Earths Future最新文献

Internal climate variability (ICV) is well-known to mask forced climate change patterns and is thus expected to also impact crop yield trends. To date, a global picture of ICV effect on crop yield projection remains unclear, which inhibits effective adaptation and risk management under climate change. By combining initial condition large ensembles from multiple climate models with machine-learning based crop model emulators, an ensemble of 2002 global maize yield simulations are conducted. The ICV effect is quantified for by the middle and end of 21st century under the business-as-usual scenario. ICV is shown to have significant influence on both the magnitude and sign of future yield change, with relatively higher impact in the top producing countries. The results imply that future yield projections considering relatively limited samples of ICV can be highly misleading as they may, by chance, indicate low yield loss risk in areas which will, instead, be at high risk (or vice versa). Further analysis reveals that the ICV effect is 2.30 ± 0.02 and 1.25 ± 0.03 times larger for yield projections than temperature and precipitation projections, respectively, suggesting an amplification of ICV effect from climate system to agricultural system. This study highlights that crop yield projections are substantially more uncertain than climate projections under the influence of ICV.

Income maps have been extensively used for identifying populations vulnerable to global changes. The frequency and intensity of extreme events are likely to increase in coming years as a result of climate change. In this context, several studies have hypothesized that the economic and social impact of extreme events depend on income. However, to rigorously test this hypothesis, fine-scale spatial income data is needed, compatible with the analysis of extreme climatic events. To produce reliable high-resolution income data, we have developed an innovative machine learning framework, that we applied to produce a European 1 km-gridded data set of per capita disposable income for 2015. This data set was generated by downscaling income data available for more than 120,000 administrative units. Our learning framework showed high accuracy levels, and performed better or equally than other existing approaches used in the literature for downscaling income. It also yielded better results for the estimation of spatial inequality within administrative units. Using SHAP values, we explored the contribution of the model predictors to income predictions and found that, in addition to geographic predictors, distance to public transport or nighttime light intensity were key drivers of income predictions. More broadly, this data set offers an opportunity to explore the relationships between economic inequality and environmental degradation in health, adaptation or urban planning sectors. It can also facilitate the development of future income maps that align with the Shared Socioeconomic Pathways, and ultimately enable the assessment of future climate risks.

Central Asia (CA), a typical arid and semiarid region, has experienced worsening droughts, adversely impacting agricultural production and socioeconomic development. However, the evolution of hydrological droughts in CA remains unclear. Here, we used instrumental streamflow and reanalysis to demonstrate a decline in surface runoff in CA since the 1990s, with 44.6% and 33.2% of the area dominated by reductions in snowmelt and precipitation, respectively. We found that global warming contributes to the long-term decrease in surface runoff, while short-term fluctuations in surface runoff are caused by the El Niño-Southern Oscillation, such as southern CA drying induced by decreasing precipitation during La Niña. We project the future hydrological drought characteristics based on state-of-the-art global hydrological simulations and found increasing duration and severity of hydrological droughts in CA, especially in the Amu Darya basin, and the Caspian Sea East Coast basin. These increasing droughts are exacerbated by higher anthropogenic emissions, posing high-level risks to 39.01% of land area and 35.9% of human population under an extremely high emissions scenario. These findings highlight the need for improved water conservation technologies and concerted development strategies should be considered by national policy makers in this water-scarce and climatically sensitive region.

Numerous studies have highlighted the simultaneous relationship between the Arctic Oscillation (AO) and weather/climate in Asia. However, the stability of the precursor signals in AO for Asian surface air temperature (SAT), which is important for short-term climate prediction, has received little attention. In this study, a strengthened relationship is identified between the late-winter AO and the early spring SAT over North and Northeast Asia (NNA) around the 1990s. During 1990–2022, a positive (negative) phase of AO during late winter is generally followed by significant warming (cooling) anomalies in the NNA during early spring, whereas this relationship is insignificant during 1961–1987. Further result shows a good persistence of the late-winter AO to early spring after the 1990s. Accordingly, the AO exerts a strengthened impact on Mongolian anticyclone and Asian westerly anomalies through modulation of a Rossby wave train that propagates from the Arctic to the NNA in early spring, leading to significant SAT anomalies at NNA. Additionally, the AO-related temperature anomalies intensified in the stratosphere after the 1990s, linking AO and stratospheric polar vortex (SPV). The intensified (weakened) SPV following positive (negative) AO facilitates warming (cooling) anomalies at NNA via downward-propagating Eliassen-Palm fluxes at wave number 1 and circumpolar westerlies in middle and lower troposphere. The seasonal persistence of AO and the strengthened relationship between AO and SPV synergistically enhance the influence of late-winter AO on early spring SAT in the NNA, which might be attributed to the interdecadal changes in background circulation over the Arctic.

