ScenarioMIP-CMIP7 IAM quantification: Harmonized and Infilled Emissions and Climate Outcomes for Marker Scenarios

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Essential reference dataset for climate scenario analysis and integrated assessment modeling.

🏢実務担当者:Provides benchmark scenarios for transition risk assessment and corporate climate strategy development.

🏛政策担当者:Supports evidence-based target setting and policy evaluation for national and global decarbonization.

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: 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. Provide a basis for addressing targeted science questions about the climate effects of aspects of forcing relevant to scenario-based research. 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, [email protected]), Detlef van Vuuren (PBL, [email protected]) Emissions harmonization and infilling for CMIP7: Jarmo Kikstra (IIASA, [email protected]), Zebedee Nicholls (Climate Resource, IIASA, Uni Melbourne, [email protected]) ScenarioMIP IAM marker teams: High Emissions Pathway (H) developed by GCAMMain contact: Mel George ([email protected])Modeling team: Christoph J. Bertram ([email protected]), 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 WITCHMain contact: Laurent Drouet ([email protected])Modeling team: Lara Aleluia Reis, Marco Gambarini, Cindy Azuero, Massimo Tavoni (CMCC). Specific contributors: Pietro Andreoni (non-CO2, Politecnico di Milano), Nicolas Schlegel (optimization, CMCC), Stefan Frank and Yazhen Wu (GLOBIOM, IIASA) Medium Emissions Pathway (M) developed by IMAGEMain contact: Detlef van Vuuren ([email protected])Modeling team: Vassilis Daioglou, Isabela Tagomori, Harmen-Sytze de Boer, Mathijs Harmsen, Ioannis Dafnomilis, Elena Hooijschuur, Maarten van den Berg, Rik van Heerden, Mark Dekker, Jonathan Doelman, Elke Stehfest, Astrid Bos, Willem-Jan van Zeist, Hermen Luchtenbelt (PBL) Medium-to-Low Emissions Pathway (ML) developed by COFFEEMain contact: Roberto Schaeffer ([email protected]), Luiz Bernardo Baptista ([email protected]), Gerd Angelkorte ([email protected])Modeling team: Pedro Rochedo, Luis Felipe Sivolella, Rebecca Draeger, Pedro Maia, Huang Ken Wei and Alexandre Szklo (COPPE) Low Emissions Pathway (L) developed by MESSAGE-GLOBIOM-GAINSMain contact: Oliver Fricko ([email protected]), Yazhen Wu ([email protected]), Shaohui Zhang ([email protected])Modelling Team: Oliver Fricko, Yazhen Wu, Shaohui Zhang, Stefan Frank, Mykola Gusti, Lena Höglund-Isaksson, Aneeque Javid, Siddarth Joshi, Diogo Kramel, Alessio Mastrucci, Florian Mazcek, Setu Pelz, Yoga Pratama, Holger Rogner, Jun Shepard, Juliana Arbelaez-Gaviria, Luca Casamassima, Jinfeng Chang, Matt Gidden, Adriana Gomez-Sanabria, Anders Hammer-Stromman, Yiyi Ju, Jarmo Kikstra, Younha Kim, Paul Natsuo Kishimoto, Marta Kozicka, Tamás Krisztin, David Leclère, Andrey Lessa Derci Augustynczik, Measrainsey Meng, Amanda Palazzo, Miguel Poblete, Leopold Ringwald, Sibylle Rouet-Pollakis, Pallav Purohit, Gamze Unlu, Adriano Vinca, Fabian Wagner, Wilfried Winiwarter, Xiuming Zhang, Michael Wögerer, Behnam Zakeri, Zbigniew Klimont, Shonali Pachauri, Petr Havlík, Bas van Ruijven, Keywan Riahi, Volker Krey Low-to-Negative Emissions Pathway (LN) developed by AIMMain contact: Shinichiro Fujimori ([email protected]), Osamu Nishiura ([email protected]), Tomoko Hasegawa ([email protected])Modeling team: Shotaro Mori, Ken Oshiro, Koga Yamazaki, Ryo Totake, Diego Silva, Kiyoshi Takahashi Very Low Emissions Pathway (VL) developed by REMIND-MAGPIEMain contact: lmar Kriegler ([email protected]), Gunnar Luderer ([email protected]), Alexander Popp ([email protected])Modeling team: Gabriel Abrahão, Nico Bauer, Lavinia Baumstark, Jan Philipp Dietrich, Florian Humpenöder, Laurin Köhler-Schindler, Fabrice Lécuyer, Leon Merfort, Jessica Strefler (PIK) Air pollution: please contact Shaohui Zhang, Zbigniew Klimont (IIASA)

• openalex https://doi.org/10.5281/zenodo.19825038first seen 2026-05-29 05:06:10 · last seen 2026-05-30 05:10:11