Earths Future最新文献

Despite contributing minimally to global greenhouse gas emissions, Africa is warming faster than the global average and is projected to experience disproportionately severe heatwave-related impacts on ecosystems, human health, and economic activity. Using Coupled Model Intercomparison Project Phase 6 (CMIP6) models, we assess projected changes in compound heatwaves (CHWs, defined as co-occurring daytime and nighttime heatwaves) across Africa at three global warming levels (GWLs; 1.5°C, 2°C, and 3°C) and under three Shared Socioeconomic Pathways (SSP245, SSP370, and SSP585). Our findings reveal a robust intensification of CHWs with increasing GWLs across all scenarios. Even though the projected change is consistent across all three scenarios, under SSP370 the population exposure is higher due to a larger increase in population. Similarly, under SSP585, the Gross Domestic Product (GDP) exposure is higher because of rapid GDP growth fueled by fossil energy. Western, central, and eastern Africa are the most affected, with exposures increasing by tens to thousands of times. Additionally, rare CHWs historically occurring once every 50 or 100 years are projected to become more frequent, potentially recurring every 5–6 years, even under modest 1.5°C warming. We find a strong, statistically significant positive correlation (r > 0.85, p < 0.01) between near-surface temperature and changes in CHW metrics, indicating continued warming will further exacerbate CHWs. Surface energy budget analysis reveals that this projected warming is driven primarily by enhanced net downwelling surface radiation, modulated by enhanced downwelling longwave radiation under clear-sky conditions. Strengthening mid-to upper-tropospheric anticyclonic systems further contribute to warming.

Land-use change is a primary driver of ecosystem degradation in terrestrial biodiversity hotspots, undermining global sustainability commitments. However, tracking progress under the Land Degradation Neutrality (LDN) policy, which aims to balance degradation with restoration, requires a systematic assessment of cumulative trends, a critical underexplored gap. Here, we present the first comprehensive annual assessment of land-use changes in these hotspots (1992–2022) guided by the LDN framework. We found that 9.4% of hotspots experienced land-use change, with rates declining by 0.06 Mha/year (1992–2015) before accelerating to 0.4 Mha/year (2016–2022). While human-driven impacts (e.g., deforestation, agriculture shifts) initially dominated, causing net natural ecosystem losses, post-2015 land-use improvement efforts (e.g., revegetation) increased. Yet, net land-use degradation outweighed improvement, resulting in a land-use debt of 29.1 Mha (0.9% of global hotspots). Driven by tropical deforestation, dryland degradation, agricultural shifts and urbanization, this debt correlated with impaired ecosystem structure and function. For instance, agricultural dynamics strongly correlated with reduced greenness in high-debt continents like Asia and the Americas (r = −0.92 and r = −0.80, respectively). Despite continental-scale greenness stabilization post-2015 (stable NDVI > 92%), these regions showed reversed carbon uptake, with net primary productivity declining to −0.0032 and −0.002 Kg C/m² yr⁻¹, respectively. This vegetation greenness paradox, where stable structural greenness masks functional degradation, reveals that current improvements remain insufficient to offset historical degradation, and that structural stabilization may not guarantee functional integrity. Thus, reversing land-use debt necessitates a locally tailored policy framework that prioritizes functional recovery alongside structural greening to ensure LDN restoration practices deliver ecosystem integrity in these hotspots.

Under global brightening and warming, how intense solar radiation amplifies crop stress via photoinhibition remains poorly understood. Using data from 905 counties in China (1992–2018), we reveal that a 1% increase in dry-heat-intensive radiation (DHR) frequency reduces summer and spring maize yields by 0.36 ± 0.12% and 1.26 ± 0.48%, surpassing declines from other extreme events. High-frequency DHR events depend on strong temperature-VPD (>0.6) and temperature-solar radiation coupling (>0.5). Due to projected increases in DHR frequency, 2021–2050 maize production is expected to change by −4,151 ± 1,472t to −80 ± 28t for summer maize and −1,938 ± 681t to 1,787 ± 620t for spring maize under SSP1-2.6, with similar trends under SSP5-8.5. Although increased precipitation and radiation partially offset losses, the warming effect largely negates these benefits, resulting in production declines of 1.55% for summer maize and 9.35% for spring maize. This study highlights the overlooked role of photoinhibition in yield loss and underscores the urgency of mitigating DHR risks to safeguard agricultural production under climate change.

