Earths Future最新文献

An accurate quantification of global methane sources and sinks is imperative for assessing realistic pathways to mitigate climate change. A key challenge of quantifying the Global Methane Budget (Saunois et al., 2020, https://doi.org/10.5194/essd-12-1561-2020) is the lack of consistency in uncertainties between sectors. Here we provide a new perspective on bottom-up (BU) and top-down (TD) methane uncertainties by using an expert opinion analysis based on a questionnaire conducted in 2021. Expectedly, experts rank highest uncertainty and lowest confidence levels in the Global Methane Budget related to natural sources in BU budgets. Here, we further reveal specific uncertainty types and introduce a ranking system for uncertainties in each sector. We find that natural source uncertainty is related particularly to driver data uncertainty in freshwater, vegetation, and coastal/ocean sources, as well as parameter uncertainty in wetland models. Reducing uncertainties, most notably in aquatic and wetland sources will help balance future BU and TD global methane budgets. We suggest a new methane source partitioning over gradients of human disturbance and demonstrate that 76.3% (75.8%–79.4%) or 561 (443–700) Tg CH₄ yr⁻¹ of global emissions can be attributed to moderately impacted, man-made, artificial, or fully anthropogenic sources and 23.7% (20.6%–24.2%) or 174 (115–223) Tg CH₄ yr⁻¹ to natural and low impacted methane sources. Finally, we identify current research gaps and provide a plan of action to reduce current uncertainties in the Global Methane Budget.

Lake-effect snow (LES) storms, characterized by heavy convective precipitation downwind of large lakes, pose significant coastal hazards with severe socioeconomic consequences in vulnerable areas. In this study, we investigate how devastating LES storms could evolve in the future by employing a storyline approach, using the LES storm that occurred over Buffalo, New York, in November 2022 as an example. Using a Pseudo-Global Warming method with a fully three-dimensional two-way coupled lake-land-atmosphere modeling system at a cloud-resolving 4 km resolution, we show a 14% increase in storm precipitation under the end-century warming. This increase in precipitation is accompanied by a transition in the precipitation form from predominantly snowfall to nearly equal parts snowfall and rainfall. Through additional simulations with isolated atmospheric and lake warming, we discerned that the warmer lake contributes to increased storm precipitation through enhanced evaporation while the warmer atmosphere contributes to the increase in the storm's rainfall, at the expense of snowfall. More importantly, this shift from snowfall to rainfall was found to nearly double the area experiencing another winter hazard, Rain-on-Snow. Our study provides a plausible future storyline for the Buffalo LES storm, focusing on understanding the intricate interplay between atmospheric and lake warming in shaping the future dynamics of LES storms. It emphasizes the importance of accurately capturing the changing lake-atmosphere dynamics during LES storms under future warming.

Grasslands are one of the most common land-cover types, providing important ecosystem services globally, yet few studies have examined grassland critical-zone functioning throughout hillslopes. This study characterised a coastal grassland over a small hillslope at Point Reyes National Seashore, California, using multidisciplinary techniques, combining remotely-sensed, geophysical, plant, and soil measurements. Clustering techniques delineated the study area into four landscape zones, up-, mid-, and down-slope, and a bordering riparian ecotone, which had distinct environmental properties that varied spatially across the site, with depth, and time. Soil moisture increased with depth and down slope towards a bordering riparian zone, and co-varied with soil CO₂ flux rates both spatially and temporally. This highlighted three distinct controls of soil moisture on soil respiration: CO₂ fluxes were inhibited by high moisture content in the down-slope during the wet winter months, and converged across landscape positions in the dry summer months, while also displaying post-rain pulses. The normalised difference vegetation index (NDVI) ranged from 0.32 (September)–0.80 (April) and correlated positively with soil moisture and aboveground biomass, moving down slope. Yet, NDVI, aboveground biomass, and soil moisture were not correlated to soil organic carbon (SOC) content (0.4%–4.5%), which was highest in the mid-slope. The SOC content may instead be linked to shifts in dominant grassland species and their rhizosphere properties with landscape position. This multidisciplinary characterisation highlighted significant heterogeneity in grassland properties with landscape position, and demonstrated an approach that could be used to characterise other critical-zone environments on hillslopes.

