Abstract
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 shown through 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.
Highlights
Climate change mitigation calls for a collective initiative of the scientific community to provide robust evidence of the consequences of climate actions (IPCC, 2018), and serve scientific research as well as policy design
Historical inventories of CO2, CH4, and pollutants were based on the Community Emissions Data System (CEDS) for Historical Emissions (Hoesly et al, 2018); F-gases were aligned against the NOAA dataset (Chemical Sciences Society, 2018); N2O were aligned against the PRIMAP dataset (Gütschow et al, 2019)
The results are presented for the reference scenario (R), the socio-economic harmonisation scenario (SH), the techno and socio-economic harmonisation scenario (CSH), and for the policy, techno- and socio-economic harmonisation scenario (PSCH) as obtained from the models: E3ME, Global Change Assessment Model (GCAM), GEMINI-E3 (GEM.), Intertemporal Computable Equilibrium System (ICES)-XPS, MUSE, and TIAM
Summary
Climate change mitigation calls for a collective initiative of the scientific community to provide robust evidence of the consequences of climate actions (IPCC, 2018), and serve scientific research as well as policy design. The only existing source known for global data, the SSP database, which has been developed to feed IAMs (Dellink et al, 2017; KC and Lutz, 2017), has not been updated over time, and projections in the 2010–2020 period diverge from observed trends Implementation A key challenge in the historical emissions alignment process, was represented by overcoming the differences between the benchmark databases and the model-specific calibration database. Overall energy access is under-represented, as only 1 policy is present in the database
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