Heat stress (HS) conditions are some of the most impactful health-related climate hazards, affecting human well-being and comfort, stressing public health and civil protection services, especially in developing countries. This work presents a comprehensive assessment of summer HS conditions across southern South America (SSA), based on five widely used indices derived from temperature and humidity variables, namely wet bulb temperature (wbt), simplified wet bulb globe temperature, heat index (hi), humidex and discomfort index (discomInd). Station data (STN) and five gridded datasets were considered, addressing the challenge of observational uncertainty in SSA. HS indices exhibit different sensitivities to input climate variables. The wbt is more responsive to changes in humidity than the other indices (swbt, hi, humidex, and discomInd), which distinguishes it in terms of spatial patterns, identification of high HS days and trends. Over the recent period (1981–2022), upward trends were observed in most indices, consistent with rising temperatures. A stronger signal of change was identified for hi, whereas a weaker, less robust signal was observed for wbt. The frequency of high HS days also increases across SSA with higher agreement among datasets and indices. Comparison between STN and datasets reveals larger biases in humidity variables, which were considerably reduced when computing the indices. Among the datasets, the finer-resolution ones performed best, highlighting MSWX and ERA5-Land over ERA5, depending on the analyzed aspect. Overall, this study lays the groundwork for robust HS climate assessments across the region, supporting the development of more tailored adaptation strategies in SSA.
Floods are a recurrent phenomenon in the Indian state of Assam, with nearly 39% land classified as flood-prone. This increases the vulnerability of the agriculture sector that supports around 70% of the state’s population either directly or indirectly. While extensive research exists on the effects of floods and climate change on the agriculture sector, only a few explain their direct long-run consequences and the micro-level adaptive responses. We fill this gap by analysing the impact of floods and climate variability on the primary sector by considering Assam’s agricultural gross value added (GVA), that embodies the sector’s real economic performance in comparison to the aggregate gross domestic product, for the period 1980–2023. We found statistically significant bidirectional relationship between floods and GVA, along with interactions between floods and local climatic conditions. The findings demonstrate that environmental shocks directly affect agricultural performance. We also observe that adaptive capacity and resilience of the agriculture system are impacted indirectly. Therefore, there is a need to understand how adaptation policies need to be designed so that the resilience of the sector improves. Qualitative analysis of survey data collected from a sample of 436 farm households across 16 villages in the Brahmaputra valley, capturing local perceptions, and coping strategies help us in this direction. The study underscore mediating role of adaptive capacity, a key contribution of the study. Results emphasizes the need for a pro-active disaster risk reduction programme. Overall, the study informs policymakers that they should develop targeted strategies to further lower the adverse effects of floods and climate variability on the agricultural sector.
Global terrestrial ecosystems exhibit substantial interannual variability (IAV) in net carbon (C) flux. Determining the biogeographic origin of this variability is essential for the understanding and forecasting of global C cycling and carbon-climate feedbacks. Currently, most studies identify either global drylands or moist tropical forests as the dominant source of IAV. Considering this, we investigated whether the use of three different global ecosystem classifications of drylands and moist tropical forests, as well as two alternative geographical scales, could alter which ecosystem is the dominant contributor to terrestrial net C flux IAV. Using the simulation results of 18 dynamic global vegetation models from the TRENDY v11 model intercomparison, we calculated the absolute and area-weighted contributions of net C flux IAV for: individual 0.5° grid cells, global ecosystem classifications, and ecoregions (intermediate scale between grid cells and global ecosystems). For all three of the global ecosystem classification schemes, we found the drylands IAV contributions of 41%, 32%, and 37% were significantly greater than the associated IAV contributions of 20%, 19%, and 24% from the moist tropical forests ( p < 0.001). However, the moist tropical forests had a higher IAV contribution per unit area across all three classification schemes (∼3% versus ∼1%–2% ( p < 0.001)). At the ecoregion scale, this switch between drylands and moist tropical forests was absent; as seven of the ten highest absolute and nine of the ten highest area-weighted contributing ecoregions were drylands. Specifically, we found tropical and subtropical grasslands, savannas, and shrublands to be particularly substantial contributors to global terrestrial net C flux IAV, with the Cerrado’s absolute IAV contribution of 3.52% exceeding all but one of the other 763 global ecoregions IAV contributions (all p < 0.05). Our findings demonstrate that drylands persist as the dominant contributor to global terrestrial net C flux IAV, irrespective of different global ecosystem classifications or geographic scales.