Earth system models are powerful tools to simulate the climate response to hypothetical climate intervention strategies, such as stratospheric aerosol injection (SAI). Recent simulations of SAI implement a tool from control theory, called a controller, to determine the quantity of aerosol to inject into the stratosphere to reach or maintain specified global temperature targets, such as limiting global warming to 1.5°C above pre-industrial temperatures. This work explores how internal (unforced) climate variability can impact controller-determined injection amounts using the Assessing Responses and Impacts of Solar climate intervention on the Earth system with Stratospheric Aerosol Injection (ARISE-SAI) simulations. Since the ARISE-SAI controller determines injection amounts by comparing global annual-mean surface temperature to predetermined temperature targets, internal variability that impacts temperature can impact the total injection amount as well. Using an offline version of the ARISE-SAI controller and data from Earth system model simulations, we quantify how internal climate variability and volcanic eruptions impact injection amounts. While idealized, this approach allows for the investigation of a large variety of climate states without additional simulations and can be used to attribute controller sensitivities to specific modes of internal variability.

Predicting flood event classes aids in the comprehensive investigation of flood behavior dynamics and supports flood early warning and emergency plan development. Existing studies have mainly focused on historical flood event classification and the prediction of flood hydrographs or certain metrics (e.g., magnitude and timing) but have not focused on predicting flood event classes. Our study proposes a new approach for predicting flood event classes based on the class membership functions of flood regime metrics and hydrological modeling. The approach is validated using 1446 unimpacted flood events in 68 headstream catchments widely distributed across China. The new approach performs well, with class hit rates of 68.3% ± 0.4% for all events; 65.8% ± 0.6%, 56.8% ± 0.9%, and 69.5% ± 0.9% for the small, moderate and high spike flood event classes, respectively; and 82.5% ± 1.2% and 75.4% ± 1.1% for the moderate and high dumpy flood event classes, respectively. Furthermore, it performs better in the basins of northern China than in those of southern China, particularly for the small spike flood event class in the Songliao and Yellow River Basins, with hit rates of 80.0% ± 3.2% and 78.8% ± 3.2%, respectively. Our results indicate that the new approach will help improve the prediction performance of flood events and their corresponding classes, and provide deep insights into the comprehensive dynamic patterns of flood events for early warning and control management.

Tropical cyclones are often accompanied by large amount of precipitation potentially impacting stream hydrochemistry. Global warming is altering typhoon disturbance regime. Little is known about how cyclone changes, especially cyclone-frequency reduction may affect stream hydrochemistry. In this study, we compared water and nutrient input via precipitation and output via streamflow between a frequent-typhoon period (2013–2017), with 1.2 typhoon yr⁻¹, and a no-typhoon period (2018–2022) at a long-term monitoring site, the Fushan Experimental Forest of Taiwan. Precipitation and streamflow quantities were not different between the two periods because typhoons increased the fluctuation but not the mean of monthly precipitation in the major typhoon months (July–September). Inputs of Mg²⁺, NO₃⁻, and SO₄²⁻ via precipitation were greater in the frequent-typhoon period than the no-typhoon period while inputs of other ions were not different between the two periods. Only the output of Mg²⁺ was different between the two periods, greater in the frequent-typhoon period. Output/input ratio of NO₃⁻ was greater in the no-typhoon period than the frequent-typhoon period despite the greater input in the frequent-typhoon period, while no differences were found for others. Increases in mineralization rates due to warming is suggested to be the cause of the greater NO₃⁻ output/input ratio during the no-typhoon period. Relationships between stream discharge and ion export were similar between the two periods both with and without removing typhoon events. The limited variation in hydrochemistry between periods of contrasting cyclone activities suggests high resilience of the undisturbed subtropical forests to changes in cyclone frequency at the decadal scale.

