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Crespo-Miguel R, Ordóñez C, García-Herrera R, Schnell JL, Turnock ST. Large-scale ozone episodes in Europe: Decreasing sizes in the last decades but diverging changes in the future. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 949:175071. [PMID: 39079641 DOI: 10.1016/j.scitotenv.2024.175071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Revised: 07/04/2024] [Accepted: 07/25/2024] [Indexed: 08/04/2024]
Abstract
Episodes of high near-surface ozone concentrations tend to cover large areas for several days. They are strongly dependent on meteorology, precursor emissions, and the ambient photochemical conditions. This study introduces a new pseudo-Lagrangian algorithm that identifies the spatiotemporal patterns of episodes, allowing for a good characterization of their areal extent and an assessment of their drivers. The algorithm has been used to identify ozone episodes in Europe from April to September over the last twenty years (2003-2022) in the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis as well as in the historical simulation (1950-2014) and four shared socio-economic pathways (SSPs, spanning 2015-2100) of three Earth system models (UKESM1-0-LL, EC-Earth3-AerChem and GFDL-ESM4). While the total number of episodes has increased in recent years, the frequency of large episodes has decreased following European precursor emission reductions. The analysis of the 100 largest episodes shows that they tend to occur in Northern Europe during spring and in the center and south of the continent from June onwards. Most of the top 10 episodes occurred in the first years of the century and were associated with high temperatures, enhanced solar radiation, and anticyclonic conditions. Despite the decrease in large episodes in recent years, there is uncertainty regarding future European episodes. Episodes of reduced size are found for SSPs with weak greenhouse forcing and low precursor emissions, whereas episode sizes increase in scenarios with high methane concentrations and enhanced radiative forcing, even exceeding the maximum historical size. However, the three models project episodes of different sizes for any given scenario, probably associated with their differing warming trends and the varying level of complexity in the implementation of processes. These results point to the need to implement both effective climate and air quality policies to address the ozone air pollution problem in Europe in a warming climate.
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Affiliation(s)
- Rodrigo Crespo-Miguel
- Departamento de Física de la Tierra y Astrofísica, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, Madrid, Spain.
| | - Carlos Ordóñez
- Departamento de Física de la Tierra y Astrofísica, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, Madrid, Spain.
| | - Ricardo García-Herrera
- Departamento de Física de la Tierra y Astrofísica, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, Madrid, Spain; Instituto de Geociencias (IGEO), Consejo Superior de Investigaciones Científicas-Universidad Complutense de Madrid (CSIC-UCM), Madrid, Spain.
| | - Jordan L Schnell
- Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, United States of America; NOAA Global Systems Laboratory, Boulder, CO, United States of America.
| | - Steven T Turnock
- Met Office Hadley Centre, Exeter, United Kingdom; University of Leeds, Met Office Strategic (LUMOS) Research Group, University of Leeds, Leeds, United Kingdom.
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2
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Zeller E, Timmermann A. The evolving three-dimensional landscape of human adaptation. SCIENCE ADVANCES 2024; 10:eadq3613. [PMID: 39383234 PMCID: PMC11463275 DOI: 10.1126/sciadv.adq3613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Accepted: 09/04/2024] [Indexed: 10/11/2024]
Abstract
Over the past 3 million years, humans have expanded their ecological niche and adapted to more diverse environments. The temporal evolution and underlying drivers behind this niche expansion remain largely unknown. By combining archeological findings with landscape topographic data and model simulations of the climate and biomes, we show that human sites clustered in areas with increased terrain roughness, corresponding to higher levels of biodiversity. We find a gradual increase in human habitat preferences toward rough terrains until about 1.1 million years ago (Ma), followed by a 300 thousand-year-long contraction of the ecological niche. This period coincided with the Mid-Pleistocene Transition and previously hypothesized ancestral population bottlenecks. Our statistical analysis further reveals that from 0.8 Ma onward, the human niche expanded again, with human species (e.g., H. heidelbergensis, H. neanderthalensis, and H. sapiens) adapting to rougher terrain, colder and drier conditions, and toward regions of higher ecological diversity.
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Affiliation(s)
- Elke Zeller
- IBS Center for Climate Physics, Busan, Republic of Korea
- Department of Climate System, PNU, Busan, Republic of Korea
| | - Axel Timmermann
- IBS Center for Climate Physics, Busan, Republic of Korea
- Department of Climate System, PNU, Busan, Republic of Korea
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Moustakis Y, Nützel T, Wey HW, Bao W, Pongratz J. Temperature overshoot responses to ambitious forestation in an Earth System Model. Nat Commun 2024; 15:8235. [PMID: 39300072 DOI: 10.1038/s41467-024-52508-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 09/07/2024] [Indexed: 09/22/2024] Open
Abstract
Despite the increasing relevance of temperature overshoot and the rather ambitious country pledges on Afforestation/Reforestation globally, the mitigation potential and the Earth system responses to large-scale non-idealized Afforestation/Reforestation patterns under a high overshoot scenario remain elusive. Here, we develop an ambitious Afforestation/Reforestation scenario by harnessing 1259 Integrated Assessment Model scenarios, restoration potential maps, and biodiversity constraints, reaching 595 Mha by 2060 and 935 Mha by 2100. We then force the Max Planck Institute's Earth System Model with this scenario which yields a reduction of peak temperature by 0.08 oC, end-of-century temperature by 0.2 oC, and overshoot duration by 13 years. Afforestation/Reforestation in the range of country pledges globally could thus constitute a useful mitigation tool in overshoot scenarios in addition to fossil fuel emission reductions, but socio-ecological implications need to be scrutinized to avoid severe side effects.
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Affiliation(s)
| | - Tobias Nützel
- Ludwig-Maximilians-Universität in Munich, Munich, Germany
| | - Hao-Wei Wey
- GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
| | - Wenkai Bao
- Ludwig-Maximilians-Universität in Munich, Munich, Germany
| | - Julia Pongratz
- Ludwig-Maximilians-Universität in Munich, Munich, Germany
- Max Planck Institute for Meteorology, Hamburg, Germany
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4
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de Vries I, Sippel S, Zeder J, Fischer E, Knutti R. Increasing extreme precipitation variability plays a key role in future record-shattering event probability. COMMUNICATIONS EARTH & ENVIRONMENT 2024; 5:482. [PMID: 39239115 PMCID: PMC11371648 DOI: 10.1038/s43247-024-01622-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 07/17/2024] [Indexed: 09/07/2024]
Abstract
Climate events that break records by large margins are a threat to society and ecosystems. Climate change is expected to increase the probability of such events, but quantifying these probabilities is challenging due to natural variability and limited data availability, especially for observations and very rare extremes. Here we estimate the probability of precipitation events that shatter records by a margin of at least one pre-industrial standard deviation. Using large ensemble climate simulations and extreme value theory, we determine empirical and analytical record shattering probabilities and find they are in high agreement. We show that, particularly in high emission scenarios, models project much higher record-shattering precipitation probabilities in a changing relative to a stationary climate by the end of the century for almost all the global land, with the strongest increases in vulnerable regions in the tropics. We demonstrate that increasing variability is an essential driver of near-term increases in record-shattering precipitation probability, and present a framework that quantifies the influence of combined trends in mean and variability on record-shattering behaviour in extreme precipitation. Probability estimates of record-shattering precipitation events in a warming world are crucial to inform risk assessment and adaptation policies.
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Affiliation(s)
- Iris de Vries
- Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland
| | - Sebastian Sippel
- Leipzig Institute for Meteorology, Leipzig University, Leipzig, Germany
| | - Joel Zeder
- Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland
| | - Erich Fischer
- Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland
| | - Reto Knutti
- Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland
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5
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Mizsei E, Radovics D, Rák G, Budai M, Bancsik B, Szabolcs M, Sos T, Lengyel S. Alpine viper in changing climate: thermal ecology and prospects of a cold-adapted reptile in the warming Mediterranean. Sci Rep 2024; 14:18988. [PMID: 39152146 PMCID: PMC11329715 DOI: 10.1038/s41598-024-69378-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 08/05/2024] [Indexed: 08/19/2024] Open
Abstract
In a rapidly changing thermal environment, reptiles are primarily dependent on in situ adaptation because of their limited ability to disperse and the restricted opportunity to shift their ranges. However, the rapid pace of climate change may surpass these adaptation capabilities or elevate energy expenditures. Therefore, understanding the variability in thermal traits at both individual and population scales is crucial, offering insights into reptiles' vulnerability to climate change. We studied the thermal ecology of the endangered Greek meadow viper (Vipera graeca), an endemic venomous snake of fragmented alpine-subalpine meadows above 1600 m of the Pindos mountain range in Greece and Albania, to assess its susceptibility to anticipated changes in the alpine thermal environment. We measured preferred body temperature in artificial thermal gradient, field body temperatures of 74 individuals in five populations encompassing the entire geographic range of the species, and collected data on the available of temperatures for thermoregulation. We found that the preferred body temperature (Tp) differed only between the northernmost and the southernmost populations and increased with female body size but did not depend on sex or the gravidity status of females. Tp increased with latitude but was unaffected by the phylogenetic position of the populations. We also found high accuracy of thermoregulation in V. graeca populations and variation in the thermal quality of habitats throughout the range. The overall effectiveness of thermoregulation was high, indicating that V. graeca successfully achieves its target temperatures and exploits the thermal landscape. Current climatic conditions limit the activity period by an estimated 1278 h per year, which is expected to increase considerably under future climate scenarios. Restricted time available for thermoregulation, foraging and reproduction will represent a serious threat to the fitness of individuals and the persistence of populations in addition to habitat loss due to mining, tourism or skiing and habitat degradation due to overgrazing in the shrinking mountaintop habitats of V. graeca.
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Affiliation(s)
- Edvárd Mizsei
- Conservation Ecology Research Group, Institute of Aquatic Ecology, HUN-REN Centre for Ecological Research, Budapest, Hungary.
- Kiskunság National Park Directorate, Kecskemét, Hungary.
- Institute of Metagenomics, University of Debrecen, Debrecen, Hungary.
| | - Dávid Radovics
- Kiskunság National Park Directorate, Kecskemét, Hungary
- Department of Ecology, University of Debrecen, Debrecen, Hungary
| | - Gergő Rák
- Department of Systematic Zoology and Ecology, Eötvös Loránd University, Budapest, Hungary
| | - Mátyás Budai
- Department of Systematic Zoology and Ecology, Eötvös Loránd University, Budapest, Hungary
| | - Barnabás Bancsik
- Department of Ecology, University of Veterinary Medicine, Budapest, Hungary
| | - Márton Szabolcs
- Conservation Ecology Research Group, Institute of Aquatic Ecology, HUN-REN Centre for Ecological Research, Budapest, Hungary
| | - Tibor Sos
- Evolutionary Ecology Group, Hungarian Department of Biology and Ecology, Babeş-Bolyai University, Cluj-Napoca, Romania
- Milvus Group Bird and Nature Protection Association, Tîrgu Mureş, Romania
| | - Szabolcs Lengyel
- Conservation Ecology Research Group, Institute of Aquatic Ecology, HUN-REN Centre for Ecological Research, Budapest, Hungary
- Biodiversity, Climate Change and Water Management Coordination Research Centre, University of Debrecen, Debrecen, Hungary
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6
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Li L, Lu C, Winiwarter W, Tian H, Canadell JG, Ito A, Jain AK, Kou-Giesbrecht S, Pan S, Pan N, Shi H, Sun Q, Vuichard N, Ye S, Zaehle S, Zhu Q. Enhanced nitrous oxide emission factors due to climate change increase the mitigation challenge in the agricultural sector. GLOBAL CHANGE BIOLOGY 2024; 30:e17472. [PMID: 39158113 DOI: 10.1111/gcb.17472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2024] [Revised: 07/17/2024] [Accepted: 07/18/2024] [Indexed: 08/20/2024]
Abstract
Effective nitrogen fertilizer management is crucial for reducing nitrous oxide (N2O) emissions while ensuring food security within planetary boundaries. However, climate change might also interact with management practices to alter N2O emission and emission factors (EFs), adding further uncertainties to estimating mitigation potentials. Here, we developed a new hybrid modeling framework that integrates a machine learning model with an ensemble of eight process-based models to project EFs under different climate and nitrogen policy scenarios. Our findings reveal that EFs are dynamically modulated by environmental changes, including climate, soil properties, and nitrogen management practices. Under low-ambition nitrogen regulation policies, EF would increase from 1.18%-1.22% in 2010 to 1.27%-1.34% by 2050, representing a relative increase of 4.4%-11.4% and exceeding the IPCC tier-1 EF of 1%. This trend is particularly pronounced in tropical and subtropical regions with high nitrogen inputs, where EFs could increase by 0.14%-0.35% (relative increase of 11.9%-17%). In contrast, high-ambition policies have the potential to mitigate the increases in EF caused by climate change, possibly leading to slight decreases in EFs. Furthermore, our results demonstrate that global EFs are expected to continue rising due to warming and regional drying-wetting cycles, even in the absence of changes in nitrogen management practices. This asymmetrical influence of nitrogen fertilizers on EFs, driven by climate change, underscores the urgent need for immediate N2O emission reductions and further assessments of mitigation potentials. This hybrid modeling framework offers a computationally efficient approach to projecting future N2O emissions across various climate, soil, and nitrogen management scenarios, facilitating socio-economic assessments and policy-making efforts.