Projections of future changes in tropical cyclone (TC) rainfall are critical for understanding evolving flood risks and infrastructure impacts under climate change. This study couples a physics-based TC Rainfall model (TCR) with the Columbia HAZard model, a statistical–dynamical TC downscaling framework, which generates synthetic storm tracks and intensity, to produce large synthetic ensembles of TC generated rainfall downscaled from 12 CMIP6 models. TC rainfall is simulated in the North Atlantic basin based on the CMIP6 historical and future simulations under three Shared Socioeconomic Pathways (SSP2-4.5, SSP3-7.0, SSP5-8.5). Projections from this integrated framework are evaluated against the Geophysical Fluid Dynamics Laboratory Rainfall Climatology and Persistence model (R-CLIPER), a statistical TC rainfall model that provides an alternative to the dynamical simulations. TCR projects widespread increases in TC rainfall, with the strongest changes along the US East and Gulf coasts and for major hurricanes (Categories 3–5). By late century, average rainfall increases reach 40%–100% in TCR compared to 30%–60% in R-CLIPER, with the largest increases in the Northeast regions. Extreme 24 h rainfall increases by up to 55% in TCR, roughly twice the magnitude simulated by R-CLIPER. Key drivers include higher TC intensities, increased atmospheric moisture, and projected slower translation speeds, which together contribute to increasing flood risks, especially when combined with more frequent sequential TC events.
Cirrus clouds have a net warming effect on Earth’s climate. It has been positioned that deliberately thinning these clouds by seeding them with ice nucleating particles could, to some extent, counter anthropogenic global warming by allowing more longwave radiation to escape to space. This climate intervention technique is known as cirrus cloud thinning (CCT). In this work, CCT has been simulated in four Earth System Models (ESMs)—UKESM, IPSL, GISS and NorESM—by increasing the sedimentation velocity of cloud ice crystals by a fixed amount under a background of SSP5-8.5 (a high emissions scenario). This experiment, proposed as part of the Geoengineering Model Intercomparison Project, was intended to explore the climatic response to CCT with a simplified methodology in order to obtain more consistent results across different ESMs. Across all four ESMs, we find a global mean cooling relative to the background scenario of –0.42 K to –0.93 K by the middle of the century and increases in precipitation. Although all ESMs do exhibit the expected cooling as a result of a reduction in cloud cover in the upper troposphere, they diverge in the responses of lower cloud coverage, humidity, and hydrological cycle. This divergence shows that there are different processes that lead to forcing at play in the models, highlighting the need for better representation of cirrus clouds and their radiative impacts.
Weather and climate extremes are transforming ecosystems in ways that threaten society through the disruption of nature’s contributions to people (NCP) from food and water security to disaster mitigation and mental well-being. While scientists and policy makers increasingly recognize the need to account for nature-related losses from climate-driven weather extremes, major research gaps remain, particularly in how climate-altered disturbance regimes will impact NCP and associated human well-being. Addressing this gap is critical for climate mitigation and adaptation planning, because the loss of NCP amplifies social-ecological vulnerability and exacerbates climate risks. However, this cross-systems dynamic remains underrepresented in most climate risk models. Climate risk modeling offers a probabilistic view of evolving hazard regimes under climate change, while ecological research provides mechanistic insight into ecosystem responses to disturbance. We argue that bridging these fields is essential to increasing societal resilience to climate change and propose an interdisciplinary research agenda to integrate social-ecological dynamics with a climate risk perspective. Advancing this agenda is critical to project, anticipate, and plan for ecosystem-related impacts of weather and climate extremes on society.
