Earths Future最新文献

Dryland ecosystems cover 40% of our planet's land surface, support billions of people, and are responding rapidly to climate and land use change. These expansive systems also dominate core aspects of Earth's climate, storing and exchanging vast amounts of water, carbon, and energy with the atmosphere. Despite their indispensable ecosystem services and high vulnerability to change, drylands are one of the least understood ecosystem types, partly due to challenges studying their heterogeneous landscapes and misconceptions that drylands are unproductive “wastelands.” Consequently, inadequate understanding of dryland processes has resulted in poor model representation and forecasting capacity, hindering decision making for these at-risk ecosystems. NASA satellite resources are increasingly available at the higher resolutions needed to enhance understanding of drylands' heterogeneous spatiotemporal dynamics. NASA's Terrestrial Ecology Program solicited proposals for scoping a multi-year field campaign, of which Adaptation and Response in Drylands (ARID) was one of two scoping studies selected. A primary goal of the scoping study is to gather input from the scientific and data end-user communities on dryland research gaps and data user needs. Here, we provide an overview of the ARID team's community engagement and how it has guided development of our framework. This includes an ARID kickoff meeting with over 300 participants held in October 2023 at the University of Arizona to gather input from data end-users and scientists. We also summarize insights gained from hundreds of follow-up activities, including from a tribal-engagement focused workshop in New Mexico, conference town halls, intensive roundtables, and international engagements.

The spatiotemporal overlap of multiple hazards defines what we call concurrent hazards, which usually cause more severe damage than what an isolated hazard would. Investigations of concurrent hazards at the global scale are limited. Here we first developed a novel criterion system for identifying concurrent hazards and then recognized 1,614 concurrent hazards during 1981–2020 from the 121,214 records including earthquake, storm, landslide, volcanic, wildfire and flood. Sixteen hot spot regions suffering from concurrent hazards were recognized for the first time at the global scale. By comparing two periods, 1981–2000 and 2001–2020, we found that the gross relative impact (economic damage and death) of concurrent hazards has considerably aggravated (6.3–117.0 times) in the past two decades. The low-income regions suffer more prominent increase (mostly 2–3 times of high-income regions), implying the inequitable patterns of concurrent hazard impact due to socioeconomic development. This spatial disparity entails the establishment of multidisciplinary and cross-regional collaborations in mitigating the impact of concurrent hazards.

Scenarios have emerged as valuable tools in managing complex human-natural systems, but the traditional approach of limiting focus on a small number of predetermined scenarios can inadvertently miss consequential dynamics, extremes, and diverse stakeholder impacts. Exploratory modeling approaches have been developed to address these issues by exploring a wide range of possible futures and identifying those that yield consequential vulnerabilities. However, vulnerabilities are typically identified based on aggregate robustness measures that do not take full advantage of the richness of the underlying dynamics in the large ensembles of model simulations and can make it hard to identify key dynamics and/or storylines that can guide planning or further analyses. This study introduces the FRamework for Narrative Storylines and Impact Classification (FRNSIC; pronounced “forensic”): a scenario discovery framework that addresses these challenges by organizing and investigating consequential scenarios using hierarchical classification of diverse outcomes across actors, sectors, and scales, while also aiding in the selection of scenario storylines, based on system dynamics that drive consequential outcomes. We present an application of this framework to the Upper Colorado River Basin, focusing on decadal droughts and their water scarcity implications for the basin's diverse users and its obligations to downstream states through Lake Powell. We show how FRNSIC can explore alternative sets of impact metrics and drought dynamics and use them to identify drought scenario storylines, that can be used to inform future adaptation planning.