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Affiliation(s)
- Linchao Li
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, Iowa, USA
| | - Chaoqun Lu
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, Iowa, USA
| | - Wilfried Winiwarter
- International Institute for Applied Systems Analysis, Laxenburg, Austria
- Institute of Environmental Engineering, University of Zielona Góra, Zielona Góra, Poland
| | - Hanqin Tian
- Center for Earth System Science and Global Sustainability, Schiller Institute for Integrated Science and Society, Boston College, Chestnut Hill, Massachusetts, USA
- Department of Earth and Environmental Sciences, Boston College, Chestnut Hill, Massachusetts, USA
| | - Josep G Canadell
- CSIRO Environment, Canberra, Australian Capital Territory, Australia
| | - Akihiko Ito
- Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, 113-8657, Japan
- Earth System Division, National Institute for Environmental Studies, Tsukuba, Japan
| | - Atul K Jain
- Department of Climate, Meteorology, and Atmospheric Sciences, University of Illinois, Urbana-Champaign, Urbana, USA
| | - Sian Kou-Giesbrecht
- Department of Earth and Environmental Sciences, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Shufen Pan
- Center for Earth System Science and Global Sustainability, Schiller Institute for Integrated Science and Society, Boston College, Chestnut Hill, Massachusetts, USA
- Department of Engineering and Environmental Studies Program, Boston College, Chestnut Hill, Massachusetts, USA
| | - Naiqing Pan
- Center for Earth System Science and Global Sustainability, Schiller Institute for Integrated Science and Society, Boston College, Chestnut Hill, Massachusetts, USA
| | - Hao Shi
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China
| | - Qing Sun
- Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
| | - Nicolas Vuichard
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, CEA CNRS, UVSQ UPSACLAY, Gif sur Yvette, France
| | - Shuchao Ye
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, Iowa, USA
| | - Sönke Zaehle
- Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Qing Zhu
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
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7
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Maqsood J, Wang X, Farooque AA, Nawaz RA. Future projections of temperature-related indices in Prince Edward Island using ensemble average of three CMIP6 models. Sci Rep 2024; 14:12661. [PMID: 38830965 PMCID: PMC11148011 DOI: 10.1038/s41598-024-63450-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 05/29/2024] [Indexed: 06/05/2024] Open
Abstract
Prince Edward Island (PEI) is an agricultural province heavily relying on rainfed agriculture. The island has already experienced significant impacts from climate change. Accurate projections of PEI temperature extreme indices are required to mitigate and adapt to the changing climate conditions. This study aims to develop ensemble projections using Coupled Model Intercomparison Project Phase 6 (CMIP6) global circulation models (GCMs) to analyze temperature extremes on PEI. In this study, the ECMWF ERA5 reanalysis dataset was chosen for stepwise cluster analysis (SCA) due to its high accuracy. Three CMIP6 (NorESM2-MM, MPI-ESM1.2-HR, and CanESM5) GCMs, along with their ensemble average, were utilized in the SCA model to project future changes in daily maximum temperature (Tmax) and minimum temperature (Tmin) at four meteorological stations on PEI (East Point, Charlottetown, Summerside, and North Cape) under two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5). These GCMs were selected based on their low, medium, and high Equilibrium Climate Sensitivity. The bias-corrected results for the future period of Tmax and Tmin showed that the GCM-specific changes in the ECS also impact the regional scale. Additionally, several temperature extreme indices, including the daily temperature range (DTR), summer days (SU), growing degree days (GDD), growing season length (GSL), ice days (ID), and frost days (FD), were analyzed for two future periods: FP1(202-2050) and FP2 (2051-2075). The results indicate that DTR, SU, GDD, and GSL are expected to increase, while ID and FD are projected to decrease during FP1 and FP2 under both scenarios. The future projected mean monthly changes in Tmax, Tmin, and the selected temperature extreme indices highlight warmer future periods and an increase in agriculture-related indices such as GDD and GSL. Specifically, July, August, and September are expected to experience even higher temperatures in the future. As the climate becomes warmer, cold extreme events are projected to be shorter in duration but more intense in terms of their impact. The largest increments/decrements for Tmax, Tmin, and their relevant indices were observed during FP2 under SSP5-8.5. The outcomes of this study provide valuable insights for agricultural development, water resource management, and the formulation of effective mitigation strategies to address the impacts of climate change on PEI.
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Affiliation(s)
- Junaid Maqsood
- Applied Research Department, Holland College, Charlottetown, PE, C1A 4Z1, Canada
| | - Xiuquan Wang
- Canadian Centre for Climate Change and Adaptation, University of Prince Edward Island, St. Peter's Bay, PE, C0A 2A0, Canada.
- School of Climate Change and Adaptation, University of Prince Edward Island, Charlottetown, PE, C1A 4P3, Canada.
| | - Aitazaz A Farooque
- Canadian Centre for Climate Change and Adaptation, University of Prince Edward Island, St. Peter's Bay, PE, C0A 2A0, Canada
- School of Climate Change and Adaptation, University of Prince Edward Island, Charlottetown, PE, C1A 4P3, Canada
- Faculty of Sustainable Design Engineering, University of Prince Edward Island, Charlottetown, PE, C1A 4P3, Canada
| | - Rana Ali Nawaz
- Canadian Centre for Climate Change and Adaptation, University of Prince Edward Island, St. Peter's Bay, PE, C0A 2A0, Canada
- Faculty of Sustainable Design Engineering, University of Prince Edward Island, Charlottetown, PE, C1A 4P3, Canada
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8
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Zuo Z, Qiao L, Zhang R, Chen D, Piao S, Xiao D, Zhang K. Importance of soil moisture conservation in mitigating climate change. Sci Bull (Beijing) 2024; 69:1332-1341. [PMID: 38485623 DOI: 10.1016/j.scib.2024.02.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 02/18/2024] [Accepted: 02/21/2024] [Indexed: 05/06/2024]
Abstract
A troubling feedback loop, where drier soil contributes to hotter climates, has been widely recognized. This study, drawing on climate model simulations, reveals that maintaining current global soil moisture levels could significantly alleviate 32.9% of land warming under low-emission scenarios. This action could also postpone reaching critical warming thresholds of 1.5 °C and 2.0 °C by at least a decade. Crucially, preserving soil moisture at current levels could prevent noticeable climate change impacts across 42% of the Earth's land, a stark deviation from projections suggesting widespread impacts before the 2060s. To combat soil drying, afforestation in mid-to-low latitude regions within the next three decades is proposed as an effective strategy to increase surface water availability. This underscores the substantial potential of nature-based solutions for managing soil moisture, benefiting both climate change mitigation and ecological enhancement.
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Affiliation(s)
- Zhiyan Zuo
- Key Laboratory of Polar Atmosphere-ocean-ice System for Weather and Climate of Ministry of Education/Shanghai Key Laboratory of Ocean-Land-Atmosphere Boundary Dynamics and Climate Change, Department of Atmospheric and Oceanic Sciences/Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China.
| | - Liang Qiao
- Key Laboratory of Polar Atmosphere-ocean-ice System for Weather and Climate of Ministry of Education/Shanghai Key Laboratory of Ocean-Land-Atmosphere Boundary Dynamics and Climate Change, Department of Atmospheric and Oceanic Sciences/Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Renhe Zhang
- Key Laboratory of Polar Atmosphere-ocean-ice System for Weather and Climate of Ministry of Education/Shanghai Key Laboratory of Ocean-Land-Atmosphere Boundary Dynamics and Climate Change, Department of Atmospheric and Oceanic Sciences/Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China.
| | - Deliang Chen
- Department of Earth Sciences, University of Gothenburg, Gothenburg 40530, Sweden.
| | - Shilong Piao
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100091, China
| | - Dong Xiao
- Key Laboratory of Cites' Mitigation and Adaptation to Climate Change in Shanghai, China Meteorological Administration, Shanghai 200030, China
| | - Kaiwen Zhang
- Key Laboratory of Polar Atmosphere-ocean-ice System for Weather and Climate of Ministry of Education/Shanghai Key Laboratory of Ocean-Land-Atmosphere Boundary Dynamics and Climate Change, Department of Atmospheric and Oceanic Sciences/Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
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9
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Weber J, King JA, Abraham NL, Grosvenor DP, Smith CJ, Shin YM, Lawrence P, Roe S, Beerling DJ, Martin MV. Chemistry-albedo feedbacks offset up to a third of forestation's CO 2 removal benefits. Science 2024; 383:860-864. [PMID: 38386743 DOI: 10.1126/science.adg6196] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 12/15/2023] [Indexed: 02/24/2024]
Abstract
Forestation is widely proposed for carbon dioxide (CO2) removal, but its impact on climate through changes to atmospheric composition and surface albedo remains relatively unexplored. We assessed these responses using two Earth system models by comparing a scenario with extensive global forest expansion in suitable regions to other plausible futures. We found that forestation increased aerosol scattering and the greenhouse gases methane and ozone following increased biogenic organic emissions. Additionally, forestation decreased surface albedo, which yielded a positive radiative forcing (i.e., warming). This offset up to a third of the negative forcing from the additional CO2 removal under a 4°C warming scenario. However, when forestation was pursued alongside other strategies that achieve the 2°C Paris Agreement target, the offsetting positive forcing was smaller, highlighting the urgency for simultaneous emission reductions.
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Affiliation(s)
- James Weber
- Leverhulme Centre for Climate Change Mitigation, School of Biosciences, University of Sheffield, Sheffield S10 2TN, UK
| | - James A King
- Leverhulme Centre for Climate Change Mitigation, School of Biosciences, University of Sheffield, Sheffield S10 2TN, UK
| | - Nathan Luke Abraham
- Centre for Atmospheric Science, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK
- National Centre for Atmospheric Science, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK
| | - Daniel P Grosvenor
- Centre for Environmental Modelling and Computation (CEMAC), School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK
- Met Office Hadley Centre, Exeter EX1 3PB, UK
| | - Christopher J Smith
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK
- International Institute for Applied Systems Analysis, A-2361 Laxenburg, Austria
| | - Youngsub Matthew Shin
- Centre for Atmospheric Science, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK
| | - Peter Lawrence
- NCAR Earth System Laboratory, Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO 80307, USA
| | | | - David J Beerling
- Leverhulme Centre for Climate Change Mitigation, School of Biosciences, University of Sheffield, Sheffield S10 2TN, UK
| | - Maria Val Martin
- Leverhulme Centre for Climate Change Mitigation, School of Biosciences, University of Sheffield, Sheffield S10 2TN, UK
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10
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Trancoso R, Syktus J, Allan RP, Croke J, Hoegh-Guldberg O, Chadwick R. Significantly wetter or drier future conditions for one to two thirds of the world's population. Nat Commun 2024; 15:483. [PMID: 38212324 PMCID: PMC10784476 DOI: 10.1038/s41467-023-44513-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 12/15/2023] [Indexed: 01/13/2024] Open
Abstract
Future projections of precipitation are uncertain, hampering effective climate adaptation strategies globally. Our understanding of changes across multiple climate model simulations under a warmer climate is limited by this lack of coherence across models. Here, we address this challenge introducing an approach that detects agreement in drier and wetter conditions by evaluating continuous 120-year time-series with trends, across 146 Global Climate Model (GCM) runs and two elevated greenhouse gas (GHG) emissions scenarios. We show the hotspots of future drier and wetter conditions, including regions already experiencing water scarcity or excess. These patterns are projected to impact a significant portion of the global population, with approximately 3 billion people (38% of the world's current population) affected under an intermediate emissions scenario and 5 billion people (66% of the world population) under a high emissions scenario by the century's end (or 35-61% using projections of future population). We undertake a country- and state-level analysis quantifying the population exposed to significant changes in precipitation regimes, offering a robust framework for assessing multiple climate projections.
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Affiliation(s)
- Ralph Trancoso
- School of The Environment, The University of Queensland, Brisbane, QLD, Australia.
- Climate Projections and Services, Department of Environment and Science, Queensland Government, Brisbane, QLD, Australia.
| | - Jozef Syktus
- School of The Environment, The University of Queensland, Brisbane, QLD, Australia
| | - Richard P Allan
- Department of Meteorology and National Centre for Earth Observation, University of Reading, Reading, UK
| | - Jacky Croke
- Centre for Climate, Environment and Sustainability, School of Earth and Atmospheric Sciences, Queensland University of Technology, Brisbane, QLD, Australia
| | - Ove Hoegh-Guldberg
- School of The Environment, The University of Queensland, Brisbane, QLD, Australia
| | - Robin Chadwick
- Met Office Hadley Centre, Exeter, UK
- Global Systems Institute, Department of Mathematics, University of Exeter, Exeter, UK
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11
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Childs ML, Lyberger K, Harris M, Burke M, Mordecai EA. Climate warming is expanding dengue burden in the Americas and Asia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.08.24301015. [PMID: 38260629 PMCID: PMC10802639 DOI: 10.1101/2024.01.08.24301015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Climate change poses significant threats to public health, with dengue representing a growing concern due to its high existing burden and sensitivity to climatic conditions. Yet, the quantitative impacts of temperature warming on dengue, both in the past and in the future, remain poorly understood. In this study, we quantify how dengue responds to climatic fluctuations, and use this inferred temperature response to estimate the impacts of historical warming and forecast trends under future climate change scenarios. To estimate the causal impact of temperature on the spread of dengue in the Americas and Asia, we assembled a dataset encompassing nearly 1.5 million dengue incidence records from 21 countries. Our analysis revealed a nonlinear relationship between temperature and dengue incidence with the largest marginal effects at lower temperatures (around 15°C), peak incidence at 27.8°C (95% CI: 27.3 - 28.2°C), and subsequent declines at higher temperatures. Our findings indicate that historical climate change has already increased dengue incidence 18% (12 - 25%) in the study region, and projections suggest a potential increase of 40% (17 - 76) to 57% (33 - 107%) by mid-century depending on the climate scenario, with some areas seeing up to 200% increases. Notably, our models suggest that lower emissions scenarios would substantially reduce the warming-driven increase in dengue burden. Together, these insights contribute to the broader understanding of how long-term climate patterns influence dengue, providing a valuable foundation for public health planning and the development of strategies to mitigate future risks due to climate change.
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Affiliation(s)
- Marissa L Childs
- Center for the Environment, Harvard University, Cambridge, MA, USA
| | - Kelsey Lyberger
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Mallory Harris
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Marshall Burke
- Global Environmental Policy, Stanford University, Stanford, CA, USA
- Center on Food Security and the Environment, Stanford University, Stanford, CA, USA
- National Bureau of Economic Research, Cambridge, MA, USA
| | - Erin A Mordecai
- Department of Biology, Stanford University, Stanford, CA, USA
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12
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Nelson GC, Vanos J, Havenith G, Jay O, Ebi KL, Hijmans RJ. Global reductions in manual agricultural work capacity due to climate change. GLOBAL CHANGE BIOLOGY 2024; 30:e17142. [PMID: 38273519 DOI: 10.1111/gcb.17142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 12/19/2023] [Accepted: 12/21/2023] [Indexed: 01/27/2024]
Abstract
Manual outdoor work is essential in many agricultural systems. Climate change will make such work more stressful in many regions due to heat exposure. The physical work capacity metric (PWC) is a physiologically based approach that estimates an individual's work capacity relative to an environment without any heat stress. We computed PWC under recent past and potential future climate conditions. Daily values were computed from five earth system models for three emission scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5) and three time periods: 1991-2010 (recent past), 2041-2060 (mid-century) and 2081-2100 (end-century). Average daily PWC values were aggregated for the entire year, the growing season, and the warmest 90-day period of the year. Under recent past climate conditions, the growing season PWC was below 0.86 (86% of full work capacity) on half the current global cropland. With end-century/SSP5-8.5 thermal conditions this value was reduced to 0.7, with most affected crop-growing regions in Southeast and South Asia, West and Central Africa, and northern South America. Average growing season PWC could falls below 0.4 in some important food production regions such as the Indo-Gangetic plains in Pakistan and India. End-century PWC reductions were substantially greater than mid-century reductions. This paper assesses two potential adaptions-reducing direct solar radiation impacts with shade or working at night and reducing the need for hard physical labor with increased mechanization. Removing the effect of direct solar radiation impacts improved PWC values by 0.05 to 0.10 in the hottest periods and regions. Adding mechanization to increase horsepower (HP) per hectare to levels similar to those in some higher income countries would require a 22% increase in global HP availability with Sub-Saharan Africa needing the most. There may be scope for shifting to less labor-intensive crops or those with labor peaks in cooler periods or shift work to early morning.
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Affiliation(s)
- Gerald C Nelson
- University of Illinois, Urbana-Champaign, Urbana, Illinois, USA
| | | | | | - Ollie Jay
- University of Sydney, Sydney, New South Wales, Australia
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13
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Li KF, Tung KK. Solar cycle as a distinct line of evidence constraining Earth's transient climate response. Nat Commun 2023; 14:8430. [PMID: 38114458 PMCID: PMC10730699 DOI: 10.1038/s41467-023-43583-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 11/14/2023] [Indexed: 12/21/2023] Open
Abstract
Severity of warming predicted by climate models depends on their Transient Climate Response (TCR). Inter-model spread of TCR has persisted at ~ 100% of its mean for decades. Existing observational constraints of TCR are based on observed historical warming response to historical forcing and their uncertainty spread is just as wide, mainly due to forcing uncertainty, and especially that of aerosols. Contrary, no aerosols are involved in solar-cycle forcing, providing an independent, tighter, constraint. Here, we define a climate sensitivity metric: time-dependent response regressed against time-dependent forcing, allowing phenomena with dissimilar time variations, such as the solar cycle with 11-year cyclic forcing, to be used to constrain TCR, which has a linear time-dependent forcing. We find a theoretical linear relationship between the two. The latest coupled atmosphere-ocean climate models obey the same linear relationship statistically. The proposed observational constraint on TCR is about [Formula: see text] as narrow as existing constraints. The central estimate, 2.2 oC, is at the midpoint of the spread of the latest generation of climate models, which are more sensitive than those of the previous generations.
