Nature Geoscience最新文献

Correction to: Nature Geoscience https://doi.org/10.1038/s41561-022-01070-6, published online 5 January 2023.

Marine heatwaves and ocean acidification extreme events are periods during which temperature and acidification reach statistically extreme levels (90th percentile), relative to normal variability, potentially endangering ecosystems. As the threats from marine heatwaves and ocean acidification extreme events grow with climate change, there is need for skilful predictions of events months to years in advance. Previous work has demonstrated that climate models can predict marine heatwaves up to 12 months in advance in key regions, but forecasting of ocean acidification extreme events has been difficult due to the complexity of the processes leading to extremes and sparse observations. Here we use the Community Earth System Model Seasonal-to-Multiyear Large Ensemble to make predictions of marine heatwaves and two forms of ocean acidification extreme events, as defined by anomalies in hydrogen ion concentration and aragonite saturation state. We show that the ensemble skilfully predicts marine heatwaves and ocean acidification extreme events as defined by aragonite saturation state up to 1 year in advance. Predictive skill for ocean acidification extremes as defined by hydrogen ion concentration is lower, probably reflecting mismatch between model and observed state. Skill is highest in the eastern Pacific, reflecting the predictable contribution of El Niño/Southern Oscillation to regional variability. A forecast generated in late 2023 during the 2023–2024 El Niño event finds high likelihood for widespread marine heatwaves and ocean acidification extreme events in 2024.

A two-decade-long accumulation of freshwater in the Arctic Ocean’s Beaufort Gyre has recently started to be released. Here we use satellite observations and model simulations to show that changes in wind regimes and sea ice declines are causing freshwater to accumulate close to the export gateways to the North Atlantic. This emerging buffer zone plays an important role in modulating the propagation of freshwater into the subpolar North Atlantic.

Climate change and disturbance threaten forested ecosystems across the globe. Our ability to predict the future distribution of forests requires understanding the limiting factors for regeneration. Forest canopies buffer against near-surface air temperature and vapour pressure deficit extremes, and ongoing losses of forest canopy from disturbances such as wildfire can exacerbate climate constraints on natural regeneration. Here we combine experimental, empirical and simulation-based evidence to show that soil surface temperatures constrain the low-elevation extent of forests in the western United States. Simulated potential soil surface temperatures predict the position of the low-elevation forest treeline, exhibiting temperature thresholds consistent with field and laboratory studies. High-resolution historical and future surface temperature maps show that 107,000–238,000 km² (13–20%) of currently forested area exceeds the critical thermal threshold for forest regeneration and this area is projected to more than double by 2050. Soil surface temperature is an important physical control on seedling survival at low elevations that will likely be an increasing constraint on the extent of western United States forests as the climate warms.

The Atlantic Meridional Overturning Circulation is the main driver of northward heat transport in the Atlantic Ocean today, setting global climate patterns. Whether global warming has affected the strength of this overturning circulation over the past century is still debated: observational studies suggest that there has been persistent weakening since the mid-twentieth century, whereas climate models systematically simulate a stable circulation. Here, using Earth system and eddy-permitting coupled ocean–sea-ice models, we show that a freshening of the subarctic Atlantic Ocean and weakening of the overturning circulation increase the temperature and salinity of the South Atlantic on a decadal timescale through the propagation of Kelvin and Rossby waves. We also show that accounting for upper-end meltwater input in historical simulations significantly improves the data–model agreement on past changes in the Atlantic Meridional Overturning Circulation, yielding a slowdown of 0.46 sverdrups per decade since 1950. Including estimates of subarctic meltwater input for the coming century suggests that this circulation could be 33% weaker than its anthropogenically unperturbed state under 2 °C of global warming, which could be reached over the coming decade. Such a weakening of the overturning circulation would substantially affect the climate and ecosystems.

