Scenario Model Intercomparison Project

Scenario Model Intercomparison Project
Name	Scenario Model Intercomparison Project
Abbreviation	Scenario MIP
Discipline	Climate science
Established	2010s

Scenario Model Intercomparison Project The Scenario Model Intercomparison Project coordinates comparative assessments of climate, socioeconomic, and policy scenarios across multiple Intergovernmental Panel on Climate Change cycles, linking outputs from integrated assessment models, Earth system models, and sectoral models to inform international assessments such as the Paris Agreement and the IPCC Fifth Assessment Report. It provides standardized scenario frameworks used by communities associated with Article 6 of the Paris Agreement, United Nations Framework Convention on Climate Change, World Bank Group, International Energy Agency, and research programs like Coupled Model Intercomparison Project and Model Intercomparison Project initiatives. The project connects modeling centers at institutions including Massachusetts Institute of Technology, Princeton University, University of Oxford, Stanford University, and national laboratories such as Lawrence Berkeley National Laboratory and Oak Ridge National Laboratory.

Overview

Scenario MIP establishes common scenario protocols that enable cross-comparison among modeling efforts, harmonizing pathways like Representative Concentration Pathways used in the IPCC Fifth Assessment Report, socioeconomic pathways aligned with Shared Socioeconomic Pathways and policy narratives relevant to United Nations Sustainable Development Goals, European Union energy targets, and commitments under the Kyoto Protocol. The project fosters collaboration between modeling groups at NOAA, NASA, National Oceanic and Atmospheric Administration, National Aeronautics and Space Administration, Met Office Hadley Centre, Max Planck Institute for Meteorology, French Alternative Energies and Atomic Energy Commission, and universities such as Columbia University and University of California, Berkeley. Scenario MIP outputs support decision-makers at entities like World Health Organization, Food and Agriculture Organization, International Monetary Fund, and Organisation for Economic Co-operation and Development.

History and Development

Scenario MIP evolved from earlier coordination efforts tied to the Intergovernmental Panel on Climate Change assessment cycles and the expansion of Coupled Model Intercomparison Project Phase 5 protocols, drawing on scenario work from Energy Modeling Forum and the Global Change Assessment Model community. Key milestones include integration with IPCC Special Report on Global Warming of 1.5 °C, adoption of harmonized socioeconomic baselines influenced by Millennium Development Goals transitions, and collaboration with initiatives at International Institute for Applied Systems Analysis, Potsdam Institute for Climate Impact Research, and Stockholm Environment Institute. Workshops at Royal Society venues, presentations at the American Geophysical Union meetings, and coordination through programs like Future Earth and World Climate Research Programme shaped its governance and data protocols.

Methodology

Scenario MIP prescribes standardized experimental designs, forcing datasets, and metadata standards that enable traceability across models from groups at National Center for Atmospheric Research, Geophysical Fluid Dynamics Laboratory, Scripps Institution of Oceanography, Tyndall Centre for Climate Change Research, and Institut Pierre-Simon Laplace. The methodology integrates greenhouse gas concentration trajectories with land-use change datasets based on harmonization procedures influenced by the Harmonized Emissions Database approach and statistical practices from Intergovernmental Panel on Climate Change guidance. It uses ensemble strategies similar to those of Coupled Model Intercomparison Project Phase 6, uncertainty quantification techniques common at European Centre for Medium-Range Weather Forecasts, and scenario storylines reminiscent of research at International Energy Agency and Organisation for Economic Co-operation and Development. Data distribution and archival follow protocols utilized by Earth System Grid Federation, PANGAEA, and national data centers such as British Atmospheric Data Centre.

Key Findings and Applications

Analyses facilitated by Scenario MIP have clarified outcomes for temperature targets in the context of Paris Agreement pledges, provided sectoral projections relevant to International Maritime Organization regulations and International Civil Aviation Organization mitigation pathways, and informed assessments of adaptation needs comparable to studies by United Nations Environment Programme and Green Climate Fund. Results have been used in national risk assessments at ministries in United States Department of Energy, Ministry of Defence (United Kingdom), and German Federal Environment Agency, and in corporate resilience planning by firms such as Shell plc and BP plc. Peer-reviewed syntheses have been published in journals associated with Nature Climate Change, Proceedings of the National Academy of Sciences, and Geophysical Research Letters, and have influenced scenario use in reports by World Resources Institute, Carbon Disclosure Project, and International Renewable Energy Agency.

Participating Models and Institutions

Participants include integrated assessment models like MESSAGE, REMIND, GCAM, IMAGE, and WITCH; Earth system and climate models such as HadGEM, CESM, MPI-ESM, GFDL CM4, and IPSL-CM; and sectoral or impact models developed at Potsdam Institute for Climate Impact Research, National Institute for Environmental Studies, Japanese Research Institute for Humanity and Nature, and Canadian Centre for Climate Modelling and Analysis. Institutional partners include European Commission Joint Research Centre, United Nations Development Programme, Asian Development Bank, African Development Bank, Australian Bureau of Meteorology, and regional consortia like Asia-Pacific Economic Cooperation research networks.

Criticisms and Limitations

Critics highlight dependence on scenario archetypes derived from Shared Socioeconomic Pathways and Representative Concentration Pathways, arguing these can embed assumptions rooted in modeling cultures at Stanford University, Massachusetts Institute of Technology, and Imperial College London, potentially biasing policy-relevant outputs. Limitations include coarse resolution relative to impacts modeled by institutions such as Inter-American Development Bank or World Agroforestry Centre, challenges in representing equity concerns emphasized by United Nations Development Programme, and difficulties reconciling economic modules used in International Monetary Fund analyses with physical processes modeled at Max Planck Institute for Meteorology or National Center for Atmospheric Research. Debates persist about scenario governance, transparency, and accessibility involving stakeholders like Open Knowledge Foundation, Data.gov, and Creative Commons advocates.

Category:Climate modeling