Ecosystem water use efficiency (WUE) is a crucial parameter for understanding the interaction between carbon and water cycles. However, the spatio–temporal evolution and drivers of WUE remain unclear. This study utilized global annual scale global land surface satellite gross primary productivity and evapotranspiration data from 1982 to 2018 to estimate WUE and analyze its spatio–temporal characteristics. Additionally, the study investigated the response of WUE changes to five environmental factors (precipitation [PRE], soil moisture, temperature [TEM], palmer drought severity index, and vapor pressure deficit [VPD]) on WUE changes using partial correlation and structural equation modeling. The results suggested that the global annual WUE increased markedly over the study period, at an average rate of 0.0016 gC m⁻² mm⁻¹ H₂O year⁻¹. In contrast to the existing knowledge on the drivers of WUE change, climate change was found to have a larger contribution to WUE changes at the global and regional scales, especially in terms of TEM and VPD. A positive correlation between TEM and WUE was observed, but extreme TEM could lead to a decrease in WUE. VPD had the most significant direct effect on WUE, and its negative effect offset the positive influence of TEM especially in hyper-arid, semi-arid, and arid regions. These findings offer new insights into the impact of VPD and global warming on WUE.

Around 60% of households in Texas currently rely on electricity for space heating. As decarbonization efforts increase, non-electrified households could adopt electric heat pumps, significantly increasing peak (highest) electricity demand in winter. Simultaneously, anthropogenic climate change is expected to increase temperatures, the potential for summer heat waves, and associated electricity demand for cooling. Uncertainty regarding the timing and magnitude of these concurrent changes raises questions about how they will jointly affect the seasonality of peak demand, firm capacity requirements, and grid reliability. This study investigates the net effects of residential space heating electrification and climate change on long-term demand patterns and load shedding potential, using climate change projections, a predictive load model, and a direct current optimal power flow (DCOPF) model of the Texas grid. Results show that full electrification of residential space heating by replacing existing fossil fuel use with higher efficiency heat pumps could significantly improve reliability under hotter futures. Less efficient heat pumps may result in more severe winter peaking events and increased reliability risks. As heating electrification intensifies, system planners will need to balance the potential for greater resource adequacy risk caused by shifts in seasonal peaking behavior alongside the benefits (improved efficiency and reductions in emissions).

Stratospheric aerosol injection (SAI) has been proposed as a potential method for mitigating risks and impacts associated with anthropogenic climate change. One such risk is widespread permafrost thaw and associated carbon release. While permafrost has been shown to stabilize under different SAI scenarios, natural variability may mask this forced response and make it difficult to detect if and when SAI is stabilizing permafrost. Here we use the 10-member ensemble from the ARISE-SAI-1.5 simulations to assess the spread in projected active layer depth and permafrost temperature across boreal permafrost soils and specifically in four peatland and Yedoma regions. The forced response in active layer depth and permafrost temperature quickly diverges between an SAI and non-SAI world, but individual ensemble members overlap for several years following SAI deployment. We find that, due to projected permafrost variability, it may take more than a decade of SAI deployment to detect the effects of SAI on permafrost temperature and almost 30 years to detect its effects on active layer depth. Not only does natural variability make it more difficult to detect SAI's influence, it could also affect the likelihood of reaching a permafrost tipping point. In some realizations, SAI fails to prevent a local tipping point that is also reached in a non-SAI world. Our results underscore the importance of accounting for natural variability in assessments of SAI's potential influence on the climate system.

Marine heatwave (MHW), a prolonged period of anomalously warm seawater, has a catastrophic repercussion on marine ecosystems. With global warming, MHWs have become increasingly frequent, intense, and prolonged. To avoid irreversible damages from such extreme events, net-zero carbon emissions by the 2050s, called carbon neutrality, were proposed. Here, we evaluate the impact of carbon neutrality on MHWs in the late 21st century using multi-model projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathway (SSP) 1–1.9 and SSP3-7.0 scenarios. It is found that if the current regional rivalry over carbon emissions continues (i.e., SSP3-7.0), the MHWs in the late 21st century will become stronger and longer than historical ones, especially in the western boundary current and equatorial current regions. Approximately 68% of the global ocean will be exposed to permanent MHWs, regionally 93% in the Indian Ocean, 76% in the Pacific Ocean, 68% in the Atlantic Ocean, 65% in the Coastal Ocean, and 48% in the Southern Ocean. Such MHWs can be significantly reduced by achieving carbon neutrality (i.e., SSP1-1.9). In particular, the spatial proportion of the ocean exposed to permanent MHWs can be reduced to as low as 0.02%–0.07%, depending on the regions. This result underscores the critical importance of ongoing efforts to achieve net-zero carbon emissions to reduce the potential ecological risks induced by extreme MHWs.