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Affiliation(s)
- King-Fai Li
- Department of Environmental Sciences, University of California, Riverside, CA, USA
| | - Ka-Kit Tung
- Department of Applied Mathematics, University of Washington, Seattle, CA, USA.
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14
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Beck HE, McVicar TR, Vergopolan N, Berg A, Lutsko NJ, Dufour A, Zeng Z, Jiang X, van Dijk AIJM, Miralles DG. High-resolution (1 km) Köppen-Geiger maps for 1901-2099 based on constrained CMIP6 projections. Sci Data 2023; 10:724. [PMID: 37872197 PMCID: PMC10593765 DOI: 10.1038/s41597-023-02549-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 09/07/2023] [Indexed: 10/25/2023] Open
Abstract
We introduce Version 2 of our widely used 1-km Köppen-Geiger climate classification maps for historical and future climate conditions. The historical maps (encompassing 1901-1930, 1931-1960, 1961-1990, and 1991-2020) are based on high-resolution, observation-based climatologies, while the future maps (encompassing 2041-2070 and 2071-2099) are based on downscaled and bias-corrected climate projections for seven shared socio-economic pathways (SSPs). We evaluated 67 climate models from the Coupled Model Intercomparison Project phase 6 (CMIP6) and kept a subset of 42 with the most plausible CO2-induced warming rates. We estimate that from 1901-1930 to 1991-2020, approximately 5% of the global land surface (excluding Antarctica) transitioned to a different major Köppen-Geiger class. Furthermore, we project that from 1991-2020 to 2071-2099, 5% of the land surface will transition to a different major class under the low-emissions SSP1-2.6 scenario, 8% under the middle-of-the-road SSP2-4.5 scenario, and 13% under the high-emissions SSP5-8.5 scenario. The Köppen-Geiger maps, along with associated confidence estimates, underlying monthly air temperature and precipitation data, and sensitivity metrics for the CMIP6 models, can be accessed at www.gloh2o.org/koppen .
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Affiliation(s)
- Hylke E Beck
- King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
| | - Tim R McVicar
- CSIRO Environment, Canberra, ACT, Australia
- Australian Research Council Centre of Excellence for Climate Extremes, Canberra, ACT, Australia
| | - Noemi Vergopolan
- Atmospheric and Ocean Sciences Program, Princeton University, Princeton, New Jersey, USA
- NOAA Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, USA
| | - Alexis Berg
- University of Montreal, Montreal, Quebec, Canada
| | - Nicholas J Lutsko
- Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California, USA
| | - Ambroise Dufour
- King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Zhenzhong Zeng
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Xin Jiang
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Albert I J M van Dijk
- Fenner School of Environment & Society, The Australian National University, Canberra, Australia
| | - Diego G Miralles
- Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium
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15
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Kumar N, Singh VG, Singh SK, Behera DK, Gašparović M. Modeling of land use change under the recent climate projections of CMIP6: a case study of Indian river basin. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:107219-107235. [PMID: 37127743 DOI: 10.1007/s11356-023-26960-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 04/08/2023] [Indexed: 05/03/2023]
Abstract
The aim of the study was to investigate the land use change dynamics under CMIP6 projections using Land Change Modeler (LCM). The Global Sensitivity Analysis (GSA) techniques was applied to quantify the sensitivity of single parameter and combination of parameters. Land use and land cover (LULC) transitions of the baseline period (2006-2016) was assessed with a model performance accuracy of 80%. Receiver operating characteristic (ROC) analysis shows that the model has performed well for all the LULC classes except builtup land. Prediction under the SSP245 scenario depicts that areal extent of agricultural, forest, and snow, and glacier will decrease by the mid-century (2045). However, the grassland and barren land area will increase from the baseline period. A similar change pattern with a higher magnitude has also been predicted under SSP585 scenario. The CMIP6 forcing index considers socio-economic effects and LCM predicted an expansion in barren land which may be attributed to changes in cryosphere in the studied area.
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Affiliation(s)
- Nirmal Kumar
- K. Banerjee Centre for Atmospheric and Ocean Studies, University of Allahabad, Prayagraj, 211002, Uttar Pradesh, India
| | - Vikram Gaurav Singh
- K. Banerjee Centre for Atmospheric and Ocean Studies, University of Allahabad, Prayagraj, 211002, Uttar Pradesh, India
| | - Sudhir Kumar Singh
- K. Banerjee Centre for Atmospheric and Ocean Studies, University of Allahabad, Prayagraj, 211002, Uttar Pradesh, India.
| | | | - Mateo Gašparović
- Faculty of Geodesy, University of Zagreb, Kaciceva 26, Zagreb, Croatia
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16
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Jiang X, Su H, Jiang JH, Neelin JD, Wu L, Tsushima Y, Elsaesser G. Muted extratropical low cloud seasonal cycle is closely linked to underestimated climate sensitivity in models. Nat Commun 2023; 14:5586. [PMID: 37696809 PMCID: PMC10495370 DOI: 10.1038/s41467-023-41360-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Accepted: 08/31/2023] [Indexed: 09/13/2023] Open
Abstract
A large spread in model estimates of the equilibrium climate sensitivity (ECS), defined as the global mean near-surface air-temperature increase following a doubling of atmospheric CO2 concentration, leaves us greatly disadvantaged in guiding policy-making for climate change adaptation and mitigation. In this study, we show that the projected ECS in the latest generation of climate models is highly related to seasonal variations of extratropical low-cloud fraction (LCF) in historical simulations. Marked reduction of extratropical LCF from winter to summer is found in models with ECS > 4.75 K, in accordance with the significant reduction of extratropical LCF under a warming climate in these models. In contrast, a pronounced seasonal cycle of extratropical LCF, as supported by satellite observations, is largely absent in models with ECS < 3.3 K. The distinct seasonality in extratropical LCF in climate models is ascribed to their different prevailing cloud regimes governing the extratropical LCF variability.
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Affiliation(s)
- Xianan Jiang
- Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, Los Angeles, CA, USA.
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.
| | - Hui Su
- Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Civil and Environmental Engineering, Hong Kong University of Science and Technology, Hong Kong, China
- Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jonathan H Jiang
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - J David Neelin
- Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, CA, USA
| | - Longtao Wu
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | | | - Gregory Elsaesser
- NASA Goddard Institute for Space Studies, and Department of Applied Physics and Mathematics, Columbia University, New York, NY, USA
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17
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Cammarano D, Olesen JE, Helming K, Foyer CH, Schönhart M, Brunori G, Bandru KK, Bindi M, Padovan G, Thorsen BJ, Freund F, Abalos D. Models can enhance science-policy-society alignments for climate change mitigation. NATURE FOOD 2023; 4:632-635. [PMID: 37468615 DOI: 10.1038/s43016-023-00807-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/21/2023]
Affiliation(s)
- Davide Cammarano
- Department of Agroecology, iClimate, Center for Circular Bioeconomy (CBIO), Aarhus University, Tjele, Denmark.
| | - Jørgen Eivind Olesen
- Department of Agroecology, iClimate, Center for Circular Bioeconomy (CBIO), Aarhus University, Tjele, Denmark
| | - Katharina Helming
- Leibniz Centre for Agricultural Landscape Research (ZALF), Muencheberg, Germany
| | | | - Martin Schönhart
- Institute of Sustainable Economic Development, University of Natural Resources and Life Sciences, Vienna, Austria
| | - Gianluca Brunori
- Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy
| | | | - Marco Bindi
- Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Florence, Italy
| | - Gloria Padovan
- Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Florence, Italy
| | - Bo Jellesmark Thorsen
- Department of Food and Resource Economics, University of Copenhagen, Copenhagen, Denmark
| | - Florian Freund
- Johann Heinrich von Thünen Institute-Federal Research Institute for Rural Areas, Forestry and Fisheries, Institute of Market Analysis, Braunschweig, Germany
| | - Diego Abalos
- Department of Agroecology, iClimate, Center for Circular Bioeconomy (CBIO), Aarhus University, Tjele, Denmark.
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18
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Petrosyan V, Dinets V, Osipov F, Dergunova N, Khlyap L. Range Dynamics of Striped Field Mouse ( Apodemus agrarius) in Northern Eurasia under Global Climate Change Based on Ensemble Species Distribution Models. BIOLOGY 2023; 12:1034. [PMID: 37508463 PMCID: PMC10376031 DOI: 10.3390/biology12071034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 07/06/2023] [Accepted: 07/20/2023] [Indexed: 07/30/2023]
Abstract
The striped field mouse (Apodemus agrarius Pallas, 1771) is a widespread species in Northern Eurasia. It damages crops and carries zoonotic pathogens. Its current and future range expansion under climate change may negatively affect public health and the economy, warranting further research to understand the ecological and invasive characteristics of the species. In our study, we used seven algorithms (GLM, GAM, GBS, FDA, RF, ANN, and MaxEnt) to develop robust ensemble species distribution models (eSDMs) under current (1970-2000) and future climate conditions derived from global circulation models (GCMs) for 2021-2040, 2041-2060, 2061-2080, and 2081-2100. Simulation of climate change included high-, medium-, and low-sensitivity GCMs under four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). We analyzed the habitat suitability across GCMs and scenarios by constructing geographical ranges and calculating their centroids. The results showed that the range changes depended on both the sensitivity of GCMs and scenario. The main trends were range expansion to the northeast and partial loss of habitat in the steppe area. The striped field mouse may form a continuous range from Central Europe to East Asia, closing the range gap that has existed for 12 thousand years. We present 49 eSDMs for the current and future distribution of A. agrarius (for 2000-2100) with quantitative metrics (gain, loss, change) of the range dynamics under global climate change. The most important predictor variables determining eSDMs are mean annual temperature, mean diurnal range of temperatures, the highest temperature of the warmest month, annual precipitation, and precipitation in the coldest month. These findings could help limit the population of the striped field mouse and predict distribution of the species under global climate change.
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Affiliation(s)
- Varos Petrosyan
- A.N. Severtsov Institute of Ecology and Evolution of the Russian Academy of Sciences, Moscow 119071, Russia
| | - Vladimir Dinets
- Psychology Department, University of Tennessee, Knoxville, TN 37996, USA
| | - Fedor Osipov
- A.N. Severtsov Institute of Ecology and Evolution of the Russian Academy of Sciences, Moscow 119071, Russia
| | - Natalia Dergunova
- A.N. Severtsov Institute of Ecology and Evolution of the Russian Academy of Sciences, Moscow 119071, Russia
| | - Lyudmila Khlyap
- A.N. Severtsov Institute of Ecology and Evolution of the Russian Academy of Sciences, Moscow 119071, Russia
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19
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Hourdin F, Ferster B, Deshayes J, Mignot J, Musat I, Williamson D. Toward machine-assisted tuning avoiding the underestimation of uncertainty in climate change projections. SCIENCE ADVANCES 2023; 9:eadf2758. [PMID: 37467323 DOI: 10.1126/sciadv.adf2758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Accepted: 06/16/2023] [Indexed: 07/21/2023]
Abstract
Documenting the uncertainty of climate change projections is a fundamental objective of the inter-comparison exercises organized to feed into the Intergovernmental Panel on Climate Change (IPCC) reports. Usually, each modeling center contributes to these exercises with one or two configurations of its climate model, corresponding to a particular choice of "free parameter" values, resulting from a long and often tedious "model tuning" phase. How much uncertainty is omitted by this selection and how might readers of IPCC reports and users of climate projections be misled by its omission? We show here how recent machine learning approaches can transform the way climate model tuning is approached, opening the way to a simultaneous acceleration of model improvement and parametric uncertainty quantification. We show how an automatic selection of model configurations defined by different values of free parameters can produce different "warming worlds," all consistent with present-day observations of the climate system.
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20
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Mason RAB, Bozec YM, Mumby PJ. Demographic resilience may sustain significant coral populations in a 2°C-warmer world. GLOBAL CHANGE BIOLOGY 2023; 29:4152-4160. [PMID: 37097011 DOI: 10.1111/gcb.16741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 04/05/2023] [Accepted: 04/06/2023] [Indexed: 05/03/2023]
Abstract
Projections of coral reefs under climate change have important policy implications, but most analyses have focused on the intensification of climate-related physical stress rather than explicitly modelling how coral populations respond to stressors. Here, we analyse the future of the Great Barrier Reef (GBR) under multiple, spatially realistic drivers which allows less impacted sites to facilitate recovery. Under a Representative Concentration Pathway (RCP) 2.6 CMIP5 climate ensemble, where warming is capped at ~2°C, GBR mean coral cover declined mid-century but approached present-day levels towards 2100. This is considerably more optimistic than most analyses. However, under RCP4.5, mean coral cover declined by >80% by late-century, and reached near zero under RCP ≥6.0. While these models do not allow for adaptation, they significantly extend past studies by revealing demographic resilience of coral populations to low levels of additional warming, though more pessimistic outcomes might be expected under CMIP6. Substantive coral populations under RCP2.6 would facilitate long-term genetic adaptation, adding value to ambitious greenhouse emissions mitigation.
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Affiliation(s)
- Robert A B Mason
- School of Biological Sciences, University of Queensland, St. Lucia, Queensland, Australia
| | - Yves-Marie Bozec
- School of Biological Sciences, University of Queensland, St. Lucia, Queensland, Australia
| | - Peter J Mumby
- School of Biological Sciences, University of Queensland, St. Lucia, Queensland, Australia
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21
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Lu J, Zeng L, Holford P, Beattie GAC, Wang Y. Discovery of Brassica Yellows Virus and Porcine Reproductive and Respiratory Syndrome Virus in Diaphorina citri and Changes in Virome Due to Infection with ' Ca. L. asiaticus'. Microbiol Spectr 2023; 11:e0499622. [PMID: 36943045 PMCID: PMC10100913 DOI: 10.1128/spectrum.04996-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 02/19/2023] [Indexed: 03/23/2023] Open
Abstract
Detection of new viruses or new virus hosts is essential for the protection of economically important agroecosystems and human health. Increasingly, metatranscriptomic data are being used to facilitate this process. Such data were obtained from adult Asian citrus psyllids (ACP) (Diaphorina citri Kuwayama) that fed solely on mandarin (Citrus ×aurantium L.) plants grafted with buds infected with 'Candidatus Liberibacter asiaticus' (CLas), a phloem-limited bacterium associated with the severe Asian variant of huanglongbing (HLB), the most destructive disease of citrus. Brassica yellows virus (BrYV), the causative agent of yellowing or leafroll symptoms in brassicaceous plants, and its associated RNA (named as BrYVaRNA) were detected in ACP. In addition, the porcine reproductive and respiratory syndrome virus (PRRSV), which affects pigs and is economically important to pig production, was also found in ACP. These viruses were not detected in insects feeding on plants grafted with CLas-free buds. Changes in the concentrations of insect-specific viruses within the psyllid were caused by coinfection with CLas. IMPORTANCE The cross transmission of pathogenic viruses between different farming systems or plant communities is a major threat to plants and animals and, potentially, human health. The use of metagenomics is an effective approach to discover viruses and vectors. Here, we collected buds from the CLas-infected and CLas-free mandarin (Citrus ×aurantium L. [Rutaceae: Aurantioideae: Aurantieae]) trees from a commercial orchard and grafted them onto CLas-free mandarin plants under laboratory conditions. Through metatranscriptome sequencing, we first identified the Asian citrus psyllids feeding on plants grafted with CLas-infected buds carried the plant pathogen, brassica yellows virus and its associated RNA, and the swine pathogen, porcine reproductive and respiratory syndrome virus. These discoveries indicate that both viruses can be transmitted by grafting and acquired by ACP from CLas+ mandarin seedlings.
