Challenges in the harmonisation of global integrated assessment models: A comprehensive methodology to reduce model response heterogeneity

Harmonisation sets the ground to a solid inter-comparison of integrated assessment models. A clear and transparent harmonisation process promotes a consistent interpretation of the modelling outcomes divergences and, reducing the model variance, is instrumental to the use of integrated assessment models to support policy decision-making. Despite its crucial role for climate economic policies, the definition of a comprehensive harmonisation methodology for integrated assessment modelling remains an open challenge for the scientific community. This paper proposes a framework for a harmonisation methodology with the definition of indispensable steps and recommendations to overcome stumbling blocks in order to reduce the variance of the outcomes which depends on controllable modelling assumptions. The harmonisation approach of the PARIS REINFORCE project is presented here to layout such a framework. A decomposition analysis of the harmonisation process is shownthrough 6 integrated assessment models (GCAM, ICES-XPS, MUSE, E3ME, GEMINI-E3, and TIAM). Results prove the potentials of the proposed framework to reduce the model variance and present a powerful diagnostic tool to feedback on the quality of the harmonisation itself. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).

Automated summary

Harmonisation plays a crucial role in facilitating consistent interpretation of integrated assessment model outcomes and reducing model variance, thus supporting policy decision-making for climate economic policies. However, defining a comprehensive harmonisation methodology for integrated assessment modelling remains a challenge for the scientific community. This paper proposes a framework with indispensable steps and recommendations to reduce model variance, showcasing the potential benefits through a decomposition analysis of six integrated assessment models. The approach presented offers a powerful diagnostic tool to assess and improve the quality of harmonisation.