Severe air pollution reduces ecosystem carbon assimilation through the vegetation damaging effects of ozone and by altering the climate through aerosol effects, exacerbating global warming. In response, China implemented the Clean Air Action plan in 2013 to reduce anthropogenic emissions. Here we assess the impact of air pollution reductions due to the Clean Air Action plan on net primary productivity (NPP) in China during the period 2014–2020 using multiple measurements, process-based models and machine learning algorithms. The Clean Air Action plan led to a national NPP increase of 26.3 ± 27.9 TgC yr⁻¹, of which 20.1 ± 10.9 TgC yr⁻¹ is attributed to aerosol reductions, driven by both the enhanced light availability as a result of decreased black carbon concentrations and the increased precipitation caused by weakened aerosol climatic effects. The impact of ozone amelioration became more important over time, surpassing the effects of aerosol reduction by 2020, and is expected to drive future NPP recovery. Two machine learning models simulated similar NPP recoveries of 42.8 ± 26.8 TgC yr⁻¹ and 43.4 ± 30.1 TgC yr⁻¹. Our study highlights substantial carbon gains from controlling aerosols and surface ozone, underscoring the co-benefits of regulating air pollution for public health and carbon neutrality in China.

The Palaeocene–Eocene Thermal Maximum, a climate event 56 million years ago, was characterized by rapid carbon release and extensive ocean acidification. However, our understanding of acidification and the evolution of ocean saturation states continues to be hindered by considerable uncertainties, primarily stemming from the limited availability of proxy data. Under such conditions, data assimilation allows for an internally consistent assessment of atmospheric CO₂ changes, ocean acidification and carbonate saturation state during this period. Here, we present a reconstruction of the Palaeocene–Eocene Thermal Maximum carbon cycle perturbation by assimilating seafloor sediment CaCO₃ and sea surface temperature proxy data with simulations from an Earth system model, which includes a comprehensive carbonate system. Our reconstructions indicate a substantial increase in atmospheric CO₂ from 890 ppm (95% credible interval: 680–1,170 ppm) to 1,980 ppm (1,680–2,280 ppm), coupled with a notable decline in pH (0.46 units, ranging from 0.31 to 0.63 units) and surface-water calcite saturation state, decreasing from 10.2 (7.5–12.8) in the pre-event period to 3.8 (2.8–5.1) during the thermal maximum. Carbonate undersaturation intensified substantially in high-latitude surface waters during the Palaeocene–Eocene Thermal Maximum, paralleling the current decline in Arctic aragonite saturation driven by anthropogenic CO₂ emissions.

Assessing compliance with the human-induced warming goal in the Paris Agreement requires transparent, robust and timely metrics. Linearity between increases in atmospheric CO₂ and temperature offers a framework that appears to satisfy these criteria, producing human-induced warming estimates that are at least 30% more certain than alternative methods. Here, for 2023, we estimate humans have caused a global increase of 1.49 ± 0.11 °C relative to a pre-1700 baseline.

Atmospheric aerosol particles are essential for forming clouds and precipitation, thereby influencing Earth’s energy budget, water cycle and climate on regional and global scales. However, the origin of aerosol particles over the Amazon rainforest during the wet season is poorly understood. Earlier studies showed new particle formation in the outflow of deep convective clouds and suggested a downward flux of aerosol particles during precipitation events. Here we use comprehensive aerosol, trace gas and meteorological data from the Amazon Tall Tower Observatory to show that rainfall regularly induces bursts of nanoparticles in the nucleation size range. This can be attributed to rain-related scavenging of larger particles and a corresponding reduction of the condensation sink, along with an ozone injection into the forest canopy, which could increase the oxidation of biogenic volatile organic compounds, especially terpenes, and enhance new particle formation. During and after rainfall, the nucleation particle concentrations directly above the canopy are greater than those higher up. This gradient persists throughout the wet season for the nucleation size range, indicating continuous particle formation within the canopy, a net upward flux of newly formed particles and a paradigm shift in understanding aerosol–cloud–precipitation interactions in the Amazon. Particle bursts provide a plausible explanation for the formation of cloud condensation nuclei, leading to the local formation of green-ocean clouds and precipitation. Our findings suggest that an interplay of a rain-related reduction in the condensation sink, primary emissions of gases, mainly terpenes, and particles from the forest canopy, and convective cloud processing determines the population of cloud condensation nuclei in pristine rainforest air.