© IIASA 2022
The scenario ensemble is protected by EU Sui generis database rights.
As part of the IPCC's Sixth 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 Fifth Assessment Report (AR5) and the Special Report on Global Warming of 1.5°C (SR15), the calls for scenarios in AR6 have been expanded to include energy, emissions, and sectoral scenarios from global to national scales, thus more broadly supporting the assessment across multiple chapters (see Annex III, Part 2 of the WG III report for more details). Calls for scenarios were open for 22 months (September 2019 - July 2021) and undertaken by Lead Authors of WG III:
The compilation and assessment of the scenario ensemble was conducted by authors of the IPCC AR6 report, and the dataset is referred to as the AR6 Scenarios Database. This database is hosted on a Scenario Explorer 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, and industry. These scenarios derive from 188 unique modelling frameworks and 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 to be eligible grey literature by the same date.
The AR6 Scenarios Database is documented in Annex III.II 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. This information is provided in the scenario metadata on the Downloads page.
For ease of use, the dataset is split into multiple files, available on the downloads page:
Scenario Explorer has loads of features. To get the most out of your experience these videos might help! IIASA Scenario Explorer tutorial videos
In 2023 a series of regional webinars on the use of scenarios in AR6 WGIII were organized by IPCC TG-Data, with recordings and presentation materials hosted by IPCC.
A majority of scenarios was provided by model comparison projects which have published their scenario data in project specific databases. These project scenarios databases can hold more information than is provided here. Scenario data from this site may be freely used for non-commercial and educational purposes with proper acknowledgment of the data sources. The data source is specified in the scenario name (i.e. the project name in most cases). Users are requested to ensure proper acknowledgment of the data sources of the scenarios they use as detailed below. Annex III Section II.3 provides information about the model comparison projects that are represented in the AR6 Scenarios Database. In particular, it lists the number of models and scenarios included in the database, the areas in which models were harmonized, the leading institutions and references to the overview publications. Some of this information is also within the metadata.
Following the example of the SR15, IMPs have also been selected for the AR6 of WGIII. In contrast to SR15, the selection needed to cover a larger range of climate outcomes while keeping the number of IMPs limited. The selection focused on a range of critical themes that emerged from the AR6 assessment: 1) the level of ambitious of climate policy, 2) the different mitigation strategies, 3) timing of mitigation actions and 4) the combination of climate policy with sustainable development policies. The IMPs consist of narratives (Table II.2) as well as possible quantifications. The IMPs are illustrative and denote implications of different societal choices for the development of future emissions and associated transformations of main GHG emitting sectors. For Chapter 3, for each of the IMPs a quantitative scenario was selected from the AR6 scenario database to have particular characteristics and from diverse modelling frameworks (Annex III Table II.3).
| Acronym | Climate Category (II.3.2) | Model | Scenario name in the AR6 scenario database (II.3) | Reference |
|---|---|---|---|---|
| Cur-Pol | C7 | GCAM 5.3 | NGFS2_Current Policies | NGFS 2021 |
| Mod-Act | C6 | IMAGE 3.0 | EN_INDCi2030_3000f | Riahi et al. 2021, Bertram et al. 2021, Hasegawa et al. 2021 |
| Illustrative Mitigation Pathways (IMPs) | ||||
| Neg | C2* | COFFEE 1.1 | EN_NPi2020_400f_lowBECCS | Riahi et al. 2021, Bertram et al. 2021, Hasegawa et al. 2021 |
| Ren | C1 | REMIND-MAgPIE 2.1-4.3 | DeepElec_SSP2_ HighRE_Budg900 | Luderer et al. 2021 |
| LD | C1 | MESSAGEix-GLOBIOM 1.0 | LowEnergyDemand_1.3_IPCC | Grubler et al. 2018 |
| GS | C3 | WITCH 5.0 | CO_Bridge | van Soest et al. 2021 |
| SP | C1 | REMIND-MAgPIE 2.1-4.2 | SusDev_SDP-PkBudg1000 | Soergel et al. 2021 |
| Sensitivity cases | ||||
| Neg-2.0 | C3 | AIM/CGE 2.2 | EN_NPi2020_900f | Riahi et al. 2021, Bertram et al. 2021, Hasegawa et al. 2021 |
| Ren-2.0 | C3 | MESSAGEix-GLOBIOM_GEI 1.0 | SSP2_openres_lc_50 | Guo et al. 2022, GEIDCO, WMO & IIASA 2019 |
The scenario ensemble is made publicly available to ensure reproducibility and transparency of the scenario set and the underlying data that has been assessed in AR6. The Scenario Explorer allows for the re-use of scenario data by other research communities. Please read the guidance note and the license terms on the License page before downloading data or figures from this Scenario Explorer.
When using the scenario ensemble or exporting figures/tables from this Scenario Explorer, please use the citation as detailed below. You should also include a clear indication of the version number of the release to ensure reproducibility. See the full list of contributors below.
