Earths Future最新文献

Global sea-level rise is intensifying pressures on coastal regions, increasing the need for adaptation strategies (e.g., protect, retreat, accommodate). At the same time, decision makers require a better understanding of the available responses to address the widening adaptation implementation gap. Structural measures aimed at reducing the impacts of coastal hazards as part of the accommodation strategy have received limited attention in the coastal adaptation literature with few studies looking at how it is currently considered to address sea-level rise. We first advance a conceptual framework that separates structural from non-structural accommodation, recognizing that this distinction is essential to accurately define the adaptation “solution space.” Building on this framework, we synthesize scientific and gray literature, conduct a multilevel review of policy and technical documents, and draw on expert input to not only evaluate the current state of structural accommodation in Europe but also to highlight generic lessons for its potential implementation. This includes consideration of its advantages and disadvantages. Uptake remains fragmented and highly localized, embedded mainly in municipal spatial planning rather than national adaptation agendas, and is hampered by financial, institutional, and technical constraints. We argue that stronger policy integration and dedicated financial incentives could overcome these barriers and harness accommodation's value as a flexible option capable of reducing risk and avoiding long-term lock-in. This study improves our understanding of how this strategy can contribute to coastal resilience in Europe and beyond.

Meteorological drought, one of the most destructive natural hazards, is driven by both precipitation deficits and high evaporative demand. While precipitation has traditionally been considered the dominant driver, recent studies suggest an increasing influence of evaporative demand. However, it remains uncertain whether these findings represent individual regional cases or a boarder emerging global trend. To address this, we developed a systematic framework using a standardized precipitation evapotranspiration index (SPEI) variant experiment to attribute drought drivers across 292 major global basins. Our historical analysis (1970–2024) reveals a widespread global transition: 48.1% of the global basin area (6.43 × 10⁷ km²) transitioned from precipitation-dominated to evaporative demand-dominated drought. This transition, accelerating after 2000, originated in arid continental interiors and expanded outwards, leaving precipitation-dominated areas only one-tenth the size of evaporative demand-dominated ones. Future projections from bias-corrected coupled model intercomparison project phase 6 models indicate this transition is largely irreversible, as over 80% of historically transitioned basins are projected to maintain evaporative demand-dominated through 2100. Basins that have not yet transitioned are also projected to transition toward either evaporative demand-dominated or precipitation and evaporative demand co-dominated drought states. Under the shared socioeconomic pathway (SSP) 5-8.5 scenario, the global area of evaporative demand-dominated droughts is projected to be 17.6% larger by 2100 than under SSP1-2.6 scenario. These findings highlight the urgent need for both climate mitigation to slow these transitions and proactive adaptation to address the new reality of drought driven by evaporative demand.

Future projections of climate change are uncertain, in part because of uncertainty in future greenhouse gas emissions. However, current widely used emission scenarios and related physical climate projections have no probabilities associated with them, presenting a challenge for risk-informed climate adaptation decision making. Motivated to close this gap, we demonstrate an ensemble of full-complexity Earth System Model-based climate projections that include explicit estimates of emissions uncertainty. This approach avoids the need to condition future Earth System Model projections on storyline-based climate scenarios and provides information that can be probabilistically interpreted directly for arbitrary climate metrics including regional climate impact drivers. This addresses a key need of climate risk assessment for climate adaptation. Our demonstration is intended to motivate further engagement on development and delivery of probabilistic climate information, that complements information from scenario-based climate projections.