A rapidly growing population across mountain regions is pressuring expansion onto steeper slopes, leading to increased exposure of people and their assets to slow-moving landslides. These moving hillslopes can inflict damage to buildings and infrastructure, accelerate with urban alterations, and catastrophically fail with climatic and weather extremes. Yet, systematic estimates of slow-moving landslide exposure and their drivers have been elusive. Here, we present a new global database of 7,764 large (A ≥ 0.1 km²) slow-moving landslides across nine IPCC regions. Using high-resolution human settlement footprint data, we identify 563 inhabited landslides. We estimate that 9% of reported slow-moving landslides are inhabited, in a given basin, and have 12% of their areas occupied by human settlements, on average. We find the density of settlements on unstable slopes decreases in basins more affected by slow-moving landslides, but varies across regions with greater flood exposure. Across most regions, urbanization can be a relevant driver of slow-moving landslide exposure, while steepness and flood exposure have regionally varying influences. In East Asia, slow-moving landslide exposure increases with urbanization, gentler slopes, and less flood exposure. Our findings quantify how disparate knowledge creates uncertainty that undermines an assessment of the drivers of slow-moving landslide exposure in mountain regions, facing a future of rising risk, such as Central Asia, Northeast Africa, and the Tibetan Plateau.

Development patterns and climate change are contributing to increasing flood risk across the United States. Limiting development in floodplains mitigates risk by reducing the assets and population exposed to flooding. Here, we develop two indexes measuring floodplain development for 18,548 communities across the continental United States. We combine land use, impervious surface, and housing data with regulatory flood maps to determine what proportion of new development has taken place in the floodplain. Nationwide from 2001 to 2019, 2.1 million acres of floodplain land were developed, and 844,000 residential properties were built in the floodplain. However, contrary to conventional perceptions of rampant floodplain development, just 26% of communities nationwide have developed in floodplains more than would be expected given the hazard they face. The indexes and the analyses they enable can help guide targeted interventions to improve flood risk management, to explore underlying drivers of flood exposure, and to inform how local-to-federal policy choices can be leveraged to limit hazardous development.

Urban areas have been shown to impact rainfall by altering both its intensity and spatial structure at sub-hourly and sub-kilometer scales. However, there is currently no clear understanding of the precise pattern of change and the mechanisms that drive these changes. Since the hydrological response in urban areas is highly sensitive to such rainfall properties, understanding these changes is critical to improving our ability to assess urban flood risk. We use 7 years of high-resolution weather radar data (4- or 5-min and 1 km) to analyze changes in patterns of rainfall intensity, spatial structure, and storm evolution across eight urban areas within Europe and the United States. The use of the same methodology across the different cities enables a consistent comparison among them. We track convective rainfall events using a storm tracking algorithm and assess changes in rainfall properties in the upwind, center, and downwind regions of each city. We also investigate changes in the frequency of storm initiations, terminations, splitting, and merging. Our results show that urban areas act to intensify rainfall—mostly over them, but sometimes on their peripheries. Overall, larger cities tend to show the largest rainfall enhancements. Our findings highlight that rainfall spatial structure is altered over the urban core; usually resulting in more spatially concentrated rainfall. We also observe increased storm initiations over most cities and increased storm splitting over one. Given that demographic projections show that future urban population will increase, our results point toward an increased future flood risk in growing cities.

The large uncertainties in estimating CH₄ emissions from wetland ecosystems, the leading natural source to the atmosphere, substantially hinder the quantification of the global CH₄ budget. This study used the IBIS-CH₄ (Integrated BIosphere Simulator-Methane) model, a process-based model integrating microbial mechanisms associated with CH₄ production and oxidation processes, to simulate global wetland CH₄ emissions from 2001 to 2020. Initially, we employed the IBIS-CH₄ model to evaluate its performance across 26 diverse wetland sites worldwide. The results showed that the magnitude and seasonality of observed CH₄ fluxes over various wetland sites were well reproduced. We then used this model to estimate the annual global wetland CH₄ emissions from 2001 to 2020, averaging 152.67 Tg CH₄ yr⁻¹, with a range of 135.72–167.57 Tg CH₄ yr⁻¹. The estimated global wetland CH₄ emissions are generally in agreement with the current bottom-up estimates (117–256 Tg CH₄ yr⁻¹) and closely overlap with independent top-down estimates (139–183 Tg CH₄ yr⁻¹). During 2001–2020, the estimated global wetland CH₄ emissions initially showed an increasing trend, followed by a decline. The peak of CH₄ emissions reached in 2010, coinciding with the peak of wetland area. The majority of global wetland CH₄ emissions were concentrated in tropical regions, which exhibited a clear seasonality and had a peak in July. The impact of meteorological factors on wetland CH₄ emissions was greater than that of leaf area index, indicating the importance of soil hydrothermal conditions on wetland CH₄ emissions.

