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Published February 5, 2026 | Version v0.1
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ScenarioMIP-CMIP7 IAM quantification: Harmonized and Infilled Emissions and Climate Outcomes for Marker Scenarios

Description

This is a pre-release of the harmonized ScenarioMIP emissions data. Please refer to the Rules for data use and data sharing of the IAM ScenarioMIP Data at https://scenariomip.apps.ece.iiasa.ac.at.

 

Harmonized Emissions of the IAM ScenarioMIP projections for CMIP7

ScenarioMIP-CMIP7 consists of alternative plausible futures including quantified emissions and land use projections. 

The primary objectives of ScenarioMIP are to:

  1. Facilitate integrated research leading to a better understanding of the physical climate system consequences of future scenarios and their impact on natural and social systems, including adaptation and mitigation considerations.

  2. Provide a basis for addressing targeted science questions about the climate effects of aspects of forcing relevant to scenario-based research.

  3. Provide a basis for various international efforts that target improved methods to quantify projection uncertainties based on multi-model ensembles.

ScenarioMIP is part of the Coupled Model Intercomparison Project organised by the World Climate Research Programme, and integrates research across the climate science, integrated assessment modeling (IAM), mitigation, and impacts, adaptation and vulnerability (IAV) communities. 

Seven IAM teams participated in the scenario development process. Each scenario has been implemented with multiple IAMs, and a marker scenario was selected from the available model interpretations. The current pre-release comprises the harmonized emissions of the marker scenarios only. Harmonized emissions of additional non-marker quantifications will follow. 

This pre-release hosts limited data, with the publication of more data variables to follow. The available data are the emissions variables that have gone into the climate emulator MAGICC and its climate outcomes. The reported emissions variables are harmonized to CMIP7 historical emissions, and consistent with CMIP7 earth system model forcings: GHG concentrations and gridded emissions, as available on the Earth System Grid Federation (see input4MIPs: https://input4mips-cvs.readthedocs.io/en/latest/).

For more information, please contact:

  • Scientific Lead: Keywan Riahi (IIASA, riahi@iiasa.ac.at), Detlef van Vuuren (PBL, Detlef.vanVuuren@pbl.nl)

  • Emissions harmonization and infilling for CMIP7: Jarmo Kikstra (IIASA, kikstra@iiasa.ac.at), Zebedee Nicholls (Climate Resource, IIASA, Uni Melbourne, zebedee.nicholls@climate-resource.com)

  • ScenarioMIP IAM marker teams:

    • High Emissions Pathway (H) developed by GCAM: Mel George, Christoph J. Bertram, Andrew G. Miller, Xin Zhao, Claudia Rodes Bachs, Jay Fuhrman, Rachel Hoesly, Haewon C. McJeon, Brian O'Neill, Yang Ou, Jon Sampedro, Steven J. Smith, Dirk-Jan Van de Ven, Matt Gidden, Ryna Cui (CGS-UMD [Center for Global Sustainability, School of Public Policy, University of Maryland, College Park, Maryland, USA], KAIST, BC3, Peking University)

    • High-to-Low Emissions Pathway (HL) developed by WITCH: Laurent Drouet, Lara Aleluia (CMCC)

    • Medium Emissions Pathway (M) developed by IMAGE: Detlef van Vuuren, Vassilis Daioglou (PBL)

    • Medium-to-Low Emissions Pathway (ML) developed by COFFEE: Roberto Schaeffer, Luiz Bernardo Baptista, Gerd Angelkorte (COPPE)
      This pathway is still in development and will be included in a later release.

    • Low Emissions Pathway (L) developed by MESSAGE-GLOBIOM-GAINS: Oliver Fricko, Volker Krey, Keywan Riahi (IIASA)

    • Very Low Emissions Pathway (VL) developed by REMIND-MAGPIE: Elmar Kriegler, Laurin Köhler-Schindler, Florian Humpenöder (PIK)

    • Low-to-Negative Emissions Pathway (LN) developed by AIM: Shinichiro Fujimori, Tomoko Hasegawa (Kyoto University)

  • Air pollution: please contact Shaohui Zhang, Zbigniew Klimont (IIASA)

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This dataset provides early access to the scenario data while in parallel the IAM teams are preparing the documentation and scientific manuscripts that should be used by the users as the citation of the underlying scenario data.

The scenario data was provided by the IAM teams early February 2026. After this point, the data can be used for scientific purposes. Scientific references for the scenario data will become available latest by 1 September 2026. This is the date when citable preprints of the underlying IAM publications are expected to become available.

The following restrictions apply to the data during the “early access period” between February 1, 2026 and August 31, 2026:

  1. Data can be used only upon registration at the ScenarioMIP Explorer or by requesting to download via Zenodo.
  2. The data can be used only for scientific purposes aimed at the production of peer-reviewed publications. The posting of the scenario data and/or analyses based on the data on social media or other dissemination (in the public or the press) is thus strictly prohibited.
  3. Data is provided only for own use by those registered at the ScenarioMIP Explorer or by requesting to download via Zenodo. Sharing with third parties is not allowed.
  4. Submissions of papers using the IAM scenario data need to wait until the descriptions of the underlying IAM scenarios are published as preprints. Papers based on the IAM scenario data should not be submitted until after 01 September 2026, when preprints of the underlying IAM documentation become available.
  5. Papers using the data should use the appropriate citation (guidelines will become available in Spring 2026)
  6. The use of the data in the IPCC Reports is allowed using the ScenarioMIP database as a preliminary citation. The IPCC Authors should make sure that citations in the report are updated in Spring 2026 when the citation guidance becomes available.

After the “early access” period (ending at 01 September 2026), above restrictions are lifted and the data can be used according to the database license. Users are expected to follow standard scientific practice, using the citation guidance provided by the IAM teams involved in the ScenarioMIP effort. The IAM teams will provide preprints of their articles and create a DOI for the data.

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