Marine cloud brightening (MCB) via sea-salt aerosol (SSA) injections is one commonly researched method to cool the Earth either regionally or globally, and potentially reduce impacts of global warming. There is evidence from both high-resolution climate modeling and natural analogs that the introduction of aerosols in the Arctic atmosphere leads to cloud brightening. This study is the first comparison of Arctic MCB using multiple Earth System Models (ESMs). All three models suggest that SSA injection induces cloud and sky brightening that can substantially cool the Arctic. However, uncertainties in aerosol-cloud interactions mean that the SSA mass required for cooling varies greatly between models, a feature which was also found for injections at lower latitudes. We evaluate a possible Arctic MCB scenario in which SSA injection is scaled up over time to maintain near present-day annual-mean Arctic surface air temperature under a moderate greenhouse gas emissions scenario. The MCB cooling of the Arctic successfully maintains Arctic sea ice and, in contrast to our expectation that cooling one hemisphere leads to the large tropical rainfall shifts, we do not see robust precipitation changes outside of the Arctic. The Atlantic Meridional Overturning Circulation (AMOC) is also shown to be maintained but we caution that not all processes driving the AMOC are represented in these ESMs. Finally, we emphasize that we idealize aspects of the SSA injection in these simulations and we do not consider the technical or governance feasibility of deploying Arctic MCB, nor the impacts on coastal communities, ecosystems, and atmospheric chemistry.

This study explores the drivers of urban water use and their spatial-temporal patterns in 142 small and mid-sized cities across the Contiguous United States (CONUS) by analyzing the data directly collected from these cities and using advanced machine learning techniques. We identify five distinguished clusters across CONUS, each showing unique trends of the impact of drivers on water use. We find that socioeconomic factors significantly influence water use in eastern and southwestern cities, while climatic variables such as precipitation and temperature range dominate in central and northwestern regions. Temporal analysis reveals the impacts of major socioeconomic and climatic disruptions on urban water use in the period 2011–2021, including the COVID lockdown, the rapid growth of data centers, and the drought of 2012. In addition, our analysis suggests that economic growth in small and mid-sized US cities continues to be accompanied by rising water use, contrasting with the opposite trend observed in large cities in prior studies. This implies that as smaller cities develop, their water use may increase above current levels until incomes reach a higher threshold, highlighting the need to improve water use efficiency. This study also presents useful insights for developing effective water demand management strategies in response to climatic variability and socioeconomic growth in small and mid-sized cities.

This study uses different downscaling techniques and reference observations to investigate the characteristics of extreme storm events over the conterminous United States in historical and a projected future scenario. While previous studies agree on the projected changes in intensity and frequency of precipitation extremes, there is a lack of consensus regarding how their size will change in response to an increase in radiative forcing. Moreover, the influence of different downscaling techniques on their characteristics has not been thoroughly examined. This study employs an ensemble of high-resolution projections derived from six CMIP6 GCMs, using dynamical, statistical and artificial intelligence based downscaling techniques and two reference observations. Overall, we find noticeable differences in the size, average depth, and total precipitation volume of these storms among the climate ensembles in the historical period. Despite these differences in the historical period, we find consistent future changes across various ensembles. We find a robust projected increase in storm size during Winter and Spring but a decrease in size during Summer in the East. Nevertheless, irrespective of changes in their size, extreme storms are projected to intensify across all the ensembles and seasons.

Multiple hazard risks (MHRs) in coastal zones will continue to increase due to climate change and rising sea levels. These disproportionate impacts create shared challenges that require cross-border mitigation efforts. However, understanding how coastal areas exhibit common risk patterns and how such patterns can inform risk-based cooperation remains fairly limited. Here, we investigated international cooperation potential among 126 coastal countries from an integrated perspective of their risk similarity, geopolitical stance, and knowledge exchange. We conducted a high-resolution assessment of multiple hazard risks (including earthquakes, landslides, flooding, and cyclones) and developed a bottom-up similarity measure to identify common risk profiles across regions from both size and space. Our analysis revealed a notably high degree of risk similarity across country pairs, suggesting greater potential for cooperation than that previously recognized; 89% of country pairs with high risk similarity lacked strong partnerships in consensus-building or knowledge-sharing. This cooperation gap was even more pronounced in the Global South and small island developing states. Instead of relying solely on geographic proximity or existing alliances, we argue for a shift in focus toward partnerships grounded in shared risk challenges. This approach can help to build collective resilience to achieve Sustainable Development Goals for climate action (SDG 13) and partnerships for the goals (SDG 17).