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Affiliation(s)
- Jinming Lu
- College of Forestry and Biotechnology, Zhejiang A&F University, Linan, Hangzhou, Zhejiang, China
- College of Plant Protection, South China Agricultural University, Guangzhou, Guangdong, China
| | - Lixia Zeng
- College of Plant Protection, South China Agricultural University, Guangzhou, Guangdong, China
| | - Paul Holford
- School of Science, Western Sydney University, Penrith, New South Wales, Australia
| | - George A. C. Beattie
- School of Science, Western Sydney University, Penrith, New South Wales, Australia
| | - Yanjing Wang
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Advanced Agricultural Sciences, Zhejiang A&F University, Linan, Hangzhou, Zhejiang, China
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22
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Murali G, Iwamura T, Meiri S, Roll U. Future temperature extremes threaten land vertebrates. Nature 2023; 615:461-467. [PMID: 36653454 DOI: 10.1038/s41586-022-05606-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Accepted: 11/28/2022] [Indexed: 01/19/2023]
Abstract
The frequency, duration, and intensity of extreme thermal events are increasing and are projected to further increase by the end of the century1,2. Despite the considerable consequences of temperature extremes on biological systems3-8, we do not know which species and locations are most exposed worldwide. Here we provide a global assessment of land vertebrates' exposures to future extreme thermal events. We use daily maximum temperature data from 1950 to 2099 to quantify future exposure to high frequency, duration, and intensity of extreme thermal events to land vertebrates. Under a high greenhouse gas emission scenario (Shared Socioeconomic Pathway 5-8.5 (SSP5-8.5); 4.4 °C warmer world), 41.0% of all land vertebrates (31.1% mammals, 25.8% birds, 55.5% amphibians and 51.0% reptiles) will be exposed to extreme thermal events beyond their historical levels in at least half their distribution by 2099. Under intermediate-high (SSP3-7.0; 3.6 °C warmer world) and intermediate (SSP2-4.5; 2.7 °C warmer world) emission scenarios, estimates for all vertebrates are 28.8% and 15.1%, respectively. Importantly, a low-emission future (SSP1-2.6, 1.8 °C warmer world) will greatly reduce the overall exposure of vertebrates (6.1% of species) and can fully prevent exposure in many species assemblages. Mid-latitude assemblages (desert, shrubland, and grassland biomes), rather than tropics9,10, will face the most severe exposure to future extreme thermal events. By 2099, under SSP5-8.5, on average 3,773 species of land vertebrates (11.2%) will face extreme thermal events for more than half a year period. Overall, future extreme thermal events will force many species and assemblages into constant severe thermal stress. Deep greenhouse gas emissions cuts are urgently needed to limit species' exposure to thermal extremes.
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Affiliation(s)
- Gopal Murali
- Jacob Blaustein Center for Scientific Cooperation, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel.
- Mitrani Department of Desert Ecology, The Swiss Institute for Dryland Environments and Energy Research, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel.
| | - Takuya Iwamura
- Department F.-A. Forel for Aquatic and Environmental Sciences, Faculty of Science, University of Geneva, Geneva, Switzerland
- Department of Forest Ecosystems and Society, College of Forestry, Oregon State University, Corvallis, OR, USA
| | - Shai Meiri
- School of Zoology, Tel Aviv University, Tel Aviv, Israel
- The Steinhardt Museum of Natural History, Tel Aviv University, Tel Aviv, Israel
| | - Uri Roll
- Mitrani Department of Desert Ecology, The Swiss Institute for Dryland Environments and Energy Research, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel
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Sandoval-Martínez J, Badano EI, Guerra-Coss FA, Flores Cano JA, Flores J, Gelviz-Gelvez SM, Barragán-Torres F. Selecting tree species to restore forest under climate change conditions: Complementing species distribution models with field experimentation. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 329:117038. [PMID: 36528941 DOI: 10.1016/j.jenvman.2022.117038] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 12/09/2022] [Accepted: 12/12/2022] [Indexed: 06/17/2023]
Abstract
The long-term success of forest restoration programs can be improved using climate-based species distribution models (SDMs) to predict which tree species will tolerate climate change. However, as SDMs cannot estimate if species will recruit at these habitats, determining whether their predictions apply to early life-cycle stages of trees is critical to support such a usage. For this, we propose sowing seeds of the focal tree species under the current climate and simulated climate change conditions in target restoration sites. Thus, using of SDMs to design climate-adaptive forest restoration programs would be supported if the differences in habitat occupancy probabilities of species they predict between the current and future climate concurs with the observed differences in recruitment rates of species when sowed under the current climate and simulated climate change conditions. To test this hypothesis, we calibrated SDMs for Vachellia pennatula and Prosopis laevigata, two pioneer tree species widely recommended to restore human-degraded drylands in Mexico, and transferred them to climate change scenarios. After that, we applied the experimental approach proposed above to validate the predictions of SDMs. These models predicted that V. pennatula will decrease its habitat occupancy probabilities across Mexico, while P. laevigata was predicted to keep out their current habitat occupancy probabilities, or even increase them, in climate change scenarios. The results of the field experiment supported these predictions, as recruitment rates of V. pennatula were lower under simulated climate change than under the current climate, while no differences were found for the recruitment rates of P. laevigata between these environmental conditions. These findings demonstrate that SDMs provide meaningful insights for designing climate-adaptive forest restoration programs but, before applying this methodology, predictions of these models must be validated with field experiments to determine whether the focal tree species will recruit under climate change conditions. Moreover, as the pioneer trees used to test our proposal seem to be differentially sensitive to climate change, this approach also allows establishing what species must be prescribed to restore forests with a view to the future and what species must be avoided in these practices.
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Affiliation(s)
- Jesús Sandoval-Martínez
- IPICYT/División de Ciencias Ambientales, Instituto Potosino de Investigación Científica y Tecnológica, Camino a la Presa San José 2055, Colonia Lomas 4(a) Sección, 78216, San Luis Potosí, Mexico
| | - Ernesto I Badano
- IPICYT/División de Ciencias Ambientales, Instituto Potosino de Investigación Científica y Tecnológica, Camino a la Presa San José 2055, Colonia Lomas 4(a) Sección, 78216, San Luis Potosí, Mexico.
| | - Francisco A Guerra-Coss
- IPICYT/División de Ciencias Ambientales, Instituto Potosino de Investigación Científica y Tecnológica, Camino a la Presa San José 2055, Colonia Lomas 4(a) Sección, 78216, San Luis Potosí, Mexico
| | - Jorge A Flores Cano
- Facultad de Agronomía y Veterinaria, Universidad Autónoma de San Luis Potosí, Carretera San Luis - Matehuala Km. 14.5, Ejido Palma de la Cruz, 78321, Soledad de Graciano Sánchez, San Luis Potosí, Mexico
| | - Joel Flores
- IPICYT/División de Ciencias Ambientales, Instituto Potosino de Investigación Científica y Tecnológica, Camino a la Presa San José 2055, Colonia Lomas 4(a) Sección, 78216, San Luis Potosí, Mexico
| | - Sandra Milena Gelviz-Gelvez
- Instituto de Investigación de Zonas Desérticas, Universidad Autónoma de San Luis Potosí, De Altaïr 200, Colonia del Llano, 78377, San Luis Potosí, Mexico
| | - Felipe Barragán-Torres
- CONACYT-IPICYT/División de Ciencias Ambientales, Instituto Potosino de Investigación Científica y Tecnológica, Camino a la Presa San José 2055, Colonia Lomas 4a Sección, 78216, San Luis Potosí, Mexico
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24
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Data-driven predictions of the time remaining until critical global warming thresholds are reached. Proc Natl Acad Sci U S A 2023; 120:e2207183120. [PMID: 36716375 PMCID: PMC9963891 DOI: 10.1073/pnas.2207183120] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
Leveraging artificial neural networks (ANNs) trained on climate model output, we use the spatial pattern of historical temperature observations to predict the time until critical global warming thresholds are reached. Although no observations are used during the training, validation, or testing, the ANNs accurately predict the timing of historical global warming from maps of historical annual temperature. The central estimate for the 1.5 °C global warming threshold is between 2033 and 2035, including a ±1σ range of 2028 to 2039 in the Intermediate (SSP2-4.5) climate forcing scenario, consistent with previous assessments. However, our data-driven approach also suggests a substantial probability of exceeding the 2 °C threshold even in the Low (SSP1-2.6) climate forcing scenario. While there are limitations to our approach, our results suggest a higher likelihood of reaching 2 °C in the Low scenario than indicated in some previous assessments-though the possibility that 2 °C could be avoided is not ruled out. Explainable AI methods reveal that the ANNs focus on particular geographic regions to predict the time until the global threshold is reached. Our framework provides a unique, data-driven approach for quantifying the signal of climate change in historical observations and for constraining the uncertainty in climate model projections. Given the substantial existing evidence of accelerating risks to natural and human systems at 1.5 °C and 2 °C, our results provide further evidence for high-impact climate change over the next three decades.
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Grundner A, Beucler T, Gentine P, Iglesias‐Suarez F, Giorgetta MA, Eyring V. Deep Learning Based Cloud Cover Parameterization for ICON. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 2022; 14:e2021MS002959. [PMID: 37035630 PMCID: PMC10078328 DOI: 10.1029/2021ms002959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 11/18/2022] [Accepted: 12/05/2022] [Indexed: 06/19/2023]
Abstract
A promising approach to improve cloud parameterizations within climate models and thus climate projections is to use deep learning in combination with training data from storm-resolving model (SRM) simulations. The ICOsahedral Non-hydrostatic (ICON) modeling framework permits simulations ranging from numerical weather prediction to climate projections, making it an ideal target to develop neural network (NN) based parameterizations for sub-grid scale processes. Within the ICON framework, we train NN based cloud cover parameterizations with coarse-grained data based on realistic regional and global ICON SRM simulations. We set up three different types of NNs that differ in the degree of vertical locality they assume for diagnosing cloud cover from coarse-grained atmospheric state variables. The NNs accurately estimate sub-grid scale cloud cover from coarse-grained data that has similar geographical characteristics as their training data. Additionally, globally trained NNs can reproduce sub-grid scale cloud cover of the regional SRM simulation. Using the game-theory based interpretability library SHapley Additive exPlanations, we identify an overemphasis on specific humidity and cloud ice as the reason why our column-based NN cannot perfectly generalize from the global to the regional coarse-grained SRM data. The interpretability tool also helps visualize similarities and differences in feature importance between regionally and globally trained column-based NNs, and reveals a local relationship between their cloud cover predictions and the thermodynamic environment. Our results show the potential of deep learning to derive accurate yet interpretable cloud cover parameterizations from global SRMs, and suggest that neighborhood-based models may be a good compromise between accuracy and generalizability.
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Affiliation(s)
- Arthur Grundner
- Deutsches Zentrum für Luft‐ und Raumfahrt e.V. (DLR)Institut für Physik der AtmosphäreOberpfaffenhofenGermany
- Center for Learning the Earth with Artificial Intelligence and Physics (LEAP)Columbia UniversityNew YorkNYUSA
| | - Tom Beucler
- Institute of Earth Surface DynamicsUniversity of LausanneLausanneSwitzerland
| | - Pierre Gentine
- Center for Learning the Earth with Artificial Intelligence and Physics (LEAP)Columbia UniversityNew YorkNYUSA
| | - Fernando Iglesias‐Suarez
- Deutsches Zentrum für Luft‐ und Raumfahrt e.V. (DLR)Institut für Physik der AtmosphäreOberpfaffenhofenGermany
| | | | - Veronika Eyring
- Deutsches Zentrum für Luft‐ und Raumfahrt e.V. (DLR)Institut für Physik der AtmosphäreOberpfaffenhofenGermany
- University of BremenInstitute of Environmental Physics (IUP)BremenGermany
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26
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Mlynczak MG, Hunt LA, Garcia RR, Harvey VL, Marshall BT, Yue J, Mertens CJ, Russell JM. Cooling and Contraction of the Mesosphere and Lower Thermosphere From 2002 to 2021. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2022; 127:e2022JD036767. [PMID: 36582199 PMCID: PMC9786278 DOI: 10.1029/2022jd036767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 09/21/2022] [Accepted: 09/22/2022] [Indexed: 06/17/2023]
Abstract
We examine the thermal structure of the mesosphere and lower thermosphere (MLT) using observations from 2002 through 2021 from the SABER instrument on the NASA TIMED satellite. These observations show that the MLT has significantly cooled and contracted between the years 2002 and 2019 (the year of the most recent solar minimum) due to a combination of a decline in the intensity of the 11-year solar cycle and increasing carbon dioxide (CO2.) During this time the thickness of atmosphere between the 1 and 10-4 hPa pressure surfaces (approximately 48 and 105 km) has contracted by 1,333 m, of which 342 m is attributed to increasing CO2. All other pressure surfaces in the MLT have similarly contracted. We further postulate that the MLT in the two most recent solar minima (2008-2009 and 2019-2020) was very likely the coldest and thinnest since the beginning of the Industrial Age. The sensitivity of the MLT to a doubling of CO2 is shown to be -7.5 K based on observed trends in temperature and growth rates of CO2. Colder temperatures observed at 10-4 hPa in 2019 than in the prior solar minimum in 2009 may be due to a decrease of 5% in solar irradiance in the Schumann-Runge band spectral region (175-200 nm).
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Affiliation(s)
| | | | | | - V. Lynn Harvey
- Laboratory for Atmospheric and Space PhysicsUniversity of ColoradoBoulderCOUSA
| | | | - Jia Yue
- Catholic University of America/NASA Goddard Space Flight CenterGreenbeltMDUSA
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Evidence for massive methane hydrate destabilization during the penultimate interglacial warming. Proc Natl Acad Sci U S A 2022; 119:e2201871119. [PMID: 35994649 PMCID: PMC9436375 DOI: 10.1073/pnas.2201871119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Our results identify an exceptionally large warming of the equatorial Atlantic intermediate waters and strong evidence of methane release and oxidation almost certainly due to massive methane hydrate destabilization during the early part of the penultimate warm episode (126,000 to 125,000 y ago). This major warming was caused by reduced advection of cold water from high latitudes and enhanced downward heat diffusion in response to a brief episode of meltwater-induced weakening of the Atlantic meridional overturning circulation and amplified by a warm mean climate. Our results highlight climatic feedback processes associated with the penultimate climate warming that can serve as a paleoanalog for modern ongoing warming. The stability of widespread methane hydrates in shallow subsurface sediments of the marine continental margins is sensitive to temperature increases experienced by upper intermediate waters. Destabilization of methane hydrates and ensuing release of methane would produce climatic feedbacks amplifying and accelerating global warming. Hence, improved assessment of ongoing intermediate water warming is crucially important, especially that resulting from a weakening of Atlantic meridional overturning circulation (AMOC). Our study provides an independent paleoclimatic perspective by reconstructing the thermal structure and imprint of methane oxidation throughout a water column of 1,300 m. We studied a sediment sequence from the eastern equatorial Atlantic (Gulf of Guinea), a region containing abundant shallow subsurface methane hydrates. We focused on the early part of the penultimate interglacial and present a hitherto undocumented and remarkably large intermediate water warming of 6.8 °C in response to a brief episode of meltwater-induced, modest AMOC weakening centered at 126,000 to 125,000 y ago. The warming of intermediate waters to 14 °C significantly exceeds the stability field of methane hydrates. In conjunction with this warming, our study reveals an anomalously low δ13C spike throughout the entire water column, recorded as primary signatures in single and pooled shells of multitaxa foraminifers. This extremely negative δ13C excursion was almost certainly the result of massive destabilization of methane hydrates. This study documents and connects a sequence of climatic events and climatic feedback processes associated with and triggered by the penultimate climate warming that can serve as a paleoanalog for modern ongoing warming.
