Earths Future最新文献

{"title":"Future Extreme Climate Events Threaten Alpine and Subalpine Woody Plants in China","authors":"Yongru Wu,&nbsp;Jian Shen,&nbsp;David C. Deane,&nbsp;Haibin Yu,&nbsp;Fangyuan Yu,&nbsp;Xuerong Wang,&nbsp;Zheng Cao,&nbsp;Rong Yu,&nbsp;Fuan Xiao,&nbsp;Tiejun Wang,&nbsp;Zhifeng Wu","doi":"10.1029/2024EF005147","DOIUrl":"https://doi.org/10.1029/2024EF005147","url":null,"abstract":"<p>Increases in the frequency, intensity, and duration of extreme climate events (ECEs) are already impacting ecosystems, with many of the strongest effects associated with high-elevation areas. Most research on the ecological impacts of climate change has focused on climatic averages, which might differ from ECEs. <i>Rhododendron</i>, a diverse genus of alpine and subalpine woody plant, plays a crucial role in ecosystem stability and biodiversity in the biodiversity hotspots of the Himalayas and Hengduan Mountains. Here, we compared the predicted impacts of average climate with those including ECEs on 189 <i>Rhododendron</i> species in China for the historical period (1981–2010) and the future period (2071–2100) under two emissions scenarios (SSP2-4.5 and SSP5-8.5). We analyzed changes in suitable habitat and patterns of species richness, weighted endemism, and phylogenetic diversity, identifying areas of coinciding high-risk as priority conservation areas. Inclusion of ECEs altered the projected areas of suitable habitat across all species from an increase of over 3% to a decrease exceeding 10%, with the distribution of most <i>Rhododendron</i> species strongly influenced by extremes of drought and high temperatures. We found fewer than 18% of high-risk areas of diversity loss were currently protected, with priority conservation areas mainly located in the Daxue, Daliang, Wumeng, and Jade Dragon Snow Mountains, as well as in the Nyingchi. We suggest inclusion of ECEs is critical when projecting changes in alpine and subalpine species distributions for effective conservation planning for climate change.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"13 1","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF005147","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143110908","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":"Quantifying the Impact of Climate Change and Forest Management on Swedish Forest Ecosystems Using the Dynamic Vegetation Model LPJ-GUESS","authors":"John Bergkvist,&nbsp;Fredrik Lagergren,&nbsp;Md. Rafikul Islam,&nbsp;David Wårlind,&nbsp;Paul A. Miller,&nbsp;Maj-Lena Finnander Linderson,&nbsp;Mats Lindeskog,&nbsp;Anna Maria Jönsson","doi":"10.1029/2024EF004662","DOIUrl":"https://doi.org/10.1029/2024EF004662","url":null,"abstract":"<p>Boreal and temperate forests are undergoing structural, compositional and functional changes in response to increasing temperatures, changes in precipitation, and rising CO₂, but the extent of the changes in forests will also depend on current and future forest management. This study utilized the dynamic vegetation model LPJ-GUESS enabled with forest management (version 4.1.2, rev11016) to simulate changes in forest ecosystem functioning and supply of ecosystem services in Sweden. We compared three alternative forest policy scenarios: Business As Usual, with no change in the proportion of forest types within landscapes; Adaptation and Resistance, with an increased area of mixed stands; and EU-Policy, with a focus on conservation and reduced management intensity. LPJ-GUESS was forced with climate data derived from an ensemble of three earth system models to study long-term implications of a low (SSP1-2.6), a high (SSP3-7.0), and a very high (SSP5-8.5) emissions scenario. Increases in net primary production varied between 4% and 8% in SSP1-2.6, 21%–25% in SSP3-7.0 and 25%–29% in SSP5-8.5 across all three forest policy scenarios, when comparing 2081–2100 to 2001–2020. Increased net primary production was mediated by a higher soil nitrogen availability and increased water use efficiency in the higher emission scenarios SSP3-7.0 and SSP5-8.5. Soil carbon storage showed small but significant decreases in SSP3-7.0 and in SSP5-8.5. Our results highlight differences in the predisposition to storm damage among forest policy scenarios, which were most pronounced in southern Sweden, with increases of 61%–76% in Business-As-Usual, 4%–11% in Adaptation and Resistance, and decreases of 7%–12% in EU-Policy when comparing 2081–2100 to 2001–2020.