Microbial processing of atmospheric nitrogen (N) deposition regulates the retention and mobilization of N in soils, with important implications for water quality. Understanding the links between N deposition, microbial communities, N transformations, and water quality is critical as N deposition shifts toward reduced N and remains persistently high in many regions. Here, we investigated these connections along an elevation transect in the Colorado Front Range. Although rates of N deposition and pools of extractable N increased down the elevation transect, soil microbial communities and N transformation rates did not follow clear elevational patterns. The subalpine microbial community was distinct, corresponding to a high C:N ratio and low pH, while the microbial communities at the lower elevation sites were all very similar. Net nitrification, mineralization, and nitrification potential rates were highest at the Plains (1,700 m) and Montane (2,527 m) sites, suggesting that these ecosystems mobilize N. In contrast, the net immobilization of N observed at the Foothills (1,978 m) and Subalpine (3,015 m) sites suggests that these ecosystems retain N deposition. The contrast in N transformation rates between the plains and foothills, both of which receive elevated N deposition, may be due to spatial heterogeneity not captured in this study and warrants further investigation. Stream N concentrations from the subalpine to the foothills were consistently low, indicating that these soils are currently able to process and retain N deposition, but this may be disrupted if drought, wildfire, or land-use change alter the ability of the soils to retain N.

To achieve the 1.5°C target of the Paris agreement, rapid, sustained, and deep emission reductions are required, which often includes negative emissions through land-based mitigation. However, the effects of future land-use change on climate are often not considered when quantifying the climate-induced impacts on human heat stress and labor capacity. By conducting simulations with three fully coupled Earth System Models, we project the effects of land-use change on heat stress and outdoor labor capacity for two contrasting future land-use scenarios under high-ambition mitigation. Achieving a sustainable land-use scenario with increasing global forest cover instead of an inequality scenario with decreasing forest cover in the Global South causes a global cooling ranging between 0.09°C and 0.35°C across the Earth System Models. However, the effects on human heat stress are less strong, especially over the regions of intense land-use change such as the tropics, where biogeophysical effects on near-surface specific humidity and wind speed counteract the cooling effect under warm extremes. The corresponding influence on outdoor labor capacity is small and inconsistent across the three Earth System Models. These results clearly highlight the importance of land-use change scenarios for achieving global temperature targets while questioning the adaptation potential for reduction in heat stress.

Marine ecosystems provide essential services to the Earth System and society. These ecosystems are threatened by anthropogenic activities and climate change. Climate change increases the risk of passing tipping points; for example, the Atlantic Meridional Overturning Circulation (AMOC) might tip under future global warming leading to additional changes in the climate system. Here, we look at the effect of an AMOC weakening on marine ecosystems by forcing the Community Earth System Model v2 (CESM2) with low (SSP1-2.6) and high (SSP5-8.5) emission scenarios from 2015 to 2100. An additional freshwater flux is added in the North Atlantic to induce an extra weakening of the AMOC. In CESM2, the AMOC weakening has a large impact on phytoplankton biomass and temperature fields through various mechanisms that change the supply of nutrients to the surface ocean. We drive a marine ecosystem model, EcoOcean, with phytoplankton biomass and temperature fields from CESM2. In EcoOcean, we see negative impacts in Total System Biomass (TSB), which are larger for high trophic level organisms. On top of anthropogenic climate change, TSB decreases by −3.78$��\%�$ and −2.03$��\%�$ in SSP1-2.6 and SSP5-8.5, respectively due to the AMOC weakening. However, regionally and for individual groups, the decrease can be as large as −30$��\%�$, showing that an AMOC weakening can be very detrimental for local ecosystems. These results show that marine ecosystems will be under increased threat if the AMOC weakens which might put additional stresses on socio-economic systems that are dependent on marine biodiversity as a food and income source.

