in adaptation governance. Although residents rely on culturally rooted and contextually informed heat-adaptation practices, such local knowledge is rarely acknowledged or integrated into formal planning. Participatory platforms remain scarce, with only isolated examples of collaborative decision-making. Identified agents of change—including researchers, women, brokers, and local experts—advocate for marginalized communities, but these efforts lack structural support. Most studies nevertheless demonstrate a strong ethical conviction, recognizing heightened vulnerabilities and calling for more just adaptation processes. Given the persistent undervaluation of local knowledge and the limited inclusion of vulnerable groups in decision-making, we advocate for the formal incorporation of justice-oriented frameworks into urban heat adaptation planning to promote equitable, community-centered responses. These findings are meant to contribute to the creation of equitable adaptation strategies, that not only mitigate the impacts of extreme heat but also strengthen the resilience of at-risk populations.Systematic review registrationhttps://doi.org/10.17605/OSF.IO/SHKE2]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1814314</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1814314</link>
        <title><![CDATA[The carbon footprint of the tea agrifood system in the context of SDG 13 (climate action): a systematic literature review]]></title>
        <pubdate>2026-09-01T00:00:00Z</pubdate>
        <category>Systematic Review</category>
        <author>Ally Mkumbukiy</author><author>Erick Mayani</author><author>Magreth Katole</author><author>Elias Chundu</author>
        <description><![CDATA[BackgroundThis study contributes to the growing interest and the need to enhance overtime transformational changes in the agrifood systems through understanding the environmental impacts of the tea agrifood system operations and identifying greenhouse gas emissions channels for improving and designing sustainable solutions to achieve SDG 13 (Climate action).ObjectivesIt explores the main sources of greenhouse gas emissions (GHG) and methods used to measure carbon footprint and global warming potential. The study identifies different adaptation and mitigation strategies that reduce emissions from the tea agrifood system.MethodsFocusing on carbon footprint as the main factor in environmental sustainability and agrifood system resilience, 60 articles were systematically analyzed using MAXQDA software.ResultsThe study found that the life cycle assessment of tea agrifood systems was highly conducted using SimaPro, different unspecified tools, and spreadsheets under ISO14040:2006, ISO14044, and PAS 2050:2011 impact evaluation standards. Moreover, electricity and energy were revealed as the leading sources of carbon emissions (CO2), followed by the overuse of chemical fertilizers, which emit other greenhouse gasses (CH4 and N2O) at the cultivation stage, and the use of coal and firewood in the processing and packaging stages. Likewise, the highest environmental footprint was due to consumption activities (47%), processing (27%), cultivation (17%), and packaging (9%).ConclusionThe study highlighted that various adaptation and mitigation strategies, including improving energy use efficiency, use of organic fertilizers, and waste composting from tea processing, can reduce carbon footprints, improve environmental sustainability, and enhance resilient, greener agrifood systems.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1880364</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1880364</link>
        <title><![CDATA[A robust multi-criteria and rank-stability framework for station-scale evaluation and ranking of CMIP6 GCM precipitation over the Jhelum River Basin]]></title>
        <pubdate>2026-09-01T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Muzamil Hassan Lone</author><author>Amit B. Mahindrakar</author><author>Kumar K.</author>
        <description><![CDATA[Accurate simulation of precipitation remains a major challenge in mountainous regions, where complex topography, mixed precipitation types, and strong seasonal contrasts constrain climate model performance. This study evaluates bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) General Circulation Models (GCMs) at station scale across the Jhelum River Basin (JRB) (1985–2014). Thirteen GCMs were assessed annually and seasonally at six stations using correlation coefficient (CC), root mean square error (RMSE), normalized RMSE (NRMSE), absolute normalized mean bias error (ANMBE), Nash–Sutcliffe efficiency (NSE), Kling-Gupta efficiency (KGE), and probability skill score (PSS). To ensure objective, reproducible model selection, we developed an integrated framework combining three independent ranking methods Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), PROMETHEE-II, and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) with explicit rank-stability quantification across methods, stations, and seasons, and a sensitivity analysis against alternative weighting and Monte-Carlo weight uncertainty. This combination of multi-method ranking with formal stability quantification is a central methodological contribution of this study. Results show bias correction substantially reduces, but does not eliminate, systematic error: annual RMSE ranges from 9.1–14.3 mm and ANMBE from 1.5–35.2%, while correlation and efficiency metrics remain weak throughout (CC: −0.02 to 0.04; NSE: −1.13 to −0.42), consistent with the expected behavior of free-running GCMs at daily resolution rather than a basin-specific deficiency. Elevation modulates performance non-uniformly: NRMSE and NSE improve with elevation while ANMBE and KGE worsen, and the highest-elevation station records both the best NRMSE/NSE and the largest annual bias in the basin. Autumn is consistently the weakest season, reflecting monsoon-withdrawal transition dynamics, localized convection, and orographic effects that coarse-resolution GCMs and a sparse station network cannot fully resolve. The integrated consensus ranking identifies MPI-ESM1-2-LR as the most robust model and MRI-ESM2-0 as the least robust, both stable across 21 of 22 alternative configurations tested; the remaining 11 models' ranking is not robust to reasonable weighting variation and should not be treated as a strict ordering. Overall, the study establishes a reproducible, rank-stability-aware framework for station-scale climate model evaluation, providing actionable guidance for precipitation-driven hydrological modeling and climate-risk assessment in Himalayan terrain.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fclim.2026.1926592</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fclim.2026.1926592</link>
        <title><![CDATA[Climate change and food security in sustainable finance: a South African perspective]]></title>
        <pubdate>2026-08-28T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Mashford Zenda</author>
        <description><![CDATA[In South Africa, climate change is increasingly threatening food security through droughts, irregular rainfall, high temperatures, floods, water shortage and reduced agricultural productivity. This study conducted a systematic review of South African studies on the integration of climate change, food security and sustainable finance. The review was implemented using Climate-Resilient Food Systems Framework and PRISMA 2020 guidelines. The review process involved identifying 173 documents from Scopus, Web of Science, Science Direct and Google Scholar, among which 37 articles were selected for the final synthesis. Results indicate that the available data comprehensively report climate change effects on agriculture, livelihoods and household food security with a focus on smallholder farmers. Nevertheless, the integration of sustainable finance into the food security and adaptation research is still very limited. Public investment, agricultural credit, green finance, climate finance, extension-linked support, and digital finance were identified as key yet disconnected mechanisms for enhancing resilience. The main obstacles are financial exclusion, poor institutional capacity, lack of coordination, insufficient climate information, poor infrastructure, and socio-economic vulnerability. This systematic review contributes to the literature by developing an integrated evidence-based conceptual framework for climate change, sustainable finance, adaptation, and food security. The study recommends that policymakers, financial institutions, and development practitioners adopt the proposed integrated conceptual framework to guide the design of climate-resilient food-system policies, sustainable finance strategies, and adaptation interventions.]]></description>
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