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"13 1","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004662","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120457","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":"Statistical Distribution of Urban Area Reveals a Converging Trend of Global Urban Land Expansion","authors":"Shengjie Hu,&nbsp;Zhenlei Yang,&nbsp;Sergio Andres Galindo Torres,&nbsp;Zipeng Wang,&nbsp;Haoying Han,&nbsp;Yoshihide Wada,&nbsp;Thomas Cherico Wanger,&nbsp;Ling Li","doi":"10.1029/2024EF005130","DOIUrl":"https://doi.org/10.1029/2024EF005130","url":null,"abstract":"<p>Urban land expansion is a major driver of many environmental and societal changes that challenge human well-being and sustainable development, but its evolutionary process and dynamics are neither clear nor well-integrated into urban science quantitatively. We analyzed the global urban extent data based on nighttime lights to examine the statistical distribution of urban land area at the global scale, and in 13 regions and countries over 29 years. The results reveal a converging temporal trend in urban land expansion from subnational to global scales, characterized by a coherent shift of urban area distribution from an initial power law toward an exponential distribution. This trend is well captured by a unified mathematical model based on the shifted power law distribution function and is reflected in the gradual predominance of medium-size cities over small-size cities in the configuration of urban systems across the world. The shift of urban area distributions bears the consequence of reduced urban system stability and resilience, and can be linked to increasing exposure of urban populations to extreme heat events and air pollution. These changes are likely to be driven by the increasing influence of external economies of scale associated with globalization. The findings challenge the status quo of land urbanization practices and emphasize the importance of medium-size cities in urban planning.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"13 1","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF005130","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143119272","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":"Global Predictability of Marine Heatwave Induced Rapid Intensification of Tropical Cyclones","authors":"Soheil Radfar,&nbsp;Ehsan Foroumandi,&nbsp;Hamed Moftakhari,&nbsp;Hamid Moradkhani,&nbsp;Gregory R. Foltz,&nbsp;Alex Sen Gupta","doi":"10.1029/2024EF004935","DOIUrl":"https://doi.org/10.1029/2024EF004935","url":null,"abstract":"<p>Prediction of the rapid intensification (RI) of tropical cyclones (TCs) is crucial for improving disaster preparedness against storm hazards. These events can cause extensive damage to coastal areas if occurring close to landfall. Available models struggle to provide accurate RI estimates due to the complexity of underlying physical mechanisms. This study provides new insights into the prediction of a subset of rapidly intensifying TCs influenced by prolonged ocean warming events known as marine heatwaves (MHWs). MHWs could provide sufficient energy to supercharge TCs. Preconditioning by MHW led to RI of recent destructive TCs, Otis (2023), Doksuri (2023), and Ian (2022), with economic losses exceeding $150 billion. Here, we analyze the TC best track and sea surface temperature data from 1981 to 2023 to identify hotspot regions for compound events, where MHWs and RI of tropical cyclones occur concurrently or in succession. Building upon this, we propose an ensemble machine learning model for RI forecasting based on storm and MHW characteristics. This approach is particularly valuable as RI forecast errors are typically largest in favorable environments, such as those created by MHWs. Our study offers insight into predicting MHW TCs, which have been shown to be stronger TCs with potentially higher destructive power. Here, we show that using MHW predictors instead of the conventional method of using sea surface temperature reduces the false alarm rate by 30%. Overall, our findings contribute to coastal hazard risk awareness amidst unprecedented climate warming causing more frequent MHWs.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 12","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004935","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118946","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":"Detecting, Attributing, and Projecting Global Marine Ecosystem and Fisheries Change: FishMIP 2.0","authors":"Julia L. Blanchard,&nbsp;Camilla Novaglio,&nbsp;Olivier Maury,&nbsp;Cheryl S. Harrison,&nbsp;Colleen M. Petrik,&nbsp;Denisse Fierro-Arcos,&nbsp;Kelly Ortega-Cisneros,&nbsp;Andrea Bryndum-Buchholz,&nbsp;Tyler D. Eddy,&nbsp;Ryan Heneghan,&nbsp;Kelsey Roberts,&nbsp;Jacob Schewe,&nbsp;Daniele Bianchi,&nbsp;Jerome Guiet,&nbsp;P. Daniel van Denderen,&nbsp;Juliano Palacios-Abrantes,&nbsp;Xiao Liu,&nbsp;Charles A. Stock,&nbsp;Yannick Rousseau,&nbsp;Matthias Büchner,&nbsp;Ezekiel