This article analyzes an interdisciplinary process carried out between 2022 and 2025 within the Argentina Hub of the My Climate Risk World Climate Research Programme lighthouse activity, aimed at developing a bottom-up understanding of climate risk. Bringing together researchers from the physical and anthropological sciences, the dialogue exposed contrasting ways of defining and mobilizing the notion of risk. This led to a sustained exploration of how climate information intersects with the historically grounded social-territorial configurations in which climate risk takes shape. Through a range of activities, the Hub examined how the notion of risk is constructed when approached from different disciplinary perspectives, informing a more situated and multidimensional framing of climate risk. The article reconstructs this trajectory and the insights that emerged, highlighting how interdisciplinary engagement can expand the possibilities for generating climate risk knowledge attuned to local and regional contexts.
Extreme heat events (EHEs) are becoming more frequent and severe across the United States, yet the drivers of heat-related mortality remain unevenly understood. This study examines how heat vulnerability and regional heat conditions shape all-cause mortality anomalies across the nine U.S. climate regions. Using a national dataset of EHEs and population-normalized mortality z -scores from 2014–2023, we compared the relative influence of socioeconomic, demographic, environmental, and heat-event characteristics on mortality outcomes. Across regions, socioeconomic and demographic vulnerabilities—particularly poverty, racial/ethnic composition, social isolation, limited green space, and older age—were the strongest predictors of elevated mortality during extreme heat. In contrast, event characteristics such as duration, temperature exceedance, and areal extent contributed comparatively little once socioeconomic and demographic vulnerability was accounted for. Mortality modeling performance varied widely by region, with particularly strong predictive signals in the Southwest, West, and South. These findings suggest that socioeconomic and demographic vulnerabilities, rather than meteorological extremes alone, may be more consistent drivers of heat-related mortality variation across U.S. climate regions. Targeted, region-specific heat-health strategies—especially those addressing social vulnerability and humidity exposure—are essential for reducing mortality risk under a warming climate.
Flash droughts are characterized by rapid onset and intensification, producing an escalating impact on agriculture and socio-environmental systems. This study analyzes the trends and drivers of Evaporative Demand Drought Index (EDDI), which is a metric for characterizing flash droughts, over the contiguous United States (CONUS) during 1980–2022. EDDI exhibits an increasing trend across a large portion of the CONUS except parts of the Intermountain West. The rising trend in EDDI suggests an increased atmospheric thirst that potentially drives flash droughts. To understand the historical changes in EDDI, we use K -means clustering to unravel the distinct spatial characters of EDDI. This method generates three distinct pairs of clusters, i.e. meridional dipole, zonal dipole and the Central US pattern. The vast majority of the increasing trend in EDDI over the CONUS can be explained by the Central US pattern, with the other patterns playing only secondary roles. Our results also reveal that changes in sea-surface temperatures and large-scale circulation associated with climate modes could contribute to changes in EDDI over the CONUS. Our findings provide implications for informing the adaptation and mitigation of flash droughts.
Enhancing climate literacy is critical to building climate resilience, with participatory approaches gaining traction among both researchers and practitioners working on bridging the gap between science, planning and action. This paper seeks to contribute to the discourse and practice of enhancing climate literacy in the Philippines by highlighting the participatory and innovative methods implemented and reflecting on the processes and outcomes of the workshop, titled ‘Training on Understanding the Latest Climate Science and Local Projections for Adaptation Planning.’ Organized by a team from the Manila Observatory under the USAID-funded Climate Resilient Cities Project, the workshop was carried out between 2023 and 2024 across six climate vulnerable Philippine cities. The climate literacy workshop aimed to enhance the capacity of local government and community stakeholders to articulate their climate narratives and create a clear and inclusive vision of their potential climate futures. To achieve this, the workshop incorporated innovative methods and tools to enhance local climate literacy: localized climate change-modified hazard maps to aid science communication, climate storylines to navigate uncertainty, the solutions framework from the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6) for a more comprehensive understanding of climate-resilient development, a modified business model canvas for simplifying resilience planning, automated weather station dashboard designs to target different age groups, and participant grouping by generation inspired by the IPCC AR6 Synthesis Report. This paper presents how these tools and approaches were applied through workshop activities, as well as some of the outputs created by local participants. Participant feedback revealed their appreciation of the personalized approaches, especially the climate story exercise, which reflected intergenerational views on climate change, as well as the hands-on activities, including pitching for the business model canvas and designing their own weather dashboards. The workshop was highly effective in deepening participants’ understanding of climate science and its changes while offering informative, interactive learning experiences that made the complex subject matter more accessible. The delivery of these workshops to the six cities demonstrated its replicability and potential for scaling up, while making sure to use climate information specific to the city and adjusting activities to respond to the needs of the city.
