Earths Future最新文献

Ocean dynamics related to large-scale circulation, such as the Gulf Stream, and smaller local ocean currents are an important driver of coastal sea-level variability along the U.S. East Coast. A relevant circulation feature in Southern New England is the Shelfbreak Jet (SBJ). The SBJ flows equatorward from the Labrador Sea toward the Gulf Stream at Cape Hatteras, following the shelf break along the Northeast U.S. Coast. The SBJ and sea level are highly correlated along the Southern New England Coast, especially at timescales of 1–15 days. Since this frequency band coincides with meteorological timescales, we explore the implications for coastal flooding. We find that SBJ transport explains, on average, about 30% of the storm surge variance along Southern New England, in a statistical sense. For a specific Nor'easter storm in March 2018, SBJ dynamics are responsible for more than 90% of the storm-surge height observed during a flood 4 days after the peak of the storm. Our results suggest local ocean dynamics are an important component of storm surges in Southern New England and can contribute, in some cases, to lingering flooding after a storm has passed. Thus, our results suggest that focusing only on large-scale circulation, such as the Gulf Stream or meridional overturning, may not be complete for understanding the dynamics essential for coastal impacts. We recommend that the role of local ocean dynamics in floods should be investigated further in other regions.

Indigenous-led Nature-based Solutions (“Indigenous-led NbS”), such as Indigenous Protected Conserved Areas and Indigenous Guardians programs, may represent a unique opportunity to advance climate and biodiversity targets grounded in Indigenous self-determination. Previous studies have comprehensively explored the scope and potential environmental outcomes of Indigenous-led NbS. Here, we build on this literature to assess how government support for Indigenous-led NbS influences climate and biodiversity outcomes. Specifically, we estimate the contribution of Indigenous-led NbS funded by the federal Government of Canada in conserving carbon stocks and biodiversity across terrestrial ecosystems. Using geospatial analysis and quasi-experimental methods, our results indicate that Indigenous-led NbS are as effective as existing Protected Areas in terms of climate change mitigation and biodiversity conservation. Moreover, our results demonstrate that government funding for Indigenous-led NbS is associated with moderate yet significant avoided land use emissions relative to Protected Areas. Based on topic-modeling applied to Indigenous-led NbS descriptions, climate and biodiversity outcomes emerge from holistic approaches to governance, intergenerational knowledge exchange, and climate-biodiversity action. Thus, government funding to Indigenous-led NbS may align biodiversity and climate outcomes with some aspects of Indigenous self-determination. The long-term alignment of these outcomes will require extended and sustained funding as well as full recognition of the rights of Indigenous Peoples.

Global warming and internal climate variability have changed winter temperature extreme regimes in North America, affecting droughts and wildfires in the western United States. However, how internal climate variability influences North American winter temperature extreme patterns remains poorly understood. Here, we demonstrate that the recent winter North American surface air temperature (SAT) exhibits an accelerated decadal alternation between Warm West-Cold East (WWCE) and Cold West-Warm East (CWWE) dipoles because their variations show shorter decadal periods during 1990–2022 than during 1950–1989 and are regulated by the Pacific Decadal Oscillation (PDO) variability. While the winter WWCE dipole mainly linked to North Pacific blocking events exhibited a smaller mean amplitude during 1990–2022 than 1950–1989 due to the weakened positive PDO phase during 1990–2022 under the positive phase of the Atlantic Multidecadal Oscillation (AMO), the winter CWWE showed a larger mean amplitude during 1990–2022 due to the stronger negative PDO phase than during 1950–1989. Our results further suggest that the recent rapid decadal shift of North American winter temperatures is primarily attributed to the PDO variability likely due to anthropogenic warming under the positive AMO.