O. Adekoya,&nbsp;Cathy Bulman,&nbsp;William Cheung,&nbsp;Villy Christensen,&nbsp;Marta Coll,&nbsp;Leonardo Capitani,&nbsp;Samik Datta,&nbsp;Elizabeth A. Fulton,&nbsp;Alba Fuster,&nbsp;Victoria Garza,&nbsp;Matthieu Lengaigne,&nbsp;Max Lindmark,&nbsp;Kieran Murphy,&nbsp;Jazel Ouled-Cheikh,&nbsp;Sowdamini S. Prasad,&nbsp;Ricardo Oliveros-Ramos,&nbsp;Jonathan C. Reum,&nbsp;Nina Rynne,&nbsp;Kim J. N. Scherrer,&nbsp;Yunne-Jai Shin,&nbsp;Jeroen Steenbeek,&nbsp;Phoebe Woodworth-Jefcoats,&nbsp;Yan-Lun Wu,&nbsp;Derek P. Tittensor","doi":"10.1029/2023EF004402","DOIUrl":"https://doi.org/10.1029/2023EF004402","url":null,"abstract":"<p>There is an urgent need for models that can robustly detect past and project future ecosystem changes and risks to the services that they provide to people. The Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) was established to develop model ensembles for projecting long-term impacts of climate change on fisheries and marine ecosystems while informing policy at spatio-temporal scales relevant to the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) framework. While contributing FishMIP models have improved over time, large uncertainties in projections remain, particularly in coastal and shelf seas where most of the world's fisheries occur. Furthermore, previous FishMIP climate impact projections have been limited by a lack of global standardized historical fishing data, low resolution of coastal processes, and uneven capabilities across the FishMIP community to dynamically model fisheries. These features are needed to evaluate how reliably the FishMIP ensemble captures past ecosystem states - a crucial step for building confidence in future projections. To address these issues, we have developed FishMIP 2.0 comprising a two-track framework for: (a) Model evaluation and attribution of past changes and (b) future climate and socioeconomic scenario projections. Key advances include improved historical climate forcing, which captures oceanographic features not previously resolved, and standardized global fishing forcing to test fishing effects systematically across models. FishMIP 2.0 is a crucial step toward a detection and attribution framework for changing marine ecosystems and toward enhanced policy relevance through increased confidence in future ensemble projections. Our results will help elucidate pathways toward achieving sustainable development goals.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 12","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023EF004402","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142868794","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":"Vegetation Greening Mitigates the Impacts of Increasing Extreme Rainfall on Runoff Events","authors":"Darren L. Ficklin,&nbsp;Danielle Touma,&nbsp;Benjamin I. Cook,&nbsp;Scott M. Robeson,&nbsp;Taehee Hwang,&nbsp;Jacob Scheff,&nbsp;A. Park Williams,&nbsp;Harper Watson,&nbsp;Ben Livneh,&nbsp;Mari R. Tye,&nbsp;Lixin Wang","doi":"10.1029/2024EF004661","DOIUrl":"https://doi.org/10.1029/2024EF004661","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>Future flood risk assessment has primarily focused on heavy rainfall as the main driver, with the assumption that projected increases in extreme rain events will lead to subsequent flooding. However, the presence of and changes in vegetation have long been known to influence the relationship between rainfall and runoff. Here, we extract historical (1850–1880) and projected (2070–2100) daily extreme rainfall events, the corresponding runoff, and antecedent conditions simulated in a prominent large Earth system model ensemble to examine the shifting extreme rainfall and runoff relationship. Even with widespread projected increases in the magnitude (78% of the land surface) and number (72%) of extreme rainfall events, we find projected declines in event-based runoff ratio (runoff/rainfall) for a majority (57%) of the Earth surface. Runoff ratio declines are linked with decreases in antecedent soil water driven by greater transpiration and canopy evaporation (both linked to vegetation greening) compared to areas with runoff ratio increases. Using a machine learning regression tree approach, we find that changes in canopy evaporation is the most important variable related to changes in antecedent soil water content in areas of decreased runoff ratios (with minimal changes in antecedent rainfall) while antecedent ground evaporation is the most important variable in areas of increased runoff ratios. Our results suggest that simulated interactions between vegetation greening, increasing evaporative demand, and antecedent soil drying are projected to diminish runoff associated with extreme rainfall events, with important implications for society.