Cities are increasingly positioned as key climate actors through transnational networks and greenhouse gas emissions reduction pledges. Upstream emissions from the consumption of goods and services account for a major portion of total urban carbon footprints. However, most city climate action plans (CAPs) only account for territorial and energy consumption-related upstream emissions, rather than addressing full consumption-based emissions. This gap is often linked to the legal limitation of municipal authority to territorial boundaries. Here, we show that cities have substantial untapped policy potential to address consumption-based emissions. The greatest missed opportunities are found in cities with extensive legal powers rather than limited authority. By analyzing eight international cities, we found that household carbon footprints ranged from 2 to 12.1 tCO _2 eq per capita and year. Current CAPs addressed sectors representing 60% of indirect emissions with at least one mitigation measure, while sectors representing 40% of indirect emissions remained entirely unaddressed. All cities can address their entire carbon footprint through soft measures, and six out of eight could address over 75% of indirect emissions through hard regulatory measures. The scope of climate action on consumption-based emissions is determined by political will, policy prioritization and administrative capacities rather than legal constraints. We discuss pathways for cities to address these emissions despite the ongoing challenges of accurate measurement and monitoring. Strengthening local democratic decision-making processes can enhance the legitimacy and accountability of consumption-focused climate action, and city networks as well as national legislation could play a key role in scaling up implementation.
Severe convective events are impactful and costly for Australia’s economy and environment. The impact of climate change on these events is unclear due to competing changes in atmospheric instability, vertical wind shear and convective inhibition. Here, we use an ensemble of high-resolution (10 km) climate simulations, including a set of atmosphere-only and ocean-coupled simulations, dynamically downscaled from CMIP6 global climate models (GCMs), to examine the impact of climate change on severe convective environments (SEV), and environments conducive to hail (SEV-hail) in Australia. We found days with SEV are projected to increase across most of the continent and in most capital cities. The largest increases to SEV and SEV-hail were found in summer (DJF) and spring (SON), the seasons where SEV and SEV-hail occur most often in the present. We use global warming levels (GWLs) to look at the impact of climate change and found high model agreement on the sign of change, with the signal of SEV increases emerging from the noise at 3°C of global warming in DJF across most of Australia. The largest increases in SEV days in capital cities were found in Sydney and in the Australian Capital Territory (ACT), with both areas having approximately 6 additional SEV days in DJF with 3°C of global warming. Trends in agricultural areas were similar to trends in the cities, with New South Wales (NSW) agricultural areas having approximately an additional 7 SEV days in DJF, and Queensland having an additional 3 days. SEV-hail decreased or did not change in most areas, but increased in south-western Australia, and in Perth and Adelaide by about 1–2 days at 3°C of global warming in DJF. Our results show generally increasing risk to cities and agricultural areas from a warmer future and highlight the need to enhance resilience to mitigate and adapt to climate change.