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Evaluation of CanESM Cloudiness, Cloud Type and Cloud Radiative Forcing Climatologies Using the CALIPSO-GOCCP and CERES Datasets. REMOTE SENSING 2022. [DOI: 10.3390/rs14153668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
In this study, the annual and seasonal climatology of cloud fraction (CF) and cloud type simulated by the Canadian Environmental System Models (CanESMs) version 5 (CanESM5) and version 2 (CanESM2) at their fully coupled and AMIP configurations were validated against the CALIPSO-GOCCP-based CF. The CFs produced using the CALIPSO-COSP simulator based on the CanESMs data at their atmospheric (AMIP) configuration are also evaluated. The simulated shortwave, longwave, and net cloud radiative forcing using the AMIP version of the CanESM5 were also validated against satellite observations based on the recent CERES radiation satellite products. On average, all models have a negative bias in the total CF with global mean biases (MBs) of 2%, 2.4%, 3.9%, 6.4,%, 5.6%, and 7.1% for the coupled-CanESM5, AMIP-CanESM5, COSP-AMIP-CanESM5, coupled-CanESM2, AMIP-CanESM2, and COSP-AMIP-CanESM2, respectively, indicating that the CanESM5 has a smaller MB. There were no significant differences between AMIP and coupled versions of the model, but the COSP-based model-simulated data showed larger biases. Although the models captured well the climatological features of CF, they also exhibited a significant bias in CF reaching up to 40% over some geographical locations. This is particularly prevalent over the low level (LL) marine stratocumulus/cumulus, convectively active tropical latitudes that are normally dominated by high level (HL) clouds and at the polar regions where all models showed negative, positive, and positive bias corresponding to these locations, respectively. The AMIP-CanESM5 model performed reasonably well simulating the global mean cloud radiative forcing (CRF) with slight negative biases in the NetCRF at the TOA and surface that would be expected if the model has a positive bias in CF. This inconsistent result may be attributed to the parameterization of the optical properties in the model. The geographical distributions of the model bias in the NetCRF, however, can be significant reaching up to ±40 Wm−2 depending on the location and atmospheric level. The Pearson correlation showed that there is a strong correlation between the global distribution of model bias in NetCRF and CF and it is significantly influenced by the LL and HL clouds.
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29
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Analysis of Future Meteorological Drought Changes in the Yellow River Basin under Climate Change. WATER 2022. [DOI: 10.3390/w14121896] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The Yellow River Basin is an important economic belt and key ecological reservation area in China. In the context of global warming, it is of great significance to project the drought disaster risk for ensuring water security and improving water resources management measures in practice. Based on the five Global Climate Models (GCMs) projections under three scenarios of the Shared Socioeconomic Pathways (SSP) (SSP126, SSP245, SSP585) released in the Sixth Coupled Model Intercomparison Project (CMIP6), this study analyzed the characteristics of meteorological drought in the Yellow River Basin in combination with SPEI indicators over 2015–2100. The result indicated that: (1) The GCMs from CMIP6 after bias correction performed better in reproducing the spatial and temporal variation of precipitation. The precipitation in the Yellow River Basin may exhibit increase trends from 2015 to 2100, especially under the SSP585 scenario. (2) The characteristics of meteorological drought in the Yellow River Basin varied from different combination scenarios. Under the SSP126 scenario, the meteorological drought will gradually intensify from 2040 to 2099, while the drought intensity under SSP245 and SSP585 scenarios will likely be higher than SSP126. (3) The spatial variation of meteorological drought in the Yellow River Basin is heterogeneous and uncertain in different combination scenarios and periods. The drought tendency in the Loess Plateau will increase significantly in the future, and the drought frequency and duration in the main water conservation areas of the Yellow River Basin was projected to increase.
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Chen Z, Zhou T, Chen X, Zhang W, Zhang L, Wu M, Zou L. Observationally constrained projection of Afro-Asian monsoon precipitation. Nat Commun 2022; 13:2552. [PMID: 35538080 PMCID: PMC9090792 DOI: 10.1038/s41467-022-30106-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 04/06/2022] [Indexed: 11/09/2022] Open
Abstract
The Afro-Asian summer monsoon (AfroASM) sustains billions of people living in many developing countries covering West Africa and Asia, vulnerable to climate change. Future increase in AfroASM precipitation has been projected by current state-of-the-art climate models, but large inter-model spread exists. Here we show that the projection spread is related to present-day interhemispheric thermal contrast (ITC). Based on 30 models from the Coupled Model Intercomparison Project Phase 6, we find models with a larger ITC trend during 1981-2014 tend to project a greater precipitation increase. Since most models overestimate present-day ITC trends, emergent constraint indicates precipitation increase in constrained projection is reduced to 70% of the raw projection, with the largest reduction in West Africa (49%). The land area experiencing significant increases of precipitation (runoff) is 57% (66%) of the raw projection. Smaller increases of precipitation will likely reduce flooding risk, while posing a challenge to future water resources management.
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Affiliation(s)
- Ziming Chen
- State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, 100029, Beijing, China
- University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Tianjun Zhou
- State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, 100029, Beijing, China.
- University of Chinese Academy of Sciences, 100049, Beijing, China.
- CAS Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences (CAS), Beijing, China.
| | - Xiaolong Chen
- State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, 100029, Beijing, China
- CAS Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences (CAS), Beijing, China
| | - Wenxia Zhang
- State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, 100029, Beijing, China
| | - Lixia Zhang
- State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, 100029, Beijing, China
- CAS Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences (CAS), Beijing, China
| | - Mingna Wu
- State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, 100029, Beijing, China
- University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Liwei Zou
- State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, 100029, Beijing, China
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Sandoval-Martínez J, Flores-Cano JA, Badano EI. Recruitment of pioneer trees with physically dormant seeds under climate change: the case of Vachellia pennatula (Fabaceae) in semiarid environments of Mexico. JOURNAL OF PLANT RESEARCH 2022; 135:453-463. [PMID: 35226225 DOI: 10.1007/s10265-022-01383-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 02/17/2022] [Indexed: 06/14/2023]
Abstract
Most tree species native to arid and semiarid ecosystems produce seeds with physical dormancy, which have impermeable coats that protect them from desiccation and prevent germination when the environmental conditions are unfavorable for seedling establishment. This dormancy mechanism may confer some degree of tolerance to seeds facing warmer and drier conditions, as those expected in several regions of the world because of climate change. Scarification of these seeds (removal of protective coats) is required for stimulating germination and seedling development. However, as scarification exposes seeds to the external environmental conditions, it can promote desiccation and viability loss in the future. To test these hypotheses, we performed field experiments and sowed scarified and unscarified seeds of a pioneer tree native to semiarid ecosystems of Mesoamerica (Vachellia pennatula) under the current climate and simulated climate change conditions. The experiments were conducted at abandoned fields using open-top chambers to increase temperature and rainout shelters to reduce rainfall. We measured microenvironmental conditions within the experimental plots and monitored seedling emergence and survival during a year. Air temperature and rainfall in climate change simulations approached the values expected for the period 2041-2080. Seedling emergence rates under these climatic conditions were lower than under the current climate. Nevertheless, emergence rates in climate change simulations were even lower for scarified than for unscarified seeds, while the converse occurred under the current climate. On the other hand, although survival rates in climate change simulations were lower than under the current climate, no effects of the scarification treatment were found. In this way, our study suggests that climate change will impair the recruitment of pioneer trees in semiarid environments, even if they produce seeds with physical dormancy, but also indicates that these negative effects will be stronger if seeds are scarified.
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Affiliation(s)
- Jesús Sandoval-Martínez
- IPICYT/División de Ciencias Ambientales, Instituto Potosino de Investigación Científica Y Tecnológica, Camino a la Presa San José 2055, Colonia Lomas 4ª Sección, 78216, San Luis Potosí, SLP, México
| | - Jorge A Flores-Cano
- Facultad de Agronomía y Veterinaria, Universidad Autónoma de San Luis Potosí, Km. 14.5 Carretera San Luis-Matehuala, 78321, Soledad de Graciano Sánchez, SLP, México
| | - Ernesto I Badano
- IPICYT/División de Ciencias Ambientales, Instituto Potosino de Investigación Científica Y Tecnológica, Camino a la Presa San José 2055, Colonia Lomas 4ª Sección, 78216, San Luis Potosí, SLP, México.
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Siller-Clavel P, Badano EI, Villarreal-Guerrero F, Prieto-Amparán JA, Pinedo-Alvarez A, Corrales-Lerma R, Álvarez-Holguín A, Hernández-Quiroz NS. Distribution Patterns of Invasive Buffelgrass (Cenchrus ciliaris) in Mexico Estimated with Climate Niche Models under the Current and Future Climate. PLANTS 2022; 11:plants11091160. [PMID: 35567161 PMCID: PMC9100534 DOI: 10.3390/plants11091160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 04/01/2022] [Accepted: 04/18/2022] [Indexed: 11/24/2022]
Abstract
In Mexico, buffelgrass (Cenchrus ciliaris) was introduced in the middle of the 20th century. Currently, buffelgrass has become an invasive species and has colonized various ecosystems in the country. In addition to its invasive capacity, climate change is a factor that has to be taken into account when considering how to effectively manage and control this species. The climatic niche models (CNM) and their projections for climate change scenarios allow for estimating the extent of biological invasions. Our study aimed to calibrate a CNM for buffelgrass in Mexico under the current climatic conditions and to project the extent of its biological invasion under climate change scenarios. For that, we used MaxEnt to generate the current CNM and to detect if climate change could cause future changes, we then evaluated the distribution patterns over the periods of 2041–2060, 2061–2080, and 2081–2100 for all the shared socioeconomic pathways (SSPs). Linear regressions were used to compare the outputs between current and future scenarios. Under the current climate, the CNM estimated that 42.2% of the continental surface of Mexico is highly suitable for buffelgrass. The regression analyses indicated no effects from climate change on the distribution of buffelgrass. Moreover, when the projected period is further in the future, and when the SSPs intensify, the surface of suitable areas for the species increases. These analyses clearly suggest Mexico is facing a biological invasion from buffelgrass, which may represent a threat to native biodiversity.
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Affiliation(s)
- Pablo Siller-Clavel
- Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Periférico Francisco R. Almada km. 1, Chihuahua 31453, Mexico; (P.S.-C.); (F.V.-G.); (J.A.P.-A.); (A.P.-A.); (R.C.-L.)
| | - Ernesto I. Badano
- IPICYT División de Ciencias Ambientales, Instituto Potosino de Investigación Científica y Tecnológica, Camino a la Presa San José 2055, Colonia Lomas 4a Sección, San Luis Potosí 78216, SLP, Mexico;
| | - Federico Villarreal-Guerrero
- Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Periférico Francisco R. Almada km. 1, Chihuahua 31453, Mexico; (P.S.-C.); (F.V.-G.); (J.A.P.-A.); (A.P.-A.); (R.C.-L.)
| | - Jesús A. Prieto-Amparán
- Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Periférico Francisco R. Almada km. 1, Chihuahua 31453, Mexico; (P.S.-C.); (F.V.-G.); (J.A.P.-A.); (A.P.-A.); (R.C.-L.)
| | - Alfredo Pinedo-Alvarez
- Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Periférico Francisco R. Almada km. 1, Chihuahua 31453, Mexico; (P.S.-C.); (F.V.-G.); (J.A.P.-A.); (A.P.-A.); (R.C.-L.)
| | - Raúl Corrales-Lerma
- Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Periférico Francisco R. Almada km. 1, Chihuahua 31453, Mexico; (P.S.-C.); (F.V.-G.); (J.A.P.-A.); (A.P.-A.); (R.C.-L.)
| | - Alan Álvarez-Holguín
- Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP), Campo Experimental La Campana, Carretera Chihuahua-Ojinaga km. 33.3, Aldama 32190, Mexico;
| | - Nathalie S. Hernández-Quiroz
- Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Periférico Francisco R. Almada km. 1, Chihuahua 31453, Mexico; (P.S.-C.); (F.V.-G.); (J.A.P.-A.); (A.P.-A.); (R.C.-L.)
- Correspondence: ; Tel.: +52-614-1392269
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Timmermann A, Yun KS, Raia P, Ruan J, Mondanaro A, Zeller E, Zollikofer C, Ponce de León M, Lemmon D, Willeit M, Ganopolski A. Climate effects on archaic human habitats and species successions. Nature 2022; 604:495-501. [PMID: 35418680 PMCID: PMC9021022 DOI: 10.1038/s41586-022-04600-9] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Accepted: 03/01/2022] [Indexed: 01/02/2023]
Abstract
It has long been believed that climate shifts during the last 2 million years had a pivotal role in the evolution of our genus Homo1–3. However, given the limited number of representative palaeo-climate datasets from regions of anthropological interest, it has remained challenging to quantify this linkage. Here, we use an unprecedented transient Pleistocene coupled general circulation model simulation in combination with an extensive compilation of fossil and archaeological records to study the spatiotemporal habitat suitability for five hominin species over the past 2 million years. We show that astronomically forced changes in temperature, rainfall and terrestrial net primary production had a major impact on the observed distributions of these species. During the Early Pleistocene, hominins settled primarily in environments with weak orbital-scale climate variability. This behaviour changed substantially after the mid-Pleistocene transition, when archaic humans became global wanderers who adapted to a wide range of spatial climatic gradients. Analysis of the simulated hominin habitat overlap from approximately 300–400 thousand years ago further suggests that antiphased climate disruptions in southern Africa and Eurasia contributed to the evolutionary transformation of Homo heidelbergensis populations into Homo sapiens and Neanderthals, respectively. Our robust numerical simulations of climate-induced habitat changes provide a framework to test hypotheses on our human origin. A new model simulation of climate change during the past 2 million years indicates that the appearances and disappearances of hominin species correlate with long-term climatic anomalies.
