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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: orcid bw Byers, Edward;
    Byers, Edward
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Byers, Edward in OpenAIRE
    orcid bw Krey, Volker;
    Krey, Volker
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Krey, Volker in OpenAIRE
    Kriegler, Elmar; orcid bw Riahi, Keywan;
    Riahi, Keywan
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Riahi, Keywan in OpenAIRE
    +35 Authors

    The data is available for download at the AR6 Scenario Explorer hosted by IIASA. As part of the IPCC's 6th Assessment Report (AR6), authors from Working Group III on Mitigation of Climate Change undertook a comprehensive exercise to collect and assess quantitative, model-based scenarios related to the mitigation of climate change. Building on previous assessments, such as those undertaken for the 5th Assessment Report (AR5) and the Special Report on Global Warming of 1.5°C (SR15), the calls for AR6 for scenarios have been expanded and includes economy-wide GHG emissions, energy, and sectoral scenarios from global to national scales, thus more broadly supporting the assessment across multiple chapters (see Annex III, Part 2 of the WGIII report for more details). The compilation and assessment of the scenario ensemble was conducted by authors of the IPCC AR6 report, and the resource is hosted by the International Institute for Applied Systems Analysis (IIASA) as part of a cooperation agreement with Working Group III of the IPCC. The scenario ensemble contains 3,131 quantitative scenarios with data on socio-economic development, greenhouse gas emissions, and sectoral transformations across energy, land use, transportation, buildings and industry. These scenarios derive from 191 unique modelling frameworks, 95+ model families that are either globally comprehensive, national, multi-regional or sectoral. The criteria for submission included that the scenario is presented in a peer-reviewed journal accepted for publication no later than October 11th, 2021, or published in a report determined by the IPCC WG III Bureau to be eligible grey literature by the same date. The AR6 scenario database is documented in Annex III.2 of the Sixth Assessment Report of Working Group III. For the purpose of the assessment, scenarios have been grouped in various categories relating to, among other things, climate outcomes, overshoot, technology availability and policy assumptions. For ease of use, the dataset is split into multiple files: Scenarios data for the Global region Scenarios data for R5 regions Scenarios data for R6 regions Scenarios data for R10 regions Scenarios data for ISO-3 (country) regions Global metadata indicators file National metadata indicators file The data is available for download at the AR6 Scenario Explorer hosted by IIASA. The license permits use of the scenario ensemble for scientific research and science communication, but restricts redistribution of substantial parts of the data. Please refer to the FAQ and legal code for more information. In addition to the data you may find more relevant information and cite one of the relevant chapters of the WG III report. If working with global or regional (R6, R10) data: Keywan Riahi, Roberto Schaeffer, et al. Mitigation Pathways Compatible with Long-Term Goals, in "Mitigation of Climate Change". Intergovernmental Panel on Climate Change, Geneva, 2022. url: http://www.ipcc.ch/report/sixth-assessment-report-working-group-3/ If working with national data (ISO region data): Franck Lecocq, Harald Winkler, et al. Mitigation and development pathways in the near- to mid-term, in "Mitigation of Climate Change". Intergovernmental Panel on Climate Change, Geneva, 2022. url: http://www.ipcc.ch/report/sixth-assessment-report-working-group-3/ If you find the metadata files particularly useful: Celine Guivarch, Elmar Kriegler, Joana Portugal Pereira, et al. Annex III: Scenarios and Modelling Methods, in "Mitigation of Climate Change". Intergovernmental Panel on Climate Change, Geneva, 2022. url: http://www.ipcc.ch/report/sixth-assessment-report-working-group-3/ Scenarios data also supports analysis in Chapters 2, 5, 6, 7, 9, 10, 12 and 15

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    ZENODO
    Dataset . 2022
    Data sources: Datacite
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      ZENODO
      Dataset . 2022
      Data sources: Datacite
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