This study compared the future global climate zones based on four radiative forcings ranging from low-end (SSP1-2.6) to high-end (SSP5-8.5) using the Köppen-Geiger climate classification. To reduce uncertainties in future projected precipitation and temperature, multimodel projections comprising 25 general circulation models (GCMs) were sourced from the recent Coupled Model Intercomparison Project phase six (CMIP6) and used to create a Multi-Model Ensemble. The changes in historical climate zones on CMIP6 simulations were divided into six periods considering data availability (1954–1964; 1964–1974; 1974–1984; 1984–1994; 1994–2004; and 2004–2014). Furthermore, the climate zone reproducibility of 25 CMIP6 GCMs was compared with the reference data sourced from Global Precipitation Climatology Centre precipitation and Climatic Research Unit temperature. The future climate zones were projected into seven periods using monthly precipitation and surface temperature under four main SSP scenarios. Consequently, the climate variables from GCMs were overestimated compared to the reference data, and the composition of the climate zones was less complex. While temperature discrepancies of 1–2°C may not drastically alter the Köppen-Geiger climate zone classifications, precipitation-based classifications are significantly impacted by the observed errors. Thus, it is crucial to recognize that despite the advancements in GCMs, they still possess limitations in accurately predicting “real” future climate changes. The projected future climate zones are simpler compared to the historical periods across six continents, with tundra and ice caps expected to disappear. This study highlights potential risks by projecting future climate zones based on varying greenhouse gas concentration levels, stressing the importance of using these projections with caution given the inherent uncertainties and limitations of GCMs.

Surge in global population and shift toward animal-based diets have accelerated expansion of livestock production, posing various environmental challenges. It requires inventorying localized, activity-specific, and indicator-extended multidimensional eco-environmental burdens and revealing their transfers within interregional trade to inform holistic livestock production management from both production and consumption sides. Herein, we construct a life cycle framework covering multiple livestock species, feeding regimes, and activities to evaluate nine environmental impacts ending up as human health, ecosystem quality and resource scarcity burdens in Chinese provincial regions. Multi-regional input-output analysis is then conducted to trace transfers of these burdens embedded within trade associated with livestock production. Results indicate that fine particulate matter formation (mainly by livestock housing) and climate change (mainly by enteric fermentation) contribute greater than 60% and 30% to health burdens. Besides for health burdens, for ecosystem burdens primarily caused by housing, and resource burdens mainly aggravated by high on-farm energy use, poultry results in the highest level. The main production regions Shandong, Henan and Sichuan lead from perspectives of both production and consumption-based burdens. Whereas regions with the largest export (Inner Mongolia, 3.87 × 10⁴ DALY for health burdens) or import (Guangdong, 3.92 × 10⁴ DALY for health burdens) do not necessarily bear greatest burdens. This work provides policy instructions in mitigating various eco-environmental burdens imposed by livestock production and promoting sustainable agricultural practices.

Summer heat extremes increasingly co-occur worldwide, posing disastrous impacts on our society and the environment. However, the spatial pattern and underlying mechanisms of concurrent heat extremes remain unclear. We used a statistical framework to estimate the spatial concurrence strength of heat extremes in the Northern Hemisphere and identified their relationships to global warming, atmospheric circulation, and land-atmosphere feedbacks. Concurrent heat extremes over different regions have significantly increased in the Northern Hemisphere from 1950 to 2023. Moreover, heat extremes show strong spatial concurrence strength, and the driving factors vary geographically. Global warming is responsible for long-term increases in the frequency and strength of concurrent heat extremes, with most pronounced impact in tropical regions. In the absence of warming trends, the temporal and spatial variations in concurrent heat extremes are mainly caused by simultaneous high atmospheric pressure controlled by large-scale circulations, particularly in mid-latitude regions. While low soil moisture enhances regional heat extremes through land-atmosphere feedbacks, it plays a minor role in driving concurrent heat extremes alone but can contribute in combination with high-pressure anomalies. Given the ever-increasing risks of heat extremes, our study underscores the importance of identifying the mechanisms of spatially concurrent heat extremes to improve prediction and mitigation of widespread heatwaves and their adverse impacts on socio-economic sustainability and human well-being.