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Affiliation(s)
- Axel Timmermann
- Center for Climate Physics, Institute for Basic Science, Busan, South Korea. .,Pusan National University, Busan, South Korea.
| | - Kyung-Sook Yun
- Center for Climate Physics, Institute for Basic Science, Busan, South Korea.,Pusan National University, Busan, South Korea
| | - Pasquale Raia
- DiSTAR, Università di Napoli Federico II, Monte Sant'Angelo, Naples, Italy
| | - Jiaoyang Ruan
- Center for Climate Physics, Institute for Basic Science, Busan, South Korea.,Pusan National University, Busan, South Korea
| | | | - Elke Zeller
- Center for Climate Physics, Institute for Basic Science, Busan, South Korea.,Pusan National University, Busan, South Korea
| | | | | | - Danielle Lemmon
- Center for Climate Physics, Institute for Basic Science, Busan, South Korea.,Pusan National University, Busan, South Korea
| | - Matteo Willeit
- Potsdam Institute for Climate Impact Research, Potsdam, Germany
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Koldasbayeva D, Tregubova P, Shadrin D, Gasanov M, Pukalchik M. Large-scale forecasting of Heracleum sosnowskyi habitat suitability under the climate change on publicly available data. Sci Rep 2022; 12:6128. [PMID: 35414080 PMCID: PMC9005721 DOI: 10.1038/s41598-022-09953-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 03/30/2022] [Indexed: 01/18/2023] Open
Abstract
This research aims to establish the possible habitat suitability of Heracleum sosnowskyi (HS), one of the most aggressive invasive plants, in current and future climate conditions across the territory of the European part of Russia. We utilised a species distribution modelling framework using publicly available data of plant occurrence collected in citizen science projects (CSP). Climatic variables and soil characteristics were considered to follow possible dependencies with environmental factors. We applied Random Forest to classify the study area. We addressed the problem of sampling bias in CSP data by optimising the sampling size and implementing a spatial cross-validation scheme. According to the Random Forest model built on the finally selected data shape, more than half of the studied territory in the current climate corresponds to a suitability prediction score higher than 0.25. The forecast of habitat suitability in future climate was highly similar for all climate models. Almost the whole studied territory showed the possibility for spread with an average suitability score of 0.4. The mean temperature of the wettest quarter and precipitation of wettest month demonstrated the highest influence on the HS distribution. Thus, currently, the whole study area, excluding the north, may be considered as s territory with a high risk of HS spreading, while in the future suitable locations for the HS habitat will include high latitudes. We showed that chosen geodata pre-processing, and cross-validation based on geospatial blocks reduced significantly the sampling bias. Obtained predictions could help to assess the risks accompanying the studied plant invasion capturing the patterns of the spread, and can be used for the conservation actions planning.
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Affiliation(s)
- Diana Koldasbayeva
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russian Federation, 121205.
| | - Polina Tregubova
- RAIC, Skolkovo Institute of Science and Technology, Moscow, Russian Federation, 121205
| | - Dmitrii Shadrin
- RAIC, Skolkovo Institute of Science and Technology, Moscow, Russian Federation, 121205.,Irkutsk National Research Technical University, Irkutsk, Russian Federation, 664074
| | - Mikhail Gasanov
- RAIC, Skolkovo Institute of Science and Technology, Moscow, Russian Federation, 121205
| | - Maria Pukalchik
- Digital Agriculture Laboratory, Skolkovo Institute of Science and Technology, Moscow, Russian Federation, 121205
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35
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Warren WS. Earning the public's trust. SCIENCE ADVANCES 2022; 8:eabo6347. [PMID: 35263145 PMCID: PMC11323826 DOI: 10.1126/sciadv.abo6347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 02/16/2022] [Indexed: 06/14/2023]
Affiliation(s)
- Warren S Warren
- Warren S. Warren, Deputy Editor, Science Advances, James B. Duke Professor at Duke University.
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36
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Evaluations of the Climatologies of Three Latest Cloud Satellite Products Based on Passive Sensors (ISCCP-H, Two CERES) against the CALIPSO-GOCCP. REMOTE SENSING 2021. [DOI: 10.3390/rs13245150] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
In this study, the climatologies of three different satellite cloud products, all based on passive sensors (CERES Edition 4.1 [EBAF4.1 and SYN4.1] and ISCCP–H), were evaluated against the CALIPSO-GOCCP (GOCCP) data, which are based on active sensors and, hence, were treated as the reference. Based on monthly averaged data (ocean + land), the passive sensors underestimated the total cloud cover (TCC) at lower (TCC < 50%), but, overall, they correlated well with the GOCCP data (r = 0.97). Over land, the passive sensors underestimated the TCC, with a mean difference (MD) of −2.6%, followed by the EBAF4.1 and ISCCP-H data with a MD of −2.0%. Over the ocean, the CERES-based products overestimated the TCC, but the SYN4.1 agreed better with the GOCCP data. The ISCCP-H data on average underestimated the TCC both over oceanic and continental regions. The annual mean TCC distribution over the globe revealed that the passive sensors generally underestimated the TCC over continental dry regions in northern Africa and southeastern South America as compared to the GOCCP, particularly over the summer hemisphere. The CERES datasets overestimated the TCC over the Pacific Islands between the Indian and eastern Pacific Oceans, particularly during the winter hemisphere. The ISCCP-H data also underestimated the TCC, particularly over the southern hemisphere near 60° S where the other datasets showed a significantly enhanced TCC. The ISCCP data also showed less TCC when compared against the GOCCP data over the tropical regions, particularly over the southern Pacific and Atlantic Oceans near the equator and also over the polar regions where the satellite retrieval using the passive sensors was generally much more challenging. The calculated global mean root meant square deviation value for the ISCCP-H data was 6%, a factor of 2 higher than the CERES datasets. Based on these results, overall, the EBAF4.1 agreed better with the GOCCP data.
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Kong Y, Zhao Z, Wang Y, Yang S, Huang G, Wang Y, Liu C, You C, Tan J, Wang C, Xu B, Cui J, Liu X, Mei Y. Integration of a Metal-Organic Framework Film with a Tubular Whispering-Gallery-Mode Microcavity for Effective CO 2 Sensing. ACS APPLIED MATERIALS & INTERFACES 2021; 13:58104-58113. [PMID: 34809420 DOI: 10.1021/acsami.1c16322] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Carbon dioxide (CO2) sensing using an optical technique is of great importance in the environment and industrial emission monitoring. However, limited by the poor specific adsorption of gas molecules as well as insufficient coupling efficiency, there is still a long way to go toward realizing a highly sensitive optical CO2 gas sensor. Herein, by combining the advantages of a whispering-gallery-mode microcavity and a metal-organic framework (MOF) film, a porous functional microcavity (PF-MC) was fabricated with the assistance of the atomic layer deposition technique and was applied to CO2 sensing. In this functional composite, the rolled-up microcavity provides the ability to tune the propagation of light waves and the electromagnetic coupling with the surroundings via an evanescent field, while the nanoporous MOF film contributes to the specific adsorption of CO2. The composite demonstrates a high sensitivity of 188 nm RIU-1 (7.4 pm/% with respect to the CO2 concentration) and a low detection limit of ∼5.85 × 10-5 RIU. Furthermore, the PF-MC exhibits great selectivity to CO2 and outstanding reproducibility, which is promising for the next-generation optical gas sensing devices.
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Affiliation(s)
- Ye Kong
- Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
- International Institute for Intelligent Nanorobots and Nanosystems, Fudan University, Shanghai 200438, P. R. China
| | - Zhe Zhao
- Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
- International Institute for Intelligent Nanorobots and Nanosystems, Fudan University, Shanghai 200438, P. R. China
| | - Yunqi Wang
- Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
- International Institute for Intelligent Nanorobots and Nanosystems, Fudan University, Shanghai 200438, P. R. China
| | - Shuo Yang
- Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
- International Institute for Intelligent Nanorobots and Nanosystems, Fudan University, Shanghai 200438, P. R. China
| | - Gaoshan Huang
- Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
- International Institute for Intelligent Nanorobots and Nanosystems, Fudan University, Shanghai 200438, P. R. China
- Yiwu Research Institute of Fudan University, Yiwu 322000, Zhejiang, P. R. China
| | - Yang Wang
- Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
- International Institute for Intelligent Nanorobots and Nanosystems, Fudan University, Shanghai 200438, P. R. China
| | - Chang Liu
- Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
- International Institute for Intelligent Nanorobots and Nanosystems, Fudan University, Shanghai 200438, P. R. China
| | - Chunyu You
- Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
- International Institute for Intelligent Nanorobots and Nanosystems, Fudan University, Shanghai 200438, P. R. China
| | - Ji Tan
- State Key Laboratory of High Performance Ceramics and Superfine Microstructure, Shanghai Institute of Ceramics, Chinese Academy of Sciences, Shanghai 200050, P. R. China
| | - Chao Wang
- Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
| | - Borui Xu
- Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
- Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception, Institute of Optoelectronics, Fudan University, Shanghai 200438, P. R. China
- Yiwu Research Institute of Fudan University, Yiwu 322000, Zhejiang, P. R. China
| | - Jizhai Cui
- Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
- International Institute for Intelligent Nanorobots and Nanosystems, Fudan University, Shanghai 200438, P. R. China
- Yiwu Research Institute of Fudan University, Yiwu 322000, Zhejiang, P. R. China
| | - Xuanyong Liu
- State Key Laboratory of High Performance Ceramics and Superfine Microstructure, Shanghai Institute of Ceramics, Chinese Academy of Sciences, Shanghai 200050, P. R. China
| | - Yongfeng Mei
- Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
- International Institute for Intelligent Nanorobots and Nanosystems, Fudan University, Shanghai 200438, P. R. China
- Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception, Institute of Optoelectronics, Fudan University, Shanghai 200438, P. R. China
- Yiwu Research Institute of Fudan University, Yiwu 322000, Zhejiang, P. R. China
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38
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Abernethy S, O'Connor FM, Jones CD, Jackson RB. Methane removal and the proportional reductions in surface temperature and ozone. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2021; 379:20210104. [PMID: 34565218 PMCID: PMC8473947 DOI: 10.1098/rsta.2021.0104] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 06/02/2021] [Indexed: 05/22/2023]
Abstract
Mitigating climate change requires a diverse portfolio of technologies and approaches, including negative emissions or removal of greenhouse gases. Previous literature focuses primarily on carbon dioxide removal, but methane removal may be an important complement to future efforts. Methane removal has at least two key benefits: reducing temperature more rapidly than carbon dioxide removal and improving air quality by reducing surface ozone concentration. While some removal technologies are being developed, modelling of their impacts is limited. Here, we conduct the first simulations using a methane emissions-driven Earth System Model to quantify the climate and air quality co-benefits of methane removal, including different rates and timings of removal. We define a novel metric, the effective cumulative removal, and use it to show that each effective petagram of methane removed causes a mean global surface temperature reduction of 0.21 ± 0.04°C and a mean global surface ozone reduction of 1.0 ± 0.2 parts per billion. Our results demonstrate the effectiveness of methane removal in delaying warming thresholds and reducing peak temperatures, and also allow for direct comparisons between the impacts of methane and carbon dioxide removal that could guide future research and climate policy. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'.
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Affiliation(s)
- S. Abernethy
- Department of Applied Physics, Stanford University, Stanford 94305, USA
- Department of Earth System Science, Stanford University, Stanford 94305, USA
| | - F. M. O'Connor
- Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3PB, UK
| | - C. D. Jones
- Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3PB, UK
| | - R. B. Jackson
- Department of Earth System Science, Stanford University, Stanford 94305, USA
- Woods Institute for the Environment and Precourt Institute for Energy, Stanford University, Stanford 94305, USA
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39
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Jägermeyr J, Müller C, Ruane AC, Elliott J, Balkovic J, Castillo O, Faye B, Foster I, Folberth C, Franke JA, Fuchs K, Guarin JR, Heinke J, Hoogenboom G, Iizumi T, Jain AK, Kelly D, Khabarov N, Lange S, Lin TS, Liu W, Mialyk O, Minoli S, Moyer EJ, Okada M, Phillips M, Porter C, Rabin SS, Scheer C, Schneider JM, Schyns JF, Skalsky R, Smerald A, Stella T, Stephens H, Webber H, Zabel F, Rosenzweig C. Climate impacts on global agriculture emerge earlier in new generation of climate and crop models. NATURE FOOD 2021; 2:873-885. [PMID: 37117503 DOI: 10.1038/s43016-021-00400-y] [Citation(s) in RCA: 90] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 09/29/2021] [Indexed: 04/30/2023]
Abstract
Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project's Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to -6% (SSP126) and from +1% to -24% (SSP585)-explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO2 concentrations and expanded high-latitude gains. The 'emergence' of climate impacts consistently occurs earlier in the new projections-before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.
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Affiliation(s)
- Jonas Jägermeyr
- NASA Goddard Institute for Space Studies, New York, NY, USA.
- Columbia University, Center for Climate Systems Research, New York, NY, USA.
- Potsdam Institute for Climate Impacts Research (PIK), Member of the Leibniz Association, Potsdam, Germany.
| | - Christoph Müller
- Potsdam Institute for Climate Impacts Research (PIK), Member of the Leibniz Association, Potsdam, Germany
| | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, NY, USA
| | - Joshua Elliott
- Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, USA
| | - Juraj Balkovic
- International Institute for Applied Systems Analysis, Laxenburg, Austria
- Faculty of Natural Sciences, Comenius University in Bratislava, Bratislava, Slovak Republic
| | - Oscar Castillo
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, FL, USA
| | - Babacar Faye
- Institut de recherche pour le développement (IRD) ESPACE-DEV, Montpellier, France
| | - Ian Foster
- Department of Computer Science, University of Chicago, Chicago, IL, USA
| | - Christian Folberth
- International Institute for Applied Systems Analysis, Laxenburg, Austria
| | - James A Franke
- Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, USA
- Department of the Geophysical Sciences, University of Chicago, Chicago, IL, USA
| | - Kathrin Fuchs
- Institute of Meteorology and Climate Research, Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
| | - Jose R Guarin
- NASA Goddard Institute for Space Studies, New York, NY, USA
- Columbia University, Center for Climate Systems Research, New York, NY, USA
| | - Jens Heinke
- Potsdam Institute for Climate Impacts Research (PIK), Member of the Leibniz Association, Potsdam, Germany
| | - Gerrit Hoogenboom
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, FL, USA
- Institute for Sustainable Food Systems, University of Florida, Gainesville, FL, USA
| | - Toshichika Iizumi
- Institute for Agro-Environmental Sciences, National Agriculture and Food Research Organization, Tsukuba, Japan
| | - Atul K Jain
- Department of Atmospheric Sciences, University of Illinois, Urbana, IL, USA
| | - David Kelly
- Department of Computer Science, University of Chicago, Chicago, IL, USA
| | - Nikolay Khabarov
- International Institute for Applied Systems Analysis, Laxenburg, Austria
| | - Stefan Lange
- Potsdam Institute for Climate Impacts Research (PIK), Member of the Leibniz Association, Potsdam, Germany
| | - Tzu-Shun Lin
- Department of Atmospheric Sciences, University of Illinois, Urbana, IL, USA
| | - Wenfeng Liu
- Center for Agricultural Water Research in China, College of Water Resources and Civil Engineering, China Agricultural University, Beijing, China
| | - Oleksandr Mialyk
- Multidisciplinary Water Management group, University of Twente, Enschede, Netherlands
| | - Sara Minoli
- Potsdam Institute for Climate Impacts Research (PIK), Member of the Leibniz Association, Potsdam, Germany
| | - Elisabeth J Moyer
- Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, USA
- Department of the Geophysical Sciences, University of Chicago, Chicago, IL, USA
| | - Masashi Okada
- Center for Climate Change Adaptation, National Institute for Environmental Studies, Tsukuba, Japan
| | - Meridel Phillips
- NASA Goddard Institute for Space Studies, New York, NY, USA
- Columbia University, Center for Climate Systems Research, New York, NY, USA
| | - Cheryl Porter
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, FL, USA
| | - Sam S Rabin
- Institute of Meteorology and Climate Research, Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
- Department of Environmental Sciences, Rutgers University, New Brunswick, NJ, USA
| | - Clemens Scheer
- Institute of Meteorology and Climate Research, Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
| | | | - Joep F Schyns
- Multidisciplinary Water Management group, University of Twente, Enschede, Netherlands
| | - Rastislav Skalsky
- International Institute for Applied Systems Analysis, Laxenburg, Austria
- Soil Science and Conservation Research Institute, National Agricultural and Food Centre, Bratislava, Slovak Republic
| | - Andrew Smerald
- Institute of Meteorology and Climate Research, Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
| | - Tommaso Stella
- Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
| | - Haynes Stephens
- Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, USA
- Department of the Geophysical Sciences, University of Chicago, Chicago, IL, USA
| | - Heidi Webber
- Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
| | - Florian Zabel
- Ludwig-Maximilians-Universität München (LMU), Munich, Germany
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Liu M, Vecchi G, Soden B, Yang W, Zhang B. Enhanced hydrological cycle increases ocean heat uptake and moderates transient climate change. NATURE CLIMATE CHANGE 2021; 11:848-853. [PMID: 34777581 PMCID: PMC8587804 DOI: 10.1038/s41558-021-01152-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 08/12/2021] [Indexed: 06/13/2023]
Abstract
The large-scale moistening of the atmosphere in response to increasing greenhouse gases amplifies the existing patterns of precipitation minus evaporation (P-E) which, in turn, amplifies the spatial contrast in sea surface salinity (SSS). Through a series of transient CO2 doubling experiments, we demonstrate that surface salinification driven by the amplified dry conditions (P-E < 0), primarily in the subtropical ocean, accelerates ocean heat uptake. The salinification also drives the sequestration of upper-level heat into the deeper ocean, reducing the thermal stratification and increasing the heat uptake through a positive feedback. The change in Atlantic Meridional Overturning Circulation due to salinification plays a secondary role in heat uptake. Consistent with the heat uptake changes, the transient climate response would increase by approximately 0.4 K without this process. Observed multi-decadal changes in subsurface temperature and salinity resembles those simulated, indicating that anthropogenically-forced changes in salinity are likely enhancing the ocean heat uptake.
