Reduced Complexity Model Intercomparison Project Phase 3: protocol and preliminary results

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Authors: Alejandro Romero-Prieto, Marit Sandstad, Benjamin M. Sanderson, Zebedee Nicholls, Norman Julius Steinert, Thomas Gasser, Camilla Mathison, Jarmo Kikstra, Thomas J. Aubry, Katsumasa Tanaka, K. Weber, Chris Smith
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Abstract

Reduced-complexity models (RCMs) are a critical tool in climate science. Their computational efficiency enables applications beyond the reach of more complex models, including uncertainty quantification, the integration of multiple lines of evidence via ensemble constraining, and running large scenario sets in the span of a few days. Thanks to these capabilities, RCMs played important roles in previous IPCC assessments, and are poised to play an important role in the upcoming Seventh Assessment Report (AR7). A key example is evaluating the climate response to the thousands of emissions scenarios in the peer-reviewed literature created with integrated assessment models. However, whether/which RCMs are suitable for performing such a task is contingent on their ability to faithfully emulate the behaviour of more complex models and observed climate change.The Reduced-Complexity Model Intercomparison Project (RCMIP) was established to assess this capability, as well as to better understand inter-RCM differences (Nicholls et al., 2020; Nicholls et al., 2021). Here, we introduce the protocol for the third and latest phase, RCMIP3. This phase focuses on two priorities. First, it provides a common set of observational benchmarks to be optionally used for ensemble constraining prior to submission, with the objective of mitigating discrepancies arising from different calibration methodologies and facilitating a clearer assessment of intrinsic model differences. Second, it requests an expanded set of variables and experiments from modelling teams to enable a more thorough evaluation of the carbon cycle representation in these models – a key gap in previous RCMIP phases. Additionally, RCMIP3 includes many of the experiments in the “Assessment Fast Track" (AFT) of the Coupled Model Intercomparison Project Phase 7 (CMIP7). As a result, RCMIP3 will improve our understanding of future model differences under these experiments, in addition to providing the community with valuable early projections.The presentation will outline the RCMIP3 protocol and highlight the types of analyses it enables, along with preliminary results. By explicitly comparing RCM outputs with both ESM simulations and observations, RCMIP3 aims to strengthen the linkage across the climate-model hierarchy as well as evaluating and showcasing the suitability of RCMs for climate assessment.Nicholls, Z., Meinshausen, M., Lewis, J., Corradi, M.R., Dorheim, K., Gasser, T., Gieseke, R., Hope, A.P., Leach, N.J., McBride, L.A., Quilcaille, Y., Rogelj, J., Salawitch, R.J., Samset, B.H., Sandstad, M., Shiklomanov, A., Skeie, R.B., Smith, C.J., Smith, S.J., Su, X., Tsutsui, J., Vega-Westhoff, B. and Woodard, D.L. 2021. Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections. Earth’s Future. 9(6), https://doi.org/10.1029/2020EF001900.Nicholls, Z.R.J., Meinshausen, M., Lewis, J., Gieseke, R., Dommenget, D., Dorheim, K., Fan, C.-S., Fuglestvedt, J.S., Gasser, T., Golüke, U., Goodwin, P., Hartin, C., Hope, A.P., Kriegler, E., Leach, N.J., Marchegiani, D., McBride, L.A., Quilcaille, Y., Rogelj, J., Salawitch, R.J., Samset, B.H., Sandstad, M., Shiklomanov, A.N., Skeie, R.B., Smith, C.J., Smith, S., Tanaka, K., Tsutsui, J. and Xie, Z. 2020. Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response. Geoscientific Model Development. 13(11), pp.5175–5190, https://doi.org/10.5194/gmd-13-5175-2020.

Fields of Study & Subjects

Climate variability and models Climate Change Policy and Economics Meteorological Phenomena and Simulations

Publication details

Journal / source
EGU General Assembly Conference Abstracts
Publication date
13 March 2026
Language
EN