Earths Future最新文献

{"title":"Heat Extremes Within Hot Summer Seasons Intensify More Than in Average Summers Under Global Warming","authors":"P. Pfleiderer,&nbsp;R. Noyelle,&nbsp;S. Sippel","doi":"10.1029/2026EF008241","DOIUrl":"https://doi.org/10.1029/2026EF008241","url":null,"abstract":"<p>The intensity and persistence of heat extremes increase in a warming climate. Warmer temperatures imply more hot days and longer hot periods per summer. However, beyond summer mean temperature change, changes in the timing of hot days within the season increase the likelihood of long-lasting uninterrupted hot periods in many mid-latitude regions and particularly in Europe. Both changes in atmospheric circulation and soil moisture have been discussed as drivers of heat persistence, yet the precise role of both drivers remains unclear. Here we compare simulated extreme hot summers in current climate, with a corresponding statistical return time of 100 years, to similarly rare summers from pre-industrial climate. The extreme summers were obtained by applying a rare event algorithm to the fully coupled CESM2 climate model; initialized in early June from a wide variety of ocean and land surface initial conditions. Our results demonstrate that the persistence and intensity of temperature anomalies beyond summer mean temperature change (i.e., relative to each climate's climatology) has increased considerably in 100-year summers. These changes are driven by comparatively small changes in soil moisture and its seasonal cycle of summer drying, and corresponding changes in land-atmosphere energy fluxes. These changes in sub-seasonal evolution of heat within hot summers occur despite no change in summer mean temperature anomalies of 100-year summers. The findings imply that the next mega-summer in western Europe likely differs from past summer extremes with more persistent and intense heatwaves during peak summer and in the second half of the season.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EF008241","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Terrestrial Poor Ecohealth Areas Continue to Expand Across Asian Drylands","authors":"Sikandar Ali,&nbsp;Akash Tariq,&nbsp;Fanjiang Zeng,&nbsp;Jordi Sardans,&nbsp;Patient Mindje Kayumba,&nbsp;Zeeshan Ahmed,&nbsp;Josep Peñuelas","doi":"10.1029/2026EF008098","DOIUrl":"https://doi.org/10.1029/2026EF008098","url":null,"abstract":"<p>The 7th Rio declaration principle emphasizes global collaboration to protect and restore ecosystem health. While dryland ecosystem health (EH) remains critical to global sustainability agendas, its long-term regional dynamics remain poorly constrained across the Asian drylands (AD), where land management decisions increasingly shape ecological outcomes. Here, we develop an integrated regional framework that combines vegetation dynamics, soil moisture, land use, and landscape spatial configuration to assess EH trajectories across AD from 2000 to 2020. We found that EH declined across AD until 2012 and partially recovered after 2013. Specifically, areas with poor EH increased by 2.1% (58 Mha), while healthy ecosystems declined by 0.08% and accounted for only 2% (7.9 Mha) of AD by 2020. These regional trends concealed pronounced spatial contrasts, with continued degradation across much of Central Asia and improvement in parts of Dryland East Asia. These divergent trends reflect interacting human land-use and climate pressures. Land-use change affected nearly 4.9% (42.87 Mha) of AD, largely driven by increasing pressure on rangelands and cropland expansion, and reductions in inland water and urbanization. Climatic conditions further contributed to these drivers, as post-2013 warming coincided with increased soil moisture stress in Central Asia, while higher precipitation supported ecohealth recovery in East Asia drylands. These findings show that recent improvements in AD remain limited in extent and unevenly distributed, emphasizing that without region-specific strategies integrating sustainable water resources management, rangeland stewardship, and climate adaptation, poor ecosystem health is likely to continue expanding across large portions of the Asian drylands.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EF008098","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148783658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hot Droughts Increase the Likelihood and Impacts of Abrupt Drought-to-Pluvial Transitions Worldwide","authors":"Yinghao Fu,&nbsp;Haishen Lü,&nbsp;Xiaosheng Qin,&nbsp;Yonghua Zhu,&nbsp;Tingxing Chen,&nbsp;Jiaying Liu,&nbsp;Yingying Xu","doi":"10.1029/2026EF008638","DOIUrl":"https://doi.org/10.1029/2026EF008638","url":null,"abstract":"<p>Hot droughts are intensifying under anthropogenic warming, yet whether extreme heat systematically alters the triggering of abrupt drought-to-pluvial transitions and their downstream impacts remains poorly understood. Here, we identify global drought-to-pluvial abrupt transition (DPAT) events and isolate the influence of antecedent thermal conditions by comparing hot-drought-triggered DPATs (DH-DPATs) with transitions preceded by droughts without concurrent heat. We find that hot drought related transitions display broader hotspots and substantially higher occurrence, with frequency increasing from 66.7% to 316.7% across the interquartile range and a higher conditional transition probability (global mean: 44.89% vs. 38.95%). They also transition faster, sustain longer post drought heavy rainfall, and produce stronger rainfall