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Affiliation(s)
- Maofeng Liu
- Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL
| | - Gabriel Vecchi
- Department of Geosciences, Princeton University, Princeton, NJ
- Princeton Environmental Institute, Princeton University, Princeton, NJ
| | - Brian Soden
- Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL
| | - Wenchang Yang
- Department of Geosciences, Princeton University, Princeton, NJ
| | - Bosong Zhang
- Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL
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Wobus C, Porter J, Lorie M, Martinich J, Bash R. Climate change, riverine flood risk and adaptation for the conterminous United States. ENVIRONMENTAL RESEARCH LETTERS : ERL [WEB SITE] 2021; 16:10.1088/1748-9326/ac1bd7. [PMID: 34567238 PMCID: PMC8459676 DOI: 10.1088/1748-9326/ac1bd7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Riverine floods are among the most costly natural disasters in the United States, and floods are generally projected to increase in frequency and magnitude with climate change. Faced with these increasing risks, improved information is needed to direct limited resources toward the most cost-effective adaptation actions available. Here we leverage a newly available flood risk dataset for residential properties in the conterminous United States to calculate expected annual damages to residential structures from inland/riverine flooding at a property-level; the cost of property-level adaptations to protect against future flood risk; and the benefits of those adaptation investments assuming both static and changing climate conditions. Our modeling projects that in the absence of adaptation, nationwide damages from riverine flooding will increase by 20-30% under high levels of warming. Floodproofing, elevation and property acquisition can each be cost-effective adaptations in certain situations, depending on the desired return on investment (i.e., benefit cost ratio), the discount rate, and the assumed rate of climate change. Incorporation of climate change into the benefit-cost calculation increases the number of properties meeting any specified benefit-cost threshold, as today's investments protect against an increasing frequency of future floods. However, because future expected damages are discounted relative to present-day, the adaptation decisions made based on a static climate assumption are very similar to the decisions made when climate change is considered. If the goal is to optimize adaptation decision making, a focus on quantifying present-day flood risk is therefore at least as important as understanding how those risks might change under a warming climate.
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42
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Towards neural Earth system modelling by integrating artificial intelligence in Earth system science. NAT MACH INTELL 2021. [DOI: 10.1038/s42256-021-00374-3] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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43
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Sellevold R, Vizcaino M. First Application of Artificial Neural Networks to Estimate 21st Century Greenland Ice Sheet Surface Melt. GEOPHYSICAL RESEARCH LETTERS 2021; 48:e2021GL092449. [PMID: 35866045 PMCID: PMC9285918 DOI: 10.1029/2021gl092449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 07/08/2021] [Accepted: 07/26/2021] [Indexed: 06/15/2023]
Abstract
Future Greenland ice sheet (GrIS) melt projections are limited by the lack of explicit melt calculations within most global climate models and the high computational cost of dynamical downscaling with regional climate models (RCMs). Here, we train artificial neural networks (ANNs) to obtain relationships between quantities consistently available from global climate model simulations and annually integrated GrIS surface melt. To this end, we train the ANNs with model output from the Community Earth System Model 2.1 (CESM2), which features an interactive surface melt calculation based on a downscaled surface energy balance. We find that ANNs compare well with an independent CESM2 simulation and RCM simulations forced by a CMIP6 subset. The ANNs estimate a melt increase for 2,081-2,100 ranging from 414 ± 275 Gt y r - 1 (SSP1-2.6) to 1,378 ± 555 Gt y r - 1 (SSP5-8.5) for the full CMIP6 suite. The primary source of uncertainty throughout the 21st century is the spread of climate model sensitivity.
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Affiliation(s)
- Raymond Sellevold
- Geoscience and Remote SensingDelft University of TechnologyDelftThe Netherlands
| | - Miren Vizcaino
- Geoscience and Remote SensingDelft University of TechnologyDelftThe Netherlands
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44
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Fyfe JC, Kharin VV, Santer BD, Cole JNS, Gillett NP. Significant impact of forcing uncertainty in a large ensemble of climate model simulations. Proc Natl Acad Sci U S A 2021; 118:e2016549118. [PMID: 34074753 PMCID: PMC8202018 DOI: 10.1073/pnas.2016549118] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Forcing due to solar and volcanic variability, on the natural side, and greenhouse gas and aerosol emissions, on the anthropogenic side, are the main inputs to climate models. Reliable climate model simulations of past and future climate change depend crucially upon them. Here we analyze large ensembles of simulations using a comprehensive Earth System Model to quantify uncertainties in global climate change attributable to differences in prescribed forcings. The different forcings considered here are those used in the two most recent phases of the Coupled Model Intercomparison Project (CMIP), namely CMIP5 and CMIP6. We show significant differences in simulated global surface air temperature due to volcanic aerosol forcing in the second half of the 19th century and in the early 21st century. The latter arise from small-to-moderate eruptions incorporated in CMIP6 simulations but not in CMIP5 simulations. We also find significant differences in global surface air temperature and Arctic sea ice area due to anthropogenic aerosol forcing in the second half of the 20th century and early 21st century. These differences are as large as those obtained in different versions of an Earth System Model employing identical forcings. In simulations from 2015 to 2100, we find significant differences in the rates of projected global warming arising from CMIP5 and CMIP6 concentration pathways that differ slightly but are equivalent in terms of their nominal radiative forcing levels in 2100. Our results highlight the influence of assumptions about natural and anthropogenic aerosol loadings on carbon budgets, the likelihood of meeting Paris targets, and the equivalence of future forcing scenarios.
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Affiliation(s)
- John C Fyfe
- Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC V8W 2Y2, Canada;
| | - Viatcheslav V Kharin
- Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC V8W 2Y2, Canada
| | - Benjamin D Santer
- Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore, CA 94550
| | - Jason N S Cole
- Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC V8W 2Y2, Canada
| | - Nathan P Gillett
- Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC V8W 2Y2, Canada
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45
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Projected land ice contributions to twenty-first-century sea level rise. Nature 2021; 593:74-82. [PMID: 33953415 DOI: 10.1038/s41586-021-03302-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Accepted: 01/27/2021] [Indexed: 02/03/2023]
Abstract
The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2-8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.
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Liu P, Kaplan JO, Mickley LJ, Li Y, Chellman NJ, Arienzo MM, Kodros JK, Pierce JR, Sigl M, Freitag J, Mulvaney R, Curran MAJ, McConnell JR. Improved estimates of preindustrial biomass burning reduce the magnitude of aerosol climate forcing in the Southern Hemisphere. SCIENCE ADVANCES 2021; 7:7/22/eabc1379. [PMID: 34049885 PMCID: PMC8163089 DOI: 10.1126/sciadv.abc1379] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Accepted: 04/12/2021] [Indexed: 06/12/2023]
Abstract
Fire plays a pivotal role in shaping terrestrial ecosystems and the chemical composition of the atmosphere and thus influences Earth's climate. The trend and magnitude of fire activity over the past few centuries are controversial, which hinders understanding of preindustrial to present-day aerosol radiative forcing. Here, we present evidence from records of 14 Antarctic ice cores and 1 central Andean ice core, suggesting that historical fire activity in the Southern Hemisphere (SH) exceeded present-day levels. To understand this observation, we use a global fire model to show that overall SH fire emissions could have declined by 30% over the 20th century, possibly because of the rapid expansion of land use for agriculture and animal production in middle to high latitudes. Radiative forcing calculations suggest that the decreasing trend in SH fire emissions over the past century largely compensates for the cooling effect of increasing aerosols from fossil fuel and biofuel sources.
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Affiliation(s)
- Pengfei Liu
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
- School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Jed O Kaplan
- Department of Earth Sciences, The University of Hong Kong, Hong Kong, China
| | - Loretta J Mickley
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Yang Li
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
- Department of Environmental Science, Baylor University, Waco, TX 76798, USA
| | - Nathan J Chellman
- Division of Hydrologic Sciences, Desert Research Institute, Reno, NV 89512, USA
| | - Monica M Arienzo
- Division of Hydrologic Sciences, Desert Research Institute, Reno, NV 89512, USA
| | - John K Kodros
- Department of Mechanical Engineering, Colorado State University, Fort Collins, CO 80521, USA
| | - Jeffrey R Pierce
- Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, USA
| | - Michael Sigl
- Oeschger Centre for Climate Change Research, University of Bern, 3012 Bern, Switzerland
- Climate and Environmental Physics, University of Bern, 3012 Bern, Switzerland
| | - Johannes Freitag
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany
| | | | - Mark A J Curran
- Australian Antarctic Division and Antarctic Climate and Ecosystem Cooperative Research Centre, Hobart, Tasmania, Australia
| | - Joseph R McConnell
- Division of Hydrologic Sciences, Desert Research Institute, Reno, NV 89512, USA
- Clare Hall, University of Cambridge, Cambridge CB3 9AL, UK
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47
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He XC, Tham YJ, Dada L, Wang M, Finkenzeller H, Stolzenburg D, Iyer S, Simon M, Kürten A, Shen J, Rörup B, Rissanen M, Schobesberger S, Baalbaki R, Wang DS, Koenig TK, Jokinen T, Sarnela N, Beck LJ, Almeida J, Amanatidis S, Amorim A, Ataei F, Baccarini A, Bertozzi B, Bianchi F, Brilke S, Caudillo L, Chen D, Chiu R, Chu B, Dias A, Ding A, Dommen J, Duplissy J, El Haddad I, Gonzalez Carracedo L, Granzin M, Hansel A, Heinritzi M, Hofbauer V, Junninen H, Kangasluoma J, Kemppainen D, Kim C, Kong W, Krechmer JE, Kvashin A, Laitinen T, Lamkaddam H, Lee CP, Lehtipalo K, Leiminger M, Li Z, Makhmutov V, Manninen HE, Marie G, Marten R, Mathot S, Mauldin RL, Mentler B, Möhler O, Müller T, Nie W, Onnela A, Petäjä T, Pfeifer J, Philippov M, Ranjithkumar A, Saiz-Lopez A, Salma I, Scholz W, Schuchmann S, Schulze B, Steiner G, Stozhkov Y, Tauber C, Tomé A, Thakur RC, Väisänen O, Vazquez-Pufleau M, Wagner AC, Wang Y, Weber SK, Winkler PM, Wu Y, Xiao M, Yan C, Ye Q, Ylisirniö A, Zauner-Wieczorek M, Zha Q, Zhou P, Flagan RC, Curtius J, Baltensperger U, Kulmala M, Kerminen VM, Kurtén T, Donahue NM, Volkamer R, Kirkby J, Worsnop DR, Sipilä M. Role of iodine oxoacids in atmospheric aerosol nucleation. Science 2021; 371:589-595. [PMID: 33542130 DOI: 10.1126/science.abe0298] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 01/06/2021] [Indexed: 11/02/2022]
Abstract
Iodic acid (HIO3) is known to form aerosol particles in coastal marine regions, but predicted nucleation and growth rates are lacking. Using the CERN CLOUD (Cosmics Leaving Outdoor Droplets) chamber, we find that the nucleation rates of HIO3 particles are rapid, even exceeding sulfuric acid-ammonia rates under similar conditions. We also find that ion-induced nucleation involves IO3 - and the sequential addition of HIO3 and that it proceeds at the kinetic limit below +10°C. In contrast, neutral nucleation involves the repeated sequential addition of iodous acid (HIO2) followed by HIO3, showing that HIO2 plays a key stabilizing role. Freshly formed particles are composed almost entirely of HIO3, which drives rapid particle growth at the kinetic limit. Our measurements indicate that iodine oxoacid particle formation can compete with sulfuric acid in pristine regions of the atmosphere.