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 12","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004661","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861874","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":"National Forest Restoration Projects in China: Cost-Efficiency, and Trade-Off Between Carbon Sequestration and Water Consumption","authors":"Jiehao Zhang,&nbsp;Yulong Zhang,&nbsp;Xia Wang,&nbsp;Tiehu He,&nbsp;Huijuan Xia,&nbsp;Kerong Zhang,&nbsp;Quanfa Zhang","doi":"10.1029/2024EF004976","DOIUrl":"https://doi.org/10.1029/2024EF004976","url":null,"abstract":"<p>International initiatives, such as the Bonn Challenge, Trillion Tree Campaign, New York Declaration on Forests, and United Nations Decade on Ecosystem Restoration, have set ambitious targets for forest restoration. However, the effectiveness and cost-efficiency of large-scale forest restoration projects (FRP) in different climatic zones, and the trade-off between carbon sequestration and water consumption caused by FRP are poorly understood. Here, we conducted a comprehensive examination of 2,778 counties in China, where the world's most ambitious FRP was executed during the past two decades. Results showed that, on average, each square kilometer of FRP yielded an additional 0.6 square kilometers of forests and contributed an extra 1354.9 tC to forest carbon storage, with the aridity index emerging as a key influencer. The actual expenditure incurred per ton of increased forest carbon storage amounted to approximately 118.9 USD in average, with the lowest in Southwest at 50.9 USD. The expansion of forest cover and enhanced biomass storage led to a notable increase in water consumption, and the trade-off was particularly pronounced in arid regions. Our study provides empirical evidence that FRP is an effective and cost-efficient climate change mitigation strategy for humid climate zones under current carbon prices. However, FRP is not cost-efficient in semi-arid and arid regions. These findings have significant implications for global forest restoration endeavors and formulating sound climate change mitigation policies.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 12","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004976","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869000","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":"Pan-Arctic Assessment of Coastal Settlements and Infrastructure Vulnerable to Coastal Erosion, Sea-Level Rise, and Permafrost Thaw","authors":"Rodrigue Tanguy,&nbsp;Annett Bartsch,&nbsp;Ingmar Nitze,&nbsp;Anna Irrgang,&nbsp;Pia Petzold,&nbsp;Barbara Widhalm,&nbsp;Clemens von Baeckmann,&nbsp;Julia Boike,&nbsp;Julia Martin,&nbsp;Aleksandra Efimova,&nbsp;Gonçalo Vieira,&nbsp;Dustin Whalen,&nbsp;Birgit Heim,&nbsp;Mareike Wieczorek,&nbsp;Guido Grosse","doi":"10.1029/2024EF005013","DOIUrl":"https://doi.org/10.1029/2024EF005013","url":null,"abstract":"<p>This study assesses the vulnerability of Arctic coastal settlements and infrastructure to coastal erosion, Sea-Level Rise (SLR) and permafrost warming. For the first time, we characterize coastline retreat consistently along permafrost coastal settlements at the regional scale for the Northern Hemisphere. We provide a new method to automatically derive long-term coastline change rates for permafrost coasts. In addition, we identify the total number of coastal settlements and associated infrastructure that could be threatened by marine and terrestrial changes using remote sensing techniques. We extended the Arctic Coastal Infrastructure data set (SACHI) to include road types, airstrips, and artificial water reservoirs. The analysis of coastline, Ground Temperature (GT) and Active Layer Thickness (ALT) changes from 2000 to 2020, in addition with SLR projection, allowed to identify exposed settlements and infrastructure for 2030, 2050, and 2100. We validated the SACHI-v2, GT and ALT data sets through comparisons with in-situ data. 60% of the detected infrastructure is built on low-lying coast (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>&lt;</mo>\u0000 </mrow>\u0000 <annotation> ${&lt; } $</annotation>\u0000 </semantics></math>10 m a.s.l). The results show that in 2100, 45% of all coastal settlements will be affected by SLR and 21% by coastal erosion. On average, coastal permafrost GT is increasing by 0.8°C per decade, and ALT is increasing by 6 cm per decade. In 2100, GT will become positive at 77% of the built infrastructure area. Our results highlight the circumpolar and international amplitude of the problem and emphasize the need for immediate adaptation measures to current and future environmental changes to counteract a deterioration of living conditions and ensure infrastructure sustainability.