Preprints
https://doi.org/10.5194/gmd-2021-79
https://doi.org/10.5194/gmd-2021-79

Submitted as: model description paper 12 May 2021

Submitted as: model description paper | 12 May 2021

Review status: a revised version of this preprint was accepted for the journal GMD and is expected to appear here in due course.

Minimal CMIP Emulator (MCE v1.2): A new simplified method for probabilistic climate projections

Junichi Tsutsui Junichi Tsutsui
  • Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry, Abiko, 270-1194, Japan

Abstract. Climate model emulators have a crucial role in assessing warming levels of many emission scenarios from probabilistic climate projections, based on new insights into Earth system response to CO2 and other forcing factors. This article describes one such tool, MCE, from model formulation to application examples associated with a recent model intercomparison study. The MCE is based on impulse response functions and parameterized physics of effective radiative forcing and carbon uptake over ocean and land. Perturbed model parameters for probabilistic projections are generated from statistical models and constrained with a Metropolis-Hastings independence sampler. A part of the model parameters associated with CO2-induced warming have a covariance structure, as diagnosed from complex climate models of the Coupled Model Intercomparison Project (CMIP). Although perturbed ensembles can cover the diversity of CMIP models effectively, they need to be constrained toward substantially lower climate sensitivity for the resulting historical warming to agree with the observed trends over recent decades. The model's simplicity and resulting successful calibration imply that a method with less complicated structures and fewer control parameters offers advantages when building reasonable perturbed ensembles in a transparent way. Experimental results for future scenarios show distinct differences between CMIP- and observation-consistent ensembles, suggesting that perturbed ensembles for scenario assessment need to be properly constrained with new insights into forced response over historical periods.

Junichi Tsutsui

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-79', Anonymous Referee #1, 30 Jul 2021
    • AC1: 'Reply on RC1', Junichi Tsutsui, 19 Oct 2021
  • RC2: 'Review of MCE v1.2 by Junichi Tsutsui', Christopher Smith, 23 Sep 2021
    • AC2: 'Reply on RC2', Junichi Tsutsui, 19 Oct 2021
  • AC3: 'Comment on gmd-2021-79', Junichi Tsutsui, 19 Oct 2021

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-79', Anonymous Referee #1, 30 Jul 2021
    • AC1: 'Reply on RC1', Junichi Tsutsui, 19 Oct 2021
  • RC2: 'Review of MCE v1.2 by Junichi Tsutsui', Christopher Smith, 23 Sep 2021
    • AC2: 'Reply on RC2', Junichi Tsutsui, 19 Oct 2021
  • AC3: 'Comment on gmd-2021-79', Junichi Tsutsui, 19 Oct 2021

Junichi Tsutsui

Model code and software

Minimal CMIP Emulator (MCE v1.2) Junichi Tsutsui https://doi.org/10.5281/zenodo.4604695

Junichi Tsutsui

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Short summary
A new simple climate model, MCE, was developed. It can emulate the basic behavior of comprehensive climate models in a minimal way with sufficient accuracy, providing a reasonable way to assess climate change mitigation scenarios in terms of consistency with long-term temperature goals. The model's simple structure is suitable for building probability distributions of key model parameters, such that they reflect uncertainty ranges of multiple climate projections and observed warming trends.