Anticipating the Flood (Anticipando la Crecida, ALC) is an outreach and research initiative focused on the co-construction of flood early warning systems (EWSs) in vulnerable neighborhoods of the Metropolitan Area of Buenos Aires (AMBA), Argentina. The approach is participatory, promoting collaboration among local actors, professionals from several disciplines, and academic and scientific communities to design solutions tailored to the specific social and environmental conditions of each community. This work aligns with three of the four priorities of the Sendai Framework for Disaster Risk Reduction, addressing disaster risk understanding, risk governance, and disaster preparedness. With over ten years of interinstitutional dialogue, ALC has been able to contextualize its actions within the political, social, and environmental settings of flood-prone neighborhoods. This sustainable approach enables the project to remain relevant over time by involving professionals, lecturers, and students in response to community needs supported through funding obtained from diverse sources. These processes have built trust between local actors and scientific institutions, facilitating the co-production of situated knowledge on flooding and the emergence of new research questions. The paper presents the protocol developed by ALC for the co-production of community-based EWSs. The results demonstrate that a bottom-up approach can effectively connect scientific knowledge with concrete actions that improve the quality of life of vulnerable populations exposed to flooding, highlighting the importance of community participation, spaces for listening and dialogue, and policy integration across all levels of the state to strengthen disaster risk management.
Some terrestrial regions have cooled despite increases in global average near-surface air temperature. It is important to study these ‘warming holes’ to understand regional climate processes and to develop strategies to mitigate global change impacts. Many warming holes have occurred in places with changes to regional hydrology. As a consequence, increases to latent heating due to shifts in specific humidity may obscure changes due to temperature (enthalpy) when studying the full energy budget of the near surface atmosphere. We ask if known warming holes in the southeastern U.S. (SEUS), northern North American Great Plains (NNAGP), and southeastern China result from such ‘water-for-temperature’ tradeoffs using a Bayesian approach that accounts for both temporal and spatial autocorrelation in climatic variables from ERA5. The SEUS warming hole lost more energy (up to −100 J kg ^−1 yr ^−1 ) than apparent from temperature trends alone, as it also became drier. The NNAGP exhibited the well known transition along the 100th meridian in which the semi-arid west lost enthalpy and latent heat, and the humid east gained near-surface atmospheric energy; these patterns were not apparent from temperature trends alone. Increases in latent heat of 50 J kg ^−1 yr ^−1 or more in the southern part of the southeastern China study area shifted significant trends in near-surface atmospheric energy further north than what was revealed by temperature trends alone. The magnitude of trends in latent heat often exceeded those of enthalpy across all study areas, emphasizing the importance of incorporating water and a more complete depiction of the energy balance into studies of regional climate.
North American wildfires are growing in frequency, extent, and intensity in recent decades, threatening ecosystems, human health, and infrastructure. While long-term trends are driven by anthropogenic warming, internal modes of oceanic variability can influence wildfire weather through adjustment in large-scale circulation and surface energy fluxes. Here, we examine how decadal to multidecadal variability, including the Pacific decadal oscillation (PDO) and the Atlantic multidecadal oscillation (AMO), modulates the influence of the El Ni & ntilde;o-Southern oscillation (ENSO) on early summer (April-June) wildfire risk. El Ni & ntilde;o is associated with increases in intensity of wildfire weather by up to 25% and earlier onset of favorable fire weather conditions by up to 10 d in western and central northern North America relative to the 1960-2020 climatology, whereas La Ni & ntilde;a corresponds to broadly opposite patterns. Decadal to multidecadal variability, such as PDO and AMO, further modulates ENSO responses, with compound phase alignments associated with larger regional anomalies and shifts in fire weather onset. These findings clarify how natural climate variability shapes regional wildfire weather and seasonal timing, providing insight relevant to risk assessment and adaptation in a warming climate.