The large-scale atmospheric circulation is a key driver for regional climate extremes, yet its response to anthropogenic forcing remains uncertain. The Pacific trough (PT) regime is a persistent circulation pattern modulating temperature, precipitation, and fires over North America. We show that the observed boreal winter-spring (December to May) PT frequency and duration have increased significantly over the past 76 years, contributing to amplified extreme anomalous heat over western and central Canada. These observed changes are not well represented in the climate simulations analyzed herein. However, our results indicate that rising greenhouse gas concentrations likely contribute to increased winter-spring PT frequency, which is further modulated by sea surface temperatures (SSTs). While the recent La Niña-like and negative Pacific Decadal Oscillation-like SST trends have dampened this increase, our results suggest that if an eventual emergence of the modeled El Niño-like response to elevated $���{\text{CO}}_2��$ were to occur in reality, it would reinstate the increase in PT frequency, duration, and downstream amplification of regional extreme heat. However, the occurrence, timing, and magnitude of this shift remain uncertain, given the complex, interlaced role of external forcings and internal variability in modulating historical trends, as well as models' inability to reproduce them. Additionally, modeling decisions regarding future trajectories for anthropogenic emissions, including aerosols and greenhouse gases, play a critical role in projecting future changes in PT frequency. Our findings underscore the need for a better understanding and modeled representation of long-term changes in the atmospheric circulation to inform climate adaptation and risk assessment.

Chile has endured a decade-long “mega-drought,” yet it remains unclear whether this represents a temporary climate anomaly or the onset of long-term aridification. While droughts are typically temporary events, persistent or recurrent droughts can indicate a transition toward aridification, that is, a gradual shift to drier conditions. We assessed how temporal changes in water supply and demand at multiple time scales affect vegetation productivity and land cover changes in continental Chile to diagnose the region's climate trajectory from drought to aridification. Since 2000, much of the region has seen a continuous decrease in water supply alongside a rise in atmospheric water demand. Further, in water-limited ecoregions, evapotranspiration, likely reflecting reduced transpiration or vegetation cover, has declined over time, with this trend intensifying over longer time scales. A long-term decline in water availability and shifting demand have led to declining vegetation productivity, especially in the Chilean Matorral and the Patagonia Steppe ecoregions. We discovered a link between these declines and drought indices related to soil moisture and actual evapotranspiration at time scales of up to 12 months. Further, our results indicate that the trends in drought indices account for up to 78% of shrubland and 40% of forest area changes across all ecoregions. The most important variable explaining cropland changes is the burned area. Our findings suggest that Chile is undergoing a transition from episodic drought to aridification, underscoring the need for adaptation strategies aligned with this emerging baseline.

Extreme sea levels leading to coastal flooding result of the combined action of waves, storm suges and astronomical tides, often referred to as the total water level (TWL), under storm conditions. Identifying different types of storms, along with their associated durations and uncertainties, provides valuable information for constructing accurate hydrographs and generating reliable flood maps. In this study, we characterize TWL storms, considering their shape and duration, with a focus on coastal flood analysis across Europe. Our proposed approach comprises three steps. First, we classify TWL storms based on their shape. We identify four storm types around Europe that reflect the different relative contributions of TWL components. Second, we introduce a method to determine the duration of individual historical storms, which is applied to estimate the durations of return level events using storm duration functions. We emphasize the importance of accurate duration functions, especially for the longest storms observed in the Mediterranean Sea, for both historical and extrapolated return period events. Third, we implement a new method to design hydrographs for extreme events, enabling the assessment of water volumes resulting from different scenarios. Due to regional variability of scenarios, the semi-enclosed Baltic and Mediterranean Seas exhibit storm surge-dominated and mixed-type storms, respectively, with associated uncertainties exceeding 20%. Our approach considers uncertainties in both storm shape and duration, particularly when the contribution of TWL components is unknown.