Extreme weather events that occur concurrently are especially damaging to society, agriculture, the economy, and ecosystems. Here, we investigate the spatial distribution, trends, persistence properties, and temporal shifts of concurrent heatwaves and droughts (CHWDs) across Canada from 1979 to 2018. Our results indicate that the regions of British Columbia and the Prairies are more susceptible to a high number of CHWDs and the Arctic region is affected by less frequent but more intense CHWDs (on average 44 and 25 events respectively). The Arctic regions also have the highest increasing trend of CHWDs due to the higher trends of temperature as compared to other regions. We also explore the relationship of CHWDs with large-scale climate drivers. The North Atlantic Oscillation has the most influence on the CHWDs affecting the coastal regions and the Arctic. EP-NP and WP also show a correlation with the CHWD events occurring in central Canada. A relatively high persistence in northeast Canada, coupled with the increasing trend of the total duration of CHWDs, highlights the increasing risk of CHWDs. We note that the timing of CHWDs shifts toward early summer in parts of the Yukon and Northwest Territories and toward late summer in the Canadian Arctic Archipelago. The changes in the number of concurrent events, their total duration, and temporal shifts of occurrence should be incorporated into adaptation and mitigation policies. The rapid variability and inconsistency of CHWDs across Canada emphasize the critical need for region-specific hazard assessments that incorporate these concurrent extreme events.

Deep soil water (θ_d), defined here as past precipitation stored in deep unsaturated soils and not replenished by precipitation in a single growing season, plays a vital role in helping trees withstand prolonged droughts in deep-vadose-zone regions. However, its contribution to total water use across tree growth stages and the effects of limited θ_d access on tree transpiration and photosynthesis remain unclear. To address this, a process-based model was parameterized using in situ root-zone measurements (from the soil surface to the apparent maximum root depth) and then used to simulate root-zone soil moisture, canopy transpiration and photosynthesis for two common species, apple (Malus domestica fuji) and black locust (Robinia pseudoacacia), in northern China. For trees aged 3–22 years, θ_d below 200 cm (θ_d200) accounted for an average of 31.9% and 40.9% of total water use in apple and black locust trees, respectively. Restricted access to θ_d200 led to decreases in annual transpiration rates and daily photosynthetic rates by 19.7% and 17.4% in apple, and by 26.2% and 20.2% in black locust. On a monthly scale, precipitation and transpiration greatly influenced θ_d200 for both species, while tree age and diameter at breast height were key annual determinants. These findings highlight a trade-off between physiological stability achieved via deeper rooting and the associated carbon costs of accessing θ_d. The findings here provide insights into sustainability of planted trees in deep vadose-zone regions.

Terrestrial water storage (TWS) in China, with the world's largest irrigated expanse and extensive mid-low latitude glaciers, is essential for effective water resource management and socioeconomic risk adaptation. However, the responses of TWS to human intervention and climate change, both during historical periods and under future scenarios, remain inadequately quantified. We reconstruct and project long-term TWS using a data-driven framework that integrates remote sensing, Earth system model (ESM) and machine learning. Our reconstructed record reveals an amplified TWS decline in China's drylands and a moderate yet persistent TWS reduction in glacier regions during 1985–2015, accentuated since the 21st century with a 13% increase in affected areas. TWS changes in drylands are primarily attributed to human irrigation ($��\sim �$39%) and precipitation ($��\sim �$24%), with the impacts of irrigation magnified by 9%–12% during drought. Humid basins show a moderate TWS response to irrigation and precipitation, modulated by intricate but unexplored interactions between atmospheric drivers, glacier-snow dynamics and underlying hydrological processes. Such discrepant response highlights the necessity for region-specific water resource management strategies: northern drylands should prioritize optimized irrigation practices while southern humid basins would benefit from enhanced adaptation to climate variability. Projections from nine ESMs indicate a likely amplification of TWS decline (13%–43%) in drylands and glacial zones by mid-century if maintaining current human intervention levels. Our findings emphasize the need to reassess climate change-induced water scarcity and refine human management regulations, particularly as existing strategies may be overlooking broader sustainability challenges in a warming climate.

Ports provide critical infrastructure services, supporting global trade, economic growth and development. Owing to their exposed coastal locations, ports are expected to face increasing climate-related risks, such as sea-level rise (SLR) and changes in storminess. However, there is a gap in current literature evaluating how ports are addressing climate-related risks through implementation of adaptation actions. This study explores if, and how, some of the largest commercial ports in the UK are adapting to risk in practice. Evidence of implemented adaptation action is extracted from Adaptation Reporting Power (ARP) reports, as mandated under the UK Climate Change Act 2008. Evidence of incremental adaptation was identified, in response to an increasingly diverse range of perceived climate-related risks. However, uncertainty around future changes in some climate-related risks, and different risk perceptions, meant ports were also coming to different judgments on when and how they should adapt. A discord between short and longer-term planning was also identified. Consequently, there remains the need to shift thinking from business-as-usual toward a more systematic and integrated consideration of short- and longer-term climate risks, adaptation and wider benefits to support decision making. This would align with a more transformational adaptation approach. This could include exploiting the renewal and investment cycle so new port infrastructure is climate-proofed when constructed. The framework presented here, to identify, catalog and evaluate implemented adaptation actions in the UK, could be applied to other regions. This would provide a more comprehensive picture of how ports are implementing adaptation globally.