To limit global warming to 1.5 or 2° by 2100, carbon dioxide removal is essential. Currently, re- and afforestation are the main implemented carbon dioxide removal practices and will be key to mitigate climate change. La Plata Basin, located in South America, has been suggested in the literature as one of the most strategic regions in the world to implement these techniques, but the prosperity of forests and their capacity to act as a carbon sink under increasing climate change is not well studied in general, and even less so in the La Plata Basin. In this work, we study changes in climatic impact-drivers that are relevant for risk and impacts for tropical forests. We apply the dynamical storyline methodology to construct seasonal storylines, conditional on the response of large-scale circulation to global warming, of change in five climatic impact-drivers : mean near-surface air temperature, agricultural/ecological drought, fire weather, mean precipitation, and aridity. We construct two final storylines, by selecting self-consistent combinations of changes in large-scale circulation throughout the seasonal cycle. In this way we can assess the plausible simultaneous response of the five climatic impact-drivers as a function of global warming on both seasonal and annual timescales. We find that the northeastern La Plata Basin, a key region for re- and afforestation, has the most challenging climatic conditions for forests. Meanwhile, the southern La Plata Basin, a region where the natural vegetation cover is mostly grassland and has been suggested as a region for afforestation, has a more suitable future climate for forests. We highlight the importance of these kinds of regional studies because forest plantations remaining stable carbon sinks in a warming world is crucial to halt global warming. Furthermore, understanding whether the La Plata Basin can sustainably support large-scale forest expansion is crucial given its importance for water availability, agriculture, and energy production in the densely populated region.
The rapid growth of primary research on wildfire-climate linkages creates new opportunities for global synthesis and integration. Using a double diamond approach and the PRISMA framework, this systematic review analyses 470 peer-reviewed articles from ScienceDirect, Web of Science and Scopus, enabling a structured synthesis that bridges thematically focused research domains into an integrated perspective. We conduct a bibliometric analysis, identify key research themes and gaps, and examine the spatial and temporal distribution of wildfires and their ecological impacts. Our analysis reveals: (1) a strong research bias toward Australia, North America, and Europe, with first-author affiliations from these continents comprising 80%, while regions like Africa and Asia facing rising wildfire risks are underrepresented due to data limitations, weak policies, and resource constraints; (2) key themes include ecosystem vulnerability, evolving fire strategies, and forest fuel dynamics, but critical gaps remain in long-term fire management effectiveness, Indigenous fire knowledge integration, and interdisciplinary research; (3) rising temperatures, prolonged droughts, and changing precipitation patterns have intensified wildfire fire regime attributes including frequency, severity, seasonality, and burned extent globally. The revised synthesis now identifies three areas of strong scientific consensus: intensifying fire weather severity in Mediterranean-type ecosystems, western North America, and boreal forests; increasing high-severity fire extent in temperate conifer forests; and lengthening fire seasons globally. Two areas of conditional agreement are identified: savanna fire frequency trends mediated by land use–climate interactions; and prescribed burning efficacy at stand versus landscape scales. Two areas of ongoing scientific uncertainty are also identified: attribution of fire regime shifts between climate change versus land use and suppression legacies; and future reburning projections in tropical forests. While remote sensing technologies such as moderate resolution imaging spectroradiometer, VIIRS, and Landsat have advanced wildfire monitoring, gaps remain in achieving real-time, high-resolution fire detection, especially in regions like Africa and Asia; and (4) finally, the reviewed literature consistently identifies a lack of interdisciplinary research that integrates fire ecology, climate science, and socio-economic dimensions, a gap that continues to limit both rigorous attribution analyses and the development of policy-relevant synthesis. Our findings highlight the urgent need for coordinated global efforts combining Earth observation technologies, advanced modelling and region-specific fire strategies.
Stratospheric aerosol injection (SAI) programs are generally understood to be technologically straightforward and inexpensive relative to other climate interventions or remedies. This gives rise to the sensible question of whether uninvolved states are at risk of having their climates covertly manipulated without their knowledge by other actors. This article seeks to contextualize and ameliorate that fear. We first survey the wide range of SAI experiments and deployments that are theorized to clarify the deployed mass requirements necessary to create discernable impacts in uninvolved states. We then explore two methods that could be reliably used by civilian uninvolved parties to detect such deployments well before they reached the scale required to induce climatic impacts. These involve detecting the plumes of sulfate precursor gases shortly after their injection using existing satellite instruments capable of monitoring point source emissions and identifying the aircraft fleets and support operations that would be required to transport and release those precursors high in the atmosphere. While small process experiments with negligible surface impacts could easily be conducted covertly, we demonstrate that deployments of the scale required to create climatic impacts would be discernible by uninvolved parties well before any climatic impacts would occur.