intensity. Mechanistically, although both event types are associated with enhanced moisture convergence, antecedent heat imposes an additional thermodynamic preconditioning characterized by deeper boundary layers and higher convective instability, making comparable moisture recovery more likely to trigger deep convection. These heat-mediated transitions amplify ecosystem carbon losses, intensifying reductions in gross primary productivity and solar-induced chlorophyll fluorescence by about 43.7% and 26.8%, respectively, with the strongest relative impacts in croplands. They also contribute to increasing population and managed-land exposure. Under future warming, DPATs are projected to shift further toward hot-drought-dominated pathways, with increases in both the contribution and transition likelihood of DH-DPATs. These results highlight a thermodynamic pathway through which hot droughts increase the likelihood and impacts of abrupt drought-to-pluvial transitions worldwide.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EF008638","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recent Temperature and Energy Imbalance Trends Point to Higher Estimates of Future Warming","authors":"G. Gyuleva,&nbsp;E. Fischer,&nbsp;R. Knutti,&nbsp;S. Sippel","doi":"10.1029/2026EF008356","DOIUrl":"https://doi.org/10.1029/2026EF008356","url":null,"abstract":"<p>Climate models simulate a wide range of 21st century warming for a given forcing scenario. Constraining this uncertainty is a central challenge in climate science because of its implications for climate policy and adaptation. The transient climate response (TCR) is a key idealized metric used to quantify future warming in response to an exponentially increasing CO₂ concentration. Climate models span a range of 1.3–3 K for TCR. In attempts to constrain this range, emergent constraints on TCR based on historical temperature trends consistently pointed toward TCR values at the lower end of the range of models. However, recent evidence from trends in the short-wave and long-wave components of Earth's energy imbalance (EEI) at the top-of-atmosphere suggests that models with higher TCR lie closer to the observed EEI trends. Here, we reconcile this discrepancy and provide a revised range for TCR of 1.9–2.6 K. Using a statistical variability-filtering approach, we show that previous temperature-based constraints were biased low due to internal variability, according to our method. We then provide an EEI-based constraint and demonstrate that short- and long-wave EEI trends have a strong potential to constrain future warming, due to the much larger inter-model spread in EEI compared to surface temperature. When considering the recent 2001–2025 period, our results show that both surface temperature and EEI trends support higher TCR values than previously estimated. This result implies that it is increasingly difficult to exclude high climate sensitivity models from the plausible range of future warming.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EF008356","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148753298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Air Quality Forecasts With Observation-Based Scaling of Anthropogenic Emissions for Urban Agglomerations","authors":"Adrien Deroubaix,&nbsp;Guy P. Brasseur,&nbsp;Maria de Fátima Andrade,&nbsp;Alejandro Herman Delgado Peralta,&nbsp;Philipp Franke,&nbsp;Mario Gavidia-Calderon,&nbsp;Judith J. Hoelzemann,&nbsp;Fei Jiang,&nbsp;Inga Labuhn,&nbsp;Laurent Menut,&nbsp;Nilton Rosário,&nbsp;Guillaume Siour,&nbsp;Rita Yuri Ynoue","doi":"10.1029/2026EF008097","DOIUrl":"https://doi.org/10.1029/2026EF008097","url":null,"abstract":"&lt;p&gt;Air quality forecasts are essential to support decision-making in urban agglomerations, where millions of people are exposed to high levels of pollution. However, these forecasts are often limited by uncertainties in anthropogenic emissions, especially in large urban agglomerations where no dedicated operational system exists. In this study, we present an observation-based emission scaling approach aimed at improving operational forecasts. This method derives scaling factors (SF) from the ratio of observed-to-modeled concentrations over the previous week and applies them to anthropogenic emissions in the forecast model, assuming that in large urban agglomerations, biases between observed and modeled concentrations are primarily driven by uncertainties in anthropogenic emission inventories. The method also derives SF for anthropogenic volatile organic compound emissions based on modeled daytime &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;O&lt;/mi&gt;\u0000 &lt;mn&gt;3&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${mathrm{O}}_{3}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; biases under the assumption of a NOx-saturated regime. We implement this method in a chemistry-transport model using a global anthropogenic emission inventory and apply it to São Paulo for two distinct periods (February–April 2023 and July–September 2024). The results show that forecasts of CO, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;NO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{NO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;O&lt;/mi&gt;\u0000 &lt;mn&gt;3&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${mathrm{O}}_{3}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; and &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;SO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{SO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; concentrations