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Affiliation(s)
- Xu-Cheng He
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland.
| | - Yee Jun Tham
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Lubna Dada
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Mingyi Wang
- Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Henning Finkenzeller
- Department of Chemistry and Cooperative Institute for Research in the Environmental Sciences, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Dominik Stolzenburg
- Faculty of Physics, University of Vienna, 1090 Vienna, Austria
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Siddharth Iyer
- Aerosol Physics Laboratory, Physics Unit, Faculty of Engineering and Natural Sciences, Tampere University, 33014 Tampere, Finland
| | - Mario Simon
- Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Andreas Kürten
- Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Jiali Shen
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Birte Rörup
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Matti Rissanen
- Aerosol Physics Laboratory, Physics Unit, Faculty of Engineering and Natural Sciences, Tampere University, 33014 Tampere, Finland
| | | | - Rima Baalbaki
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Dongyu S Wang
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, CH-5232 Villigen, Switzerland
| | - Theodore K Koenig
- Department of Chemistry and Cooperative Institute for Research in the Environmental Sciences, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Tuija Jokinen
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Nina Sarnela
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Lisa J Beck
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - João Almeida
- CERN, the European Organization for Nuclear Research, CH-1211 Geneva 23, Switzerland
| | - Stavros Amanatidis
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - António Amorim
- CENTRA and Faculdade de Ciências da Universidade de Lisboa, 1749-016 Lisboa, Portugal
| | - Farnoush Ataei
- Leibniz Institute for Tropospheric Research, 04318 Leipzig, Germany
| | - Andrea Baccarini
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, CH-5232 Villigen, Switzerland
| | - Barbara Bertozzi
- Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany
| | - Federico Bianchi
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Sophia Brilke
- Faculty of Physics, University of Vienna, 1090 Vienna, Austria
| | - Lucía Caudillo
- Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Dexian Chen
- Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Randall Chiu
- Department of Chemistry and Cooperative Institute for Research in the Environmental Sciences, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Biwu Chu
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - António Dias
- CENTRA and Faculdade de Ciências da Universidade de Lisboa, 1749-016 Lisboa, Portugal
| | - Aijun Ding
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- Jiangsu Provincial Collaborative Innovation Center of Climate Change, Nanjing 210023, China
| | - Josef Dommen
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, CH-5232 Villigen, Switzerland
| | - Jonathan Duplissy
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
- Helsinki Institute of Physics, University of Helsinki, 00014 Helsinki, Finland
| | - Imad El Haddad
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, CH-5232 Villigen, Switzerland
| | | | - Manuel Granzin
- Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Armin Hansel
- Institute of Ion Physics and Applied Physics, University of Innsbruck, 6020 Innsbruck, Austria
- Ionicon Analytik Ges.m.b.H., 6020 Innsbruck, Austria
| | - Martin Heinritzi
- Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Victoria Hofbauer
- Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Heikki Junninen
- Institute of Physics, University of Tartu, 50411 Tartu, Estonia
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Juha Kangasluoma
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Deniz Kemppainen
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Changhyuk Kim
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
- School of Civil and Environmental Engineering, Pusan National University, Busan 46241, Republic of Korea
| | - Weimeng Kong
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | | | - Aleksander Kvashin
- P.N. Lebedev Physical Institute of the Russian Academy of Sciences, 119991 Moscow, Russia
| | - Totti Laitinen
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Houssni Lamkaddam
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, CH-5232 Villigen, Switzerland
| | - Chuan Ping Lee
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, CH-5232 Villigen, Switzerland
| | - Katrianne Lehtipalo
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
- Finnish Meteorological Institute, 00560 Helsinki, Finland
| | - Markus Leiminger
- Institute of Ion Physics and Applied Physics, University of Innsbruck, 6020 Innsbruck, Austria
- Ionicon Analytik Ges.m.b.H., 6020 Innsbruck, Austria
| | - Zijun Li
- Department of Applied Physics, University of Eastern Finland, 70211 Kuopio, Finland
| | - Vladimir Makhmutov
- P.N. Lebedev Physical Institute of the Russian Academy of Sciences, 119991 Moscow, Russia
| | - Hanna E Manninen
- CERN, the European Organization for Nuclear Research, CH-1211 Geneva 23, Switzerland
| | - Guillaume Marie
- Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Ruby Marten
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, CH-5232 Villigen, Switzerland
| | - Serge Mathot
- CERN, the European Organization for Nuclear Research, CH-1211 Geneva 23, Switzerland
| | - Roy L Mauldin
- Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, CO 80309, USA
| | - Bernhard Mentler
- Institute of Ion Physics and Applied Physics, University of Innsbruck, 6020 Innsbruck, Austria
| | - Ottmar Möhler
- Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany
| | - Tatjana Müller
- Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Wei Nie
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- Jiangsu Provincial Collaborative Innovation Center of Climate Change, Nanjing 210023, China
| | - Antti Onnela
- CERN, the European Organization for Nuclear Research, CH-1211 Geneva 23, Switzerland
| | - Tuukka Petäjä
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Joschka Pfeifer
- CERN, the European Organization for Nuclear Research, CH-1211 Geneva 23, Switzerland
| | - Maxim Philippov
- P.N. Lebedev Physical Institute of the Russian Academy of Sciences, 119991 Moscow, Russia
| | | | - Alfonso Saiz-Lopez
- Department of Atmospheric Chemistry and Climate, Institute of Physical Chemistry Rocasolano, CSIC, 28006 Madrid, Spain
| | - Imre Salma
- Institute of Chemistry, Eötvös University, H-1117 Budapest, Hungary
| | - Wiebke Scholz
- Institute of Ion Physics and Applied Physics, University of Innsbruck, 6020 Innsbruck, Austria
- Ionicon Analytik Ges.m.b.H., 6020 Innsbruck, Austria
| | - Simone Schuchmann
- Institute of Physics, Johannes Gutenberg University Mainz, 55128 Mainz, Germany
| | - Benjamin Schulze
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Gerhard Steiner
- Institute of Ion Physics and Applied Physics, University of Innsbruck, 6020 Innsbruck, Austria
| | - Yuri Stozhkov
- P.N. Lebedev Physical Institute of the Russian Academy of Sciences, 119991 Moscow, Russia
| | | | - António Tomé
- Institute Infante Dom Luíz, University of Beira Interior, 6201-001 Covilhã, Portugal
| | - Roseline C Thakur
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Olli Väisänen
- Department of Applied Physics, University of Eastern Finland, 70211 Kuopio, Finland
| | | | - Andrea C Wagner
- Department of Chemistry and Cooperative Institute for Research in the Environmental Sciences, University of Colorado Boulder, Boulder, CO 80309, USA
- Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Yonghong Wang
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Stefan K Weber
- CERN, the European Organization for Nuclear Research, CH-1211 Geneva 23, Switzerland
| | - Paul M Winkler
- Faculty of Physics, University of Vienna, 1090 Vienna, Austria
| | - Yusheng Wu
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Mao Xiao
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, CH-5232 Villigen, Switzerland
| | - Chao Yan
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Qing Ye
- Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Arttu Ylisirniö
- Department of Applied Physics, University of Eastern Finland, 70211 Kuopio, Finland
| | - Marcel Zauner-Wieczorek
- Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Qiaozhi Zha
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Putian Zhou
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Richard C Flagan
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Joachim Curtius
- Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Urs Baltensperger
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, CH-5232 Villigen, Switzerland
| | - Markku Kulmala
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- Helsinki Institute of Physics, University of Helsinki, 00014 Helsinki, Finland
- Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Veli-Matti Kerminen
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Theo Kurtén
- Department of Chemistry, University of Helsinki, University of Helsinki, 00014 Helsinki, Finland
| | - Neil M Donahue
- Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Chemistry, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Rainer Volkamer
- Department of Chemistry and Cooperative Institute for Research in the Environmental Sciences, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Jasper Kirkby
- CERN, the European Organization for Nuclear Research, CH-1211 Geneva 23, Switzerland.
- Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Douglas R Worsnop
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
- Aerodyne Research, Inc., Billerica, MA 01821, USA
| | - Mikko Sipilä
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland.
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48
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Tittensor DP, Novaglio C, Harrison CS, Heneghan RF, Barrier N, Bianchi D, Bopp L, Bryndum-Buchholz A, Britten GL, Büchner M, Cheung WWL, Christensen V, Coll M, Dunne JP, Eddy TD, Everett JD, Fernandes-Salvador JA, Fulton EA, Galbraith ED, Gascuel D, Guiet J, John JG, Link JS, Lotze HK, Maury O, Ortega-Cisneros K, Palacios-Abrantes J, Petrik CM, du Pontavice H, Rault J, Richardson AJ, Shannon L, Shin YJ, Steenbeek J, Stock CA, Blanchard JL. Next-generation ensemble projections reveal higher climate risks for marine ecosystems. NATURE CLIMATE CHANGE 2021; 11:973-981. [PMID: 34745348 PMCID: PMC8556156 DOI: 10.1038/s41558-021-01173-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 09/01/2021] [Indexed: 05/16/2023]
Abstract
Projections of climate change impacts on marine ecosystems have revealed long-term declines in global marine animal biomass and unevenly distributed impacts on fisheries. Here we apply an enhanced suite of global marine ecosystem models from the Fisheries and Marine Ecosystem Model Intercomparison Project (Fish-MIP), forced by new-generation Earth system model outputs from Phase 6 of the Coupled Model Intercomparison Project (CMIP6), to provide insights into how projected climate change will affect future ocean ecosystems. Compared with the previous generation CMIP5-forced Fish-MIP ensemble, the new ensemble ecosystem simulations show a greater decline in mean global ocean animal biomass under both strong-mitigation and high-emissions scenarios due to elevated warming, despite greater uncertainty in net primary production in the high-emissions scenario. Regional shifts in the direction of biomass changes highlight the continued and urgent need to reduce uncertainty in the projected responses of marine ecosystems to climate change to help support adaptation planning.
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Affiliation(s)
- Derek P. Tittensor
- Department of Biology, Dalhousie University, Halifax, Nova Scotia Canada
- United Nations Environment Programme World Conservation Monitoring Centre, Cambridge, UK
| | - Camilla Novaglio
- Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania Australia
- Center for Marine Socio-ecology, University of Tasmania, Hobart, Tasmania Australia
| | - Cheryl S. Harrison
- School of Earth, Environmental and Marine Science, University of Texas Rio Grande Valley, Port Isabel, TX USA
- Department of Ocean and Coastal Science and Centre for Computation and Technology, Louisiana State University, Baton Rouge, LA USA
| | - Ryan F. Heneghan
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland Australia
| | - Nicolas Barrier
- MARBEC, IRD, Univ Montpellier, Ifremer, CNRS, Sète/Montpellier, France
| | - Daniele Bianchi
- Department of Atmospheric and Oceanic Sciences, University of California Los Angeles, Los Angeles, CA USA
| | - Laurent Bopp
- LMD/IPSL, CNRS, Ecole Normale Supérieure, Université PSL, Sorbonne Université, Ecole Polytechnique, Paris, France
| | | | - Gregory L. Britten
- Program in Atmospheres, Oceans, and Climate, Massachusetts Institute of Technology, Cambridge, MA USA
| | - Matthias Büchner
- Potsdam-Institute for Climate Impact Research (PIK), Potsdam, Germany
| | - William W. L. Cheung
- Institute for the Oceans and Fisheries, The University of British Columbia, Vancouver, British Columbia Canada
| | - Villy Christensen
- Institute for the Oceans and Fisheries, The University of British Columbia, Vancouver, British Columbia Canada
| | - Marta Coll
- Institute of Marine Science (ICM-CSIC), Barcelona, Spain
- Ecopath International Initiative Research Association, Barcelona, Spain
| | - John P. Dunne
- NOAA/OAR Geophysical Fluid Dynamics Laboratory, Princeton, NJ USA
| | - Tyler D. Eddy
- Centre for Fisheries Ecosystems Research, Fisheries and Marine Institute, Memorial University of Newfoundland, St. John’s, Newfoundland and Labrador Canada
| | - Jason D. Everett
- School of Mathematics and Physics, The University of Queensland, St. Lucia, Queensland Australia
- Commonwealth Scientific and Industrial Research Organisation (CSIRO) Oceans and Atmosphere, Queensland Biosciences Precinct, St Lucia, Brisbane, Queensland Australia
- Centre for Marine Science and Innovation, The University of New South Wales, Sydney, New South Wales Australia
| | | | - Elizabeth A. Fulton
- Center for Marine Socio-ecology, University of Tasmania, Hobart, Tasmania Australia
- Commonwealth Scientific and Industrial Research Organisation (CSIRO) Oceans and Atmosphere, Hobart, Tasmania Australia
| | - Eric D. Galbraith
- Department of Earth and Planetary Science, McGill University, Montreal, Quebec Canada
| | - Didier Gascuel
- UMR Ecology and Ecosystems Health (ESE), Institut Agro, Inrae, Rennes, France
| | - Jerome Guiet
- Department of Atmospheric and Oceanic Sciences, University of California Los Angeles, Los Angeles, CA USA
| | - Jasmin G. John
- NOAA/OAR Geophysical Fluid Dynamics Laboratory, Princeton, NJ USA
| | | | - Heike K. Lotze
- Department of Biology, Dalhousie University, Halifax, Nova Scotia Canada
| | - Olivier Maury
- MARBEC, IRD, Univ Montpellier, Ifremer, CNRS, Sète/Montpellier, France
| | | | - Juliano Palacios-Abrantes
- Institute for the Oceans and Fisheries, The University of British Columbia, Vancouver, British Columbia Canada
- Center for Limnology, University of Wisconsin, Madison, WI USA
| | - Colleen M. Petrik
- Department of Oceanography, Texas A&M University, College Station, TX USA
| | - Hubert du Pontavice
- UMR Ecology and Ecosystems Health (ESE), Institut Agro, Inrae, Rennes, France
- Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, NJ USA
| | - Jonathan Rault
- MARBEC, IRD, Univ Montpellier, Ifremer, CNRS, Sète/Montpellier, France
| | - Anthony J. Richardson
- School of Mathematics and Physics, The University of Queensland, St. Lucia, Queensland Australia
- Commonwealth Scientific and Industrial Research Organisation (CSIRO) Oceans and Atmosphere, Queensland Biosciences Precinct, St Lucia, Brisbane, Queensland Australia
| | - Lynne Shannon
- Department of Biological Sciences, University of Cape Town, Cape Town, South Africa
| | - Yunne-Jai Shin
- MARBEC, IRD, Univ Montpellier, Ifremer, CNRS, Sète/Montpellier, France
| | - Jeroen Steenbeek
- Ecopath International Initiative Research Association, Barcelona, Spain
| | - Charles A. Stock
- NOAA/OAR Geophysical Fluid Dynamics Laboratory, Princeton, NJ USA
| | - Julia L. Blanchard
- Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania Australia
- Center for Marine Socio-ecology, University of Tasmania, Hobart, Tasmania Australia
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Anjos LJ, Barreiros de Souza E, Amaral CT, Igawa TK, Mann de Toledo P. Future projections for terrestrial biomes indicate widespread warming and moisture reduction in forests up to 2100 in South America. Glob Ecol Conserv 2021. [DOI: 10.1016/j.gecco.2020.e01441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
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50
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Danilov-Danil’yan VI, Kattsov VM, Porfiriev BN. The Problem of Climate Change: The Field of Convergence and Interaction between Natural Sciences and the Sociohumanities. HERALD OF THE RUSSIAN ACADEMY OF SCIENCES 2020; 90:577-587. [PMID: 33250605 PMCID: PMC7682684 DOI: 10.1134/s1019331620050123] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 07/07/2020] [Accepted: 07/14/2020] [Indexed: 06/12/2023]
Abstract
The relationship and interaction between natural science and sociohumanities knowledge and methods of studying global and regional climate changes and their socioeconomic consequences are analyzed. It is argued that the methodological and instrumental basis of the interaction above involve risk theory and modeling. The key results include a comprehensive assessment and forecast of climatic risks of socioeconomic development, which make up the basis of the development of effective strategies for sustainable long-term development. Ephasized is the counterproductiveness of a straightforward approach to the climate change problem which implies as the main goal of sustainable development the radical reduction of greenhouse gas emissions. The necessity and effectiveness of a systematic approach that provides for the priority of institutional, structural, and technological transformations in society and the economy are emphasized. An important result of these transformations should involve the reduction of anthropogenic impact on the environment, including its climate formation factors, and adaptation to its climate change.
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Affiliation(s)
| | - V. M. Kattsov
- Voeikov Main Geophysical Observatory, Federal Service for Hydrometeorology and Environmental Monitoring, St. Petersburg, Russia
| | - B. N. Porfiriev
- Institute of Economic Forecasting, Russian Academy of Sciences, Moscow, Russia
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