SUPREMA - SUpport for Policy RElevant Modelling of Agriculture

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Dataset information

Country of origin
Updated
2020.07.22 00:00
Created
2020.07.22
Available languages
English
Keywords
MAGNET, farm to fork, MITERRA, IFM-CAP, CAP reform, green deal, SUPREMA, GLOBIOM, AGMEMOD, GHG, CAPRI, sustainable diets, MITERRA-EUROPE, climate change, agriculture, CAP
Quality scoring
270

Dataset description

Impact assessments for agriculture are partly based on projections delivered by models. Sectoral policies are becoming more and more interrelated. Hence, there is a need to improve the capacity of current models, connect them or redesign them to deliver on an increasing variety of policy objectives, and to explore future directions for agricultural modelling in Europe. SUPREMA (SUpport for Policy RElevant Modelling of Agriculture) is a project that has received funding from the European Union’s Horizon 2020 research and innovation programme (under grant agreement No 773499 SUPREMA) and that came to address this challenge by proposing a meta-platform that supports modelling groups linked already through various other platforms and networks. SUPREMA should help close the gaps between expectations of policy makers and the actual capacity of models to deliver relevant policy analysis. The SUPREMA model family includes a set of ‘core models’ that are already used in support of key European impact assessments in agriculture, trade, climate and bioenergy policies. One of the work-packages of the project ("Testing the SUPREMA model family") had the objective of testing the SUPREMA model family comparing model outcomes of three applications, including: (i) harmonize baseline assumptions and to the extent possible align baseline projections across models in the platform, and (ii) showcase the potential of the models in the meta-platform to respond to the upcoming and existing policy needs by means of two exploratory policy scenarios. This open dataset includes 3 components: 1 - (Baseline scenario) - the harmonized baselines (for 2030 and 2050). Please note that the baseline projections do not take into account the 2020 and possible future effects of the SARS-CoV-2 pandemic 2 - (Agricultural policy scenario) - medium-term horizon scenarios aiming comparing different models and/or model combinations, that have a large degree of ‘similarity’ such as joined indicator variables, i.e.: AGMEMOD-MITERRA (combined) modelling tool and the CAPRI model. The main focus was comparing model results in both agronomic and biophysical domains. Two variants of the agricultural policy scenario have been simulated and compared: (i) a CAP greening scenario; and (ii) a sustainable diet scenario. Both scenarios are hypothetical but have been chosen in such a way that the can provide insights in future policy issues as: (i) a further greening of the CAP fits in the policy implementation space as it is included in the ongoing policy reform of the CAP after 2020; and (ii) as increasing consumer awareness about healthy diets and their relation to meat consumption, as well as the footprint/climate consequences are highly relevant with respect to the Green Deal roadmap (December 2019) and the Farm to Fork Strategy (May 2020) documents that have been recently published. 3 - (Climate change mitigation scenario) - scenarios that quantifies the GHG mitigation potential of the EU’s agricultural sector and domestic and global impacts of the EU policy, conditional on different levels of GHG mitigation efforts in the rest of the world. These are obtained through the SUPREMA models CAPRI, GLOBIOM and MAGNET and include scenarios where the EU only takes ambitious unilateral climate action up to scenario where the 1.5 C target is pursued globally SUPREMA has been coordinated by Wageningen Research with the participation of EuroCARE, Thünen Institute, Swedish University of Agricultural Sciences (SLU), European Commission Joint Research Centre (JRC) and Research Executive Agency (REA), International Institute for Applied Systems Analysis (IIASA) and Universidad Politécnica de Madrid (UPM).
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