Mountain grasslands are vital ecosystems providing critical services such as carbon sequestration, water regulation, and biodiversity conservation. However, these ecosystems are increasingly threatened by climate change and human activities. This study evaluates vegetation dynamics in global mountain grasslands (2000–2021) using remote sensing data, CMIP6 climate projections, and human modification indices. By means of machine learning models (Random Forest, eXtreme Gradient Boosting (XGBoost), and Long Short-Term Memory (LSTM)) we identified dewpoint temperature, total evaporation, and human modification as dominant predictors of vegetation change, while soil water content and latent heat flux exhibited region-specific impacts. Results indicate that 35.1% of grasslands remained stable, 32.1% improved, and 32.7% degraded, with degradation hotspots identified in the Tibetan Plateau, Ethiopian Highlands, Rocky Mountains, and Andes, while the Middle Eastern Mountain Ranges showed signs of improvement. Future projections using a hybrid XGBoost–LSTM model indicate limited global-scale vegetation shifts by 2050 across SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios. However, regional differences are notable: the Tibetan Plateau shows a substantial increase in vegetation cover, while the Andes, Rocky Mountains, and parts of East Africa exhibit slight changes. Distributional shifts, especially under SSP5-8.5, suggest increasing spatial heterogeneity in grassland responses. These findings underscore the importance of regional-scale strategies to support grassland resilience under future climate and land-use pressures.

Degradation of coral reefs over the past several decades has caused regional-scale erosion of the shallow seafloor that serves as a protective barrier against coastal hazards along southeast Florida, USA. How future change in coral reefs may affect coastal flooding, however, has been less attended than other factors contributing to increasing risks such as sea-level rise and more intense storms. Here, the increased flooding hazard faced by Florida's coastal communities from the projected future degradation of its adjacent coral reefs is evaluated through oceanographic, coastal engineering, habitat, geospatial, and socioeconomic modeling. Risk-based valuation approaches were followed to map flood zones at 10-m² resolution along 430 km of Florida's reef-lined coast for the current and projected future coral reef conditions. The projected degradation of Florida's coral reefs can increase annual flooding to more than 8.77 km² of land and 4,980 km of roads, affecting more than 7,315 people, $412.5 million in damages to 1,400 buildings, and economic disruption of $438.1 million annually (2024 US dollars). The degradation of Florida's coral reefs would increase the annual risk to people and structures by more than 42% and 47%, respectively, but is spatially variable due to the heterogeneous alongshore nature and distribution of the reefs and communities: the increased risk exceeds $1 million/km annually to more than 17% of the coastline but also disproportionately would affect vulnerable populations. These results help identify areas where coral reef protection could help reduce the projected increased storm flooding risk to Florida's coastal communities.

Surface ozone (O₃) has complex relationships with its precursors and is also highly sensitive to meteorological variation and climate change. In China, ground-level ozone pollution remains a persistent air quality concern despite decreasing concentrations of other air pollutants in recent years. China's commitment to achieving carbon neutrality by 2060 is expected to result in unprecedented reductions in air pollutant emissions in the future. This study investigates the combined impacts of anthropogenic emission reductions and future climate change on the evolution of summertime surface O₃ under China's carbon neutrality target and the ambitious global 2°C warming scenario. Model simulations reveal an approximately 43% decline (range 31%–49%) in summertime daily maximum 8-hr average (MDA8) O₃ in China's six heavily polluted key regions from 2020 to 2060. However, risk of rebound is also projected in some near years due to weather-driven accelerated O₃ production rate, enhanced biogenic volatile organic compound (VOC) emissions and atmospheric stagnation, partially offsetting emission reduction benefits. The substantial aerosol reductions (by over 80%) would also enhance MDA8 O₃ (up to 10 ppb) from 2020 to 2060 primarily via heterogeneous reactions on aerosols. The high O₃-temperature sensitivity poses challenges to O₃ mitigation in the short term, with frequent heatwaves or droughts dampening the outcomes of ongoing anthropogenic emission control. In the long term, O₃-temperature sensitivity would be reduced by nearly half thanks to continuous anthropogenic emission control, thereby gradually increasing O₃ climatic resilience. Quicker and stronger emission control, especially for the anthropogenic VOCs, would significantly mitigate short-term rebound risks.

Facing increasing risks from climate change, governments at all levels have started to mainstream the use of climate information. It has been widely acknowledged that the inclusion of stakeholder knowledge and needs, for example, in a co-design and co-production process, is important for producing user-relevant information. Here we start from a hypothetical example and two real-world case studies from South America and West Africa to discuss the role of user values, power relationships and language in the construction of climate information. While these aspects have been discussed individually in several papers, we focus on the mutual influences of these aspects in the information construction and argue that, therefore, they cannot be considered separately. We identify five dimensions—the level of risk, the complexity of the scientific problem, user values, power relationships and language—to characterize the complexity of a given user context. Analyzing these dimensions can guide the choice and design of user engagement in a given situation. In particular, even basic research may benefit from such an engagement. Regularly accounting for these aspects in research projects may require substantial changes in the way research funding is organized and how the work of researchers is rewarded.