are significantly improved within a few weeks. For &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;PM&lt;/mtext&gt;\u0000 &lt;mn&gt;2.5&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{PM}}_{2.5}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; and &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 ","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EF008097","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148753320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can Domain-Informed Design Improve Neural Spatio-Temporal Point Processes for Earthquake Forecasting?","authors":"Weixi Tian,&nbsp;Samuel Stockman,&nbsp;Yongxian Zhang,&nbsp;Maximilian J. Werner","doi":"10.1029/2025EF007318","DOIUrl":"https://doi.org/10.1029/2025EF007318","url":null,"abstract":"<p>Statistical earthquake forecasting models, such as the Epidemic-type Aftershock Sequence (ETAS), embed decades of empirical knowledge and assumptions about earthquake triggering, clustering, and catalog completeness. In contrast, neural spatio-temporal point process (STPP) models often treat seismicity as generic spatiotemporal data without such domain-specific considerations. Using an earthquake catalog from the China Earthquake Networks Center, we investigate how seismology-motivated inputs and training strategies affect the forecasting performance of the Deep Spatio-Temporal Point Process (DeepSTPP). These domain-driven designs include introducing magnitude as an input feature, incorporating an auxiliary training period, extending visible event history, and varying magnitude thresholds. We benchmark DeepSTPP against ETAS and a homogeneous Poisson process to assess relative strengths and limitations. Our results show that certain domain-motivated configurations, such as including an auxiliary period, improve performance, particularly in forecasting immediate aftershocks. However, limitations in the model architecture, including short memory and attention dilution, restrict the benefits of event magnitude and long-range history. The results also show that DeepSTPP remains inferior to ETAS in terms of overall spatiotemporal log-likelihood, although it outperforms ETAS in temporal forecasting at lower magnitude thresholds, specifically for <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>M</mi>\u0000 <mtext>cut</mtext>\u0000 </msub>\u0000 <mo>=</mo>\u0000 <mn>1.4</mn>\u0000 <mo>−</mo>\u0000 <mn>2.8</mn>\u0000 </mrow>\u0000 <annotation> ${M}_{text{cut}}=1.4-2.8$</annotation>\u0000 </semantics></math>. This indicates that DeepSTPP does not yet perform as well as ETAS in the magnitude range most relevant to operational earthquake forecasting <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mfenced>\u0000 <mrow>\u0000 <msub>\u0000 <mi>M</mi>\u0000 <mtext>cut</mtext>\u0000 </msub>\u0000 <mo>≥</mo>\u0000 <mn>3.0</mn>\u0000 </mrow>\u0000 </mfenced>\u0000 </mrow>\u0000 <annotation> $left({M}_{text{cut}}ge 3.0right)$</annotation>\u0000 </semantics></math>. The gains observed at lower thresholds may primarily stem from DeepSTPP's flexibility in handling catalog incompleteness and artifacts. These findings highlight the value of integrating seismological practice into neural model design and point toward future architectures that can fully exploit earthquake catalogs.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EF007318","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148753062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extreme Heat and Rainfall Risk Attributed to Cumulative CO2 Emissions From Fossil Fuel Producers","authors":"Christopher W. Callahan","doi":"10.1029/2026EF008278","DOIUrl":"https://doi.org/10.1029/2026EF008278","url":null,"abstract":"<p>Legal and political approaches to climate accountability require demonstrating that a particular emitter contributed to a climate impact, but quantitative solutions to this attribution challenge remain nascent. This study leverages the proportionality of global warming to cumulative CO₂ emissions to develop statistical models that directly predict extreme climate risk from cumulative emissions. Results show that cumulative emissions from individual actors have increased the probability of extreme heat and rainfall globally; for example, emissions from the United States have increased the risk of recent extreme heat by at least 50% for one-third of the globe. Focusing on specific events demonstrates that emissions from major fossil fuel firms increased the likelihood of the 2021 Pacific Northwest heat wave by 31% and 2022 extreme rainfall in Pakistan by 7%. These results demonstrate a flexible attribution framework grounded in the proportional relationships that inform climate policy, with the potential to guide efficient climate accountability assessments.