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The Radiative Forcing Model Intercomparison Project (RFMIP) is a model intercomparison project designed to diagnose effective radiative forcing and evaluate its uncertainty in Global Climate Models.

As part of the Coupled Model Intercomparison Project phase 7 (CMIP7), the second iteration of the Radiative Forcing Model Intercomparison Project (RFMIP2.0) consists of a series of fixed-Sea Surface Temperature simulations aimed at addressing the following questions:

  1. What is the present-day radiative forcing, and its key anthropogenic contributors, since pre-industrial times?
  2. What is the temporal evolution of the radiative forcing, and its components, over the historical period and into the future?
  3. What is the influence of the underlying climate state on radiative forcing?
  4. To what extent is radiative forcing separable from radiative feedbacks when considering land processes?

Co-chairs:

Ryan Kramer GFDL, NOAA, USA.
Chris Smith Vrije Universiteit Brussel, Belgium & IIASA, Laxenburg, Austria.
Tim Andrews Met Office Hadley Centre, UK & University of Leeds, UK.


news

May 26, 2026 Final version of the RFMIP2.0 Protocol Paper has now been published in Geoscientific Model Development (GMD)! https://gmd.copernicus.org/articles/19/4447/2026/
Sep 29, 2025 Preprint of RFMIP2.0 Protocol Paper at GMD and Open for Discussion
Aug 11, 2025 RFMIP Session at the CMIP6 Community Workshop, March 2026 Japan.
Aug 11, 2025 Sign up to the RFMIP listserv/group for updates

selected publications

  1. The Radiative Forcing Model Intercomparison Project (RFMIP2.0) for CMIP7
    Ryan J. Kramer, Chris Smith, and Timothy Andrews
    Geoscientific Model Development, 2026
  2. Effective radiative forcing and adjustments in CMIP6 models
    Christopher J. Smith, Ryan J. Kramer, Gunnar Myhre, and 26 more authors
    Atmospheric Chemistry and Physics, 2020
  3. The Radiative Forcing Model Intercomparison Project (RFMIP): experimental protocol for CMIP6
    R. Pincus, P. M. Forster, and B. Stevens
    Geoscientific Model Development, 2016