Edward Byers, Volker Krey, Elmar Kriegler, Keywan Riahi, Roberto Schaeffer, Jarmo Kikstra, Robin Lamboll, Zebedee Nicholls, Marit Sanstad, Chris Smith, Kaj-Ivar van der Wijst, Alaa Al Khourdajie, Franck Lecocq, Joana Portugal-Pereira, Yamina Saheb, Anders Strømann, Harald Winkler, Cornelia Auer, Elina Brutschin, Matthew Gidden, Philip Hackstock, Mathijs Harmsen, Daniel Huppmann, Peter Kolp, Claire Lepault, Jared Lewis, Giacomo Marangoni, Eduardo Müller-Casseres, Ragnhild Skeie, Michaela Werning, Katherine Calvin, Piers Forster, Celine Guivarch, Tomoko Hasegawa, Malte Meinshausen, Glen Peters, Joeri Rogelj, Bjorn Samset, Julia Steinberger, Massimo Tavoni, Detlef van Vuuren.
AR6 Scenarios Database hosted by IIASA
International Institute for Applied Systems Analysis, 2022.
doi: 10.5281/zenodo.5886911 |
url: data.ece.iiasa.ac.at/ar6/
Download citation: bibtex (bib)
In addition to the data, you may find more relevant information in and cite one of the relevant chapters of the WG III report.
If working with global or regional (R6, R10) data, please consider citing Chapter 3:
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: Mitigation of Climate Change - Chapter 3
If working with national data (ISO region data), please consider citing Chapter 4:
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: Mitigation of Climate Change - Chapter 4
If you find the metadata files particularly useful, please consider citing Annex III:
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: Annex III: Scenarios and Modelling Methods
Scenario data also supports analysis in Chapters 2, 5, 6, 7, 9, 10, 12 and 15.
Full citation data of recent IPCC reports can be downloaded as Bibtex files here
This release is published to improve reproducibility of the report, particularly with respect to publication of the methodology, code and data of the climate assessment as detailed in Kikstra et al. 2022 https://doi.org/10.5194/egusphere-2022-471. For full details see the Downloads page.
This release coincides with the approval and acceptance of the IPCC's AR6 WG III Report Mitigation of Climate Change.
A number of projects and models have contributed ensembles of scenarios to the database. The full lists of global, regional, and national studies, with relevant citations, can be found in Annex III Sections 3.2 & 3.3 Tables II.5, II.6, II.8, II.9 & II.11.
The categorization of scenarios and metadata production for the ensemble was largely implemented using the pyam package. Provided in the initial release of the metadata are key variables used in the assessment for reproduction of numbers in the Summary for Policymakers amongst other parts of the report.
For all scenarios reporting global data, a vetting process is undertaken to ensure that key indicators were within reasonable ranges for the baseline period - primarily for indicators relating to emissions and the energy sector (please see Annex III Table II.4).
For data relating to all figures in the Summary for Policymakers and the Technical Summary, please see the IPCC Data Distribution Centre.
A climate assessment of the long-term global emissions scenarios was undertaken as part of the Chapter 3 assessment. Emissions scenarios were harmonized, infilled, and run through climate model emulators to derive probabilistic climate system variables including global surface air temperature, radiative forcing, and atmospheric concentrations.
The workflow is publicly available at https://github.com/iiasa/climate-assessment. This allows for reproduction of the climate assessment used in AR6, as well as assessment of new emissions pathways in line with the process applied in AR6. The methodology, code and data of the climate assessment is detailed in Kikstra et al. 2022 https://doi.org/10.5194/egusphere-2022-471.
This process involved a large collaboration of researchers involving:
To fill in emissions not reported for scenarios in their submission to the database, we use a large set of harmonized AR6 global emissions pathways for inferring pathways based on the relationships between concurrent species development over time observed in the larger set. This database is made available with https://doi.org/10.5281/zenodo.6390768.
The development of the Scenario Explorer is a team effort led by Daniel Huppmann, Volker Krey and many others at IIASA. The AR6 Scenarios Database and Scenario Explorer was coordinated by Edward Byers. The institutional support by IIASA in hosting the AR6 Scenario Explorer is greatly appreciated. We wish to thank current and former members of the IIASA ECE Scenario Services & Scientific Software team, Peter Kolp, Nikolay Kushin, Michael Pimmer, Philip Hackstock, Laura Wienpahl, and Max Wohlschlager for their past and ongoing contributions to software development and maintenance of the database infrastructure.
The IAMC Scientific Working Group on Data Protocols and Management and numerous authors of the AR6 WGIII Report are acknowledged for their efforts to enable consistent reporting across research groups, the development of a common data template and support in various efforts towards the AR6 scenarios process.
The substantial work by all modelling teams that submitted scenarios to the database is also gratefully recognized. This would not have been possible without extensive efforts of many lead authors reaching out to their communities to encourage scenario submissions: Franck Lecocq (CIRED), Harald Winkler (UCT), Yamina Saheb (OpenEXP), Andre Lucena (UFRJ), Anders Strømann (NTNU), Paulina Jaramillo (CMU) and Subash Dhar (DTU).
The development of the AR6 Scenario Explorer and the AR6 Scenarios Database was in part financially supported by the ENGAGE project, funded by the European Union under grant agreement No. 821471.