Cyclone Gabrielle passed along the northern coast of Aotearoa New Zealand in February 2023, producing historic rainfall accumulations and impacts. Gabrielle was an ex-tropical cyclone that stalled and re-energised off the north coast, resembling descriptions of worst case scenarios for the northeast of the country. Here we report on a comparison of the actual forecast of the storm against forecasts under conditions representative of a climate without anthropogenic interference and of a climate +2.0°C warmer than pre-industrial (about 1.0°C cooler and warmer than present respectively). We find that regional total rainfall accumulations from a Gabrielle-like storm are about 10% higher because of the historical anthropogenic warming, and will increase by a larger amount under similar future warming. These differences are driven by a 20% (relative to a non-anthropogenic world) to 30% (relative to a +2.0°C world) rise in peak rainfall rates, which in turn is mainly driven by a more temporally concentrated column-integrated moisture flux. The forecast model generates the larger increase for the +2.0°C world through greater precipitation efficiency, reflecting the importance of unresolved precipitation processes in the climate change response of rainfall extremes.

Observations and climate projections suggest a larger increase in tropical cyclone (TC)-induced rainfall than that can be explained by the Clausius-Clapeyron relationship of 7% increase in vapor content for each 1°C degree rise in temperature. However, these studies using diverse data sources and methods over various periods show inconsistencies regarding the location of this increase - whether in the TC inner core or outer regions - and offer differing explanations for the reported trends. This study uses the Pseudo-global warming methodology on simulations of 117 western North Pacific TCs making landfall in Southeast Asia to investigate changes in TC rainfall structure by the end of the century under the SSP2-4.5 and SSP3-7.0 scenarios. Specifically, it tests the sensitivity of changing trends to various analysis methods used in previous studies and identifies the underlying physical mechanisms driving these changes. The findings indicate an amplified increase in rainfall in the TC inner core across all future scenarios, along with potentially decreased rainfall in the outer region under certain future climate conditions. Among TC categories, Supertyphoons exhibit the most significant increased rainfall across future states. Changes in TC primary and secondary circulations, TC structure, and the convergence of heat and moisture are the main factors shaping future rainfall patterns, outweighing the effects of changes in atmospheric and convective stability.

While extreme weather events are often localized, the potential effects on global forests can be far reaching due to the interconnected nature of forest product markets. To better understand these dynamics, this study leverages historical forest-based wind damage data in the United States and applies this information as shocks within a global forest sector outlook model. A large, localized wind event modeled as a shock to the US South creates a one-time increase of 18.7 million m³ from salvage harvest operations, equal to over 4% of national harvest. This crowds out traditional harvest activities, leading to downward pressure on prices in the short run, followed by a persistent effect that could take approximately 25 years to dissipate from markets. Average annual wind damage contributes downward pressure on roundwood prices between 1% and 4% in the United States, and this effect is distributed to other countries. The findings suggest that large, localized shocks reverberate across regions and wood product markets due to their interconnected supply chains and trade patterns, and these impacts have important temporal dynamics. Another key result is that the magnitude of these effects are offset by endogenous market reactions in other markets. In other words, unaffected regions change their harvesting patterns in order to compensate for changes in the availability of fiber, shedding light on the importance of capturing global channels as large shocks materialize in changes in market dynamics internationally. Monte Carlo simulations suggest a wide confidence band on salvage harvest rates and prices.