Exploring low-carbon futures: A web service approach to linking diverse climate-energy-economy models
Fecha
2019Autor
Belete, G.F.
Voinov, A.
Arto, I.
Dhavala, K.
Bulavskaya, T.
Niamir, L.
Moghayer, S.
Filatova, T.
Metadatos
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Energies 12(15) : 2880 (2019)
Resumen
The use of simulation models is essential when exploring transitions to low-carbon futures and climate change mitigation and adaptation policies. There are many models developed to understand socio-environmental processes and interactions, and analyze alternative scenarios, but hardly one single model can serve all the needs. There is much expectation in climate-energy research that constructing new purposeful models out of existing models used as building blocks can meet particular needs of research and policy analysis. Integration of existing models, however, implies sophisticated coordination of inputs and outputs across different scales, definitions, data and software. This paper presents an online integration platform which links various independent models to enhance their scope and functionality. We illustrate the functionality of this web platform using several simulation models developed as standalone tools for analyzing energy, climate and economy dynamics. The models differ in levels of complexity, assumptions, modeling paradigms and programming languages, and operate at different temporal and spatial scales, from individual to global. To illustrate the integration process and the internal details of our integration framework we link an Integrated Assessment Model (GCAM), a Computable General Equilibrium model (EXIOMOD), and an Agent Based Model (BENCH). This toolkit is generic for similar integrated modeling studies. It still requires extensive pre-integration assessment to identify the appropriate models and links between them. After that, using the web service approach we can streamline module coupling, enabling interoperability between different systems and providing open access to information for a wider community of users. © 2019 by the authors.
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