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 12","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF005013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861529","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":"Climate Warming Will Exacerbate Unequal Exposure to Compound Flood-Heatwave Extremes","authors":"Qikang Zhao,&nbsp;Liang Gao,&nbsp;Qingyan Meng,&nbsp;Mingming Zhu","doi":"10.1029/2024EF005179","DOIUrl":"https://doi.org/10.1029/2024EF005179","url":null,"abstract":"<p>Compound flood-heatwave extremes (CFHWs) have threatened the sustainable development of human society and ecosystems. However, the disproportionate risks in regions with different economic development under a warming climate have not been quantified. This study carries out a global investigation on the future CFHWs under three scenarios based on 11 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Results reveal a 7.5-fold increase in global annual CFHW days by 2100 under the intermediate greenhouse-gas-emission scenario SSP2-4.5 compared to that in 1980. Under SSP2-4.5, population exposure in low-income countries in the late future (2071–2090) will be about 9-fold higher than in high-income countries compared to baseline period (1995–2014). Moreover, exposure of the poor groups living on less than $6.85/day will increase by nearly 28.1-fold. Eastern Africa and South Asia are identified as particularly high-risk regions, where large populations living in poverty face rapidly increasing CFHWs. These findings indicate that climate inequality will become more pronounced if climate warming continues without immediate effective measures. Our study also underscores the urgent need for mitigation and adaptation strategies against the future increasing CFHWs, especially for the vast low-income and high-risk regions.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 12","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF005179","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860845","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":"Improving GCM-Based Decadal Ocean Carbon Flux Predictions Using Observationally-Constrained Statistical Models","authors":"P. Gooya,&nbsp;N. C. Swart,&nbsp;P. Landschützer","doi":"10.1029/2023EF004204","DOIUrl":"https://doi.org/10.1029/2023EF004204","url":null,"abstract":"<p>An essential step toward meeting agreed climate targets and policies is the ability to understand and predict near-term changes in global carbon cycle, and importantly, ocean carbon uptake. Initialized climate model simulations have proven skillful for near-term predictability of the key physical climate variables, for example, temperature, precipitation, etc. By comparison, predictions of biogeochemical fields like ocean carbon flux, are still emerging. Initial studies indicate skillful predictions are possible for lead-times up to 6 years at global scale for some CMIP6 models. However, unlike core physical variables, biogeochemical variables are not directly initialized in existing decadal prediction systems, and extensive empirical parametrization of ocean-biogeochemistry in Earth System Models introduces a significant source of uncertainty. Here we propose a new approach for improving the skill of decadal ocean carbon flux predictions using observationally-constrained statistical models, as alternatives to the ocean-biogeochemistry models. We use observations to train multi-linear and neural-network models to predict the ocean carbon flux. To account for observational uncertainties, we train using six different observational estimates of the flux. We then apply these trained statistical models using input predictors from the Canadian Earth System Model (CanESM5) decadal prediction system to produce new decadal predictions. Our hybrid GCM-statistical approach significantly improves prediction skill, relative to the raw CanESM5 hindcast predictions over 1990–2019. Our hybrid-model skill is also larger than that obtained by any available CMIP6 model. Using bias-corrected CanESM5 predictors, we make forecasts for ocean carbon flux over 2020–2029. Both statistical models predict increases in the ocean carbon flux larger than the changes predicted from CanESM5 forecasts. Our work highlights the ability to improve decadal ocean carbon flux predictions by using observationally-trained statistical models together with robust input predictors from GCM-based decadal predictions.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 12","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023EF004204","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860846","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}