The escalation in extreme weather events has raised concerns for agriculture. The quantification of the impacts of extreme events on crop yield has predominantly concentrated on individual events like drought or heat. Numerous instances have showcased the destructive effects of compound extreme events on crop yields, surpassing those of individual events. However, their influence extent is region-specific and not fully understood in Australia's crop belt. Using a biophysical-statistical modeling approach, we quantified the individual impacts of drought, heat, frost, and compound drought and extreme temperature (DET) events on wheat yield variations in Australia. We first developed indices for these different extreme events during the wheat reproductive period based on the APSIM (Agricultural Production System sIMulator) model and then used these indices in multiple linear regression models to quantify their impacts on wheat yield variations. We found that, during 1990–2021, drought, heat, and frost events explained 48% of yield variation, while the percentage increased to 54% after including DET events, with some regions even up to 86%. In extreme low-yield years, the relative importance of DET events surpassed the sum importance of individual drought, heat, and frost events, reaching 52% in years with yields below the 10th percentiles, respectively. Our findings highlight the need to factor compound extreme weather events into climate risk management to inform the mitigation of yield losses or crop failure.

Regional disparities in natural energy resources may impede the acceleration of energy transitions in regional power systems, as the shift to net-zero power systems requires significant energy inputs. Net energy, defined as the surplus remaining after accounting for energy inputs, serves as a key metric of system performance. This study examines the net energy performance of nine regions across the nine decarbonization scenarios to 2050 using the systemwide energy return on investment (EROI) framework. This framework adopts a holistic approach to assess primary energy quality at the electricity level, using the cumulative energy demand indicator derived from life cycle assessment analysis, and integrating EROI calculations with outputs from the LUT Energy System Transition Model. None of the regional EROIs fall below 10, often regarded as a global threshold for viability, although accounting for social factors and regional variations, the minimum EROI necessary to sustain societal functions may differ substantially. Thus, the regional energy transition (ET) is techno-economically feasible without incurring a resource curse arising from further energy needs. Low-cost renewable energy (RE) technologies dominate the energy mix, while other extractable regional natural energy resources have a minimal impact on EROI trends. In highly variable RE penetrations mainly driven by solar photovoltaics and wind power, the greater requirement for enabling technologies entails a decline in regional EROIs. In essence, achieving a net-zero and cost-effective ET requires prioritizing low-cost RE technologies, indirectly mitigating the risk of a renewable resource curse and furnishing policymakers with a compelling rationale for their strategic importance.

Future population growth is expected to concentrate in urban agglomerations that overlap with various natural hazard zones. However, quantifying the resulting risks remains challenging, as hazard areas tend to be bounded locally while population forecasts are produced at much coarser scales. Addressing this gap, the high-resolution 2UP model disaggregates national-level, scenario-based population projections to a 30 arc-seconds grid, simultaneously simulating urban expansion and the distribution of urban and rural populations through 2100. By overlaying these projections with comparably detailed fluvial flood and landslide hazard data, this study demonstrates that, at a global scale, rapid urbanization will disproportionately increase population growth in hazard-prone zones compared to safer areas. This trend is particularly pronounced in sub-Saharan Africa and South Asia, where both the extent of exposed urban land and the magnitude of exposed populations are projected to rise sharply. In contrast, slower growth in North America and Europe leads to more moderate increases in hazard exposure, with smaller differences between hazardous and non-hazardous sites. Notably, while urban areas in many countries continue expanding into high-risk regions, the fraction of the total population exposed to these hazards may stabilize or even decline after 2050. The 2UP model's fine-grained outputs are especially valuable in regions with fragmented urban landscapes, large rural populations, and rapid demographic shifts, providing decision-makers and researchers with critical insights for integrated risk management and sustainable development planning.