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EF008278","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148753230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"When Recovery Becomes Infeasible: A Markov Model of Housing Abandonment Risk in Flood-Prone Areas","authors":"R. Negri,&nbsp;S. Xu,&nbsp;C. I. Dragomir,&nbsp;I. Figueira,&nbsp;M. Porfiri,&nbsp;L. Ceferino","doi":"10.1029/2025EF007958","DOIUrl":"https://doi.org/10.1029/2025EF007958","url":null,"abstract":"<p>Floods can undermine long-term community viability by depressing housing markets and triggering property abandonment cycles. This study estimates the risk of housing abandonment by integrating traditional flood-risk frameworks with the concept of sub-replacement—a condition where the cost of repairing a house exceeds its market value. We propose a new risk metric that identifies whether a house enters a sub-replacement condition within a given time horizon. Our stochastic model consists in a discrete-time Markov process that incorporates flood hazard, housing exposure, physical vulnerability, and housing market dynamics. We apply the model to two U.S. communities: Pascagoula, Mississippi, and McGregor, Florida. These two communities exhibit similar flood hazard, exposure, and building vulnerability, but markedly different housing market conditions. Despite comparable Average Annual Losses (AAL), the number of houses expected to experience sub-replacement within the next three decades is one order of magnitude larger in Pascagoula than in McGregor. We also find that the FEMA 50% rule—which mandates elevation when repair costs exceed 50% of a home's market value—reduces AAL by approximately 70%, but increases sub-replacement risk in areas with depressed housing markets. This risk is especially concerning in Pascagoula, where lower housing prices increase the number of houses expected to enter sub-replacement in the next three decades by a factor of eight. Our findings show that incorporating housing market conditions into flood risk analysis is important for anticipating long-term recovery trajectories and prevent downward spirals of disinvestment and population loss.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EF007958","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148942488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Green's Function Approach to Black Carbon: Ensembles of Policy Analysis in Southeast Asia","authors":"Lyssa M. Freese,&nbsp;Cecilia Han Springer,&nbsp;Sebastian D. Eastham,&nbsp;Noelle E. Selin","doi":"10.1029/2025EF007851","DOIUrl":"https://doi.org/10.1029/2025EF007851","url":null,"abstract":"<p>Multi-criteria decision-making requires evaluating policies impact on multiple factors, including environmental ones, which can be a computationally prohibitive exercise. Here, we diagnose Green's functions from a chemical transport model, establishing an approach that allows users to evaluate the transport of black carbon across large ensembles of scenarios with low computational cost. We use this approach to evaluate the impact of early retirement scenarios for coal plants in four countries in Southeast Asia. We assess the impacts that individual plants and scenarios have on both black carbon and <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mtext>CO</mtext>\u0000 <mn>2</mn>\u0000 </msub>\u0000 </mrow>\u0000 <annotation> ${text{CO}}_{2}$</annotation>\u0000 </semantics></math> concentrations and their temperature impacts. We show that groups of 30 of the 367 plants are responsible for 19.4% of the increase in black carbon concentration per megawatt of energy produced in the region, and 17.8% of the temperature increase per megawatt of energy produced in the region. Thus these plants could be prioritized for early closure to obtain the greatest benefits for pollution and temperature in terms of the plants' capacity.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EF007851","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148753269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating Fire Indices for Fire Ignition and Spread Rate in the Western United States","authors":"B. Wang,&nbsp;A. P. Williams,&nbsp;D. Entekhabi,&nbsp;G. D. Madakumbura,&nbsp;D. Lettenmaier,&nbsp;J. K. Balch,&nbsp;S. Rahimi,&nbsp;L. Huang,&nbsp;A. Hall","doi":"10.1029/2025EF007652","DOIUrl":"https://doi.org/10.1029/2025EF007652","url":null,"abstract":"<p>Wildfires are complex events that are challenging to model. Researchers and land managers often rely on fire indices as a proxy of fire risk in operational forecasts and future projections. However, in the scientific literature, the choice of which fire index to use is often arbitrary and not tied to specific fire behaviors. Here, we provide a comprehensive evaluation of 21 hydrometeorological variables and fire indices based on their ability to represent daily ignition probability and spread rate in the western United States. Hydrometeorological variables like saturation vapor pressure (E_S) and vapor pressure deficit (VPD) perform the best and most consistently at representing fire ignition probability across regions and vegetation types. Water-balance-based indices like 1,000-hr dead fuel moisture (FM1000) and the Keetch-Byram Drought Index (KBDI) are best at representing ignition probability in forests. In contrast, indices like the Hot-Dry-Windy index (HDW) best represent fire spread rates, especially for non-forest fires, while indices from the National Fire Danger Rating System are best for forest fire spread. Partitioning the skill of variables/indices into contributions from capturing seasonality and anomalies, ignitions are distributed based on the seasonal cycles, while seasonality and anomalies are comparably important for spread rate. We demonstrate that computational complexity does not always result in better fire variables/indices, and that distinct sets of variables/indices are needed to represent different aspects of fire behavior, emphasizing the importance of making careful and justifiable selections of fire variables/indices.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EF007652","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148752934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}