The Arctic has experienced the most rapid warming on Earth in recent decades. This affects Canada's landmass, which extends well into the Arctic. Nevertheless, limited spatial and temporal observational coverage, combined with large climate model uncertainties, pose challenges to understanding both past and future climate changes in these regions relative to preindustrial conditions. This is particularly challenging in a place like Canada that has insufficient historical data to determine preindustrial reference conditions. Emergent constraints can overcome this limitation by using historical observations for the modern post-industrial era to constrain estimates of both preindustrial reference levels and future warming. Here we apply a carefully tested Bayesian observational constraint method to simultaneously assess the externally forced historical and future warming in Canada. Testing indicates that the approach reduces bias and uncertainty in historical and future warming estimates, increasing confidence that it may also serve as a basis for developing a broader understanding of climate change in other high-latitude regions. We estimate that external forcing from human activity, has warmed Canada by 2.2 [1.3, 3.1]°C between the 1850–1900 pre-industrial period and the recent 2015–2024 decade. Applying these same observational constraints to future climate conditions indicates that Canada will warm to 5.1 [3.2, 7.0]°C above pre-industrial levels by the end-of-century under an intermediate emissions scenario SSP 2-4.5, and to 6.7 [4.6, 8.9]°C under a high-emissions scenario SSP 3-7.0, with the largest warming projected for Northern Canada, followed by Quebec.

Climate change calls for adaptive strategies to manage land system across governance levels, as differing multi-level policies distinctly shape land system and long-term ecosystem resilience. This study proposes an iterative approach for optimizing land-use pathways that balance competing policy objectives across national, provincial, and local levels without compromising ecosystem integrity in a changing climate. This approach was applied to the Huangshui River Basin on China's Qinghai-Tibet Plateau, a region facing significant challenges from climate change and human activities. We integrated the land-use change model CLUMondo with the dynamic vegetation model LPJ-GUESS to compare our sustainable development pathway against scenarios based on plans prioritizing national, provincial, and local governance objectives. The analysis revealed considerable mismatches in management goals across governance levels within the Huangshui River Basin, emphasizing the necessity of multi-scale coordination to align planning objectives for achieving desired goals. This study presents an optimization framework to quantitatively evaluate trade-offs and balance between sustainability objectives and ecosystem integrity in response to system feedbacks, offering critical insights into reconciling potentially conflicting sustainability goals across multiple scales within socio-ecological systems.

Climate change and land use/land cover (LULC) changes influence streamflow by altering precipitation patterns, evaporation, and hydrological processes. Disentangling their combined effects is critical for effective water management under increasing climatic and environmental pressures. This meta-analysis integrates quantitative and qualitative approaches to assess the impacts of precipitation, temperature, and LULC changes on streamflow using published data sets, multiple linear regression, and Random Forest models. Precipitation emerges as the dominant driver, showing significant variability and a direct linear correlation with streamflow. Temperature impacts are inconsistent, while LULC changes demonstrate nuanced effects. Conversions to agriculture generally increase streamflow, whereas transitions to forests reduce it. Multiple linear regression revealed that precipitation alone explains nearly half of the variance in streamflow, with LULC changes contributing an additional but smaller percentage. In contrast, temperature changes have minimal influence. Variability in LULC conversions correlates with residuals, underscoring diverse impacts across land use types. The Random Forest model, which allows the consideration of non-linear dependencies, achieved R² values of 0.7, confirming precipitation as the most critical predictor, followed by temperature and LULC changes. Including catchment area and climate zone added no significant improvement. These findings highlight the combined importance of precipitation, temperature and LULC changes in shaping streamflow dynamics. While comprehensive, the meta-analysis may overlook local factors such as micro-climate variations or land management practices. The variability in model predictive power underscores the challenge of modeling nonlinear relationships between climate, LULC changes, and streamflow. The results offer critical insights for sustainable water resource management and predictive hydrological modeling.