An Innovative Approach to Multi-Method Integrated Assessment Modelling of Global Climate Change

Siebers, Peer-Olaf and Lim, Zhi En and Figueredo, Grazziela P. and Hey, James (2020) An Innovative Approach to Multi-Method Integrated Assessment Modelling of Global Climate Change. Journal of Artificial Societies and Social Simulation, 23 (1). ISSN 1460-7425

[thumbnail of get_pdf.php] Text
get_pdf.php - Published Version

Download (66B)

Abstract

Modelling and simulation play an increasingly significant role in exploratory studies for informing policy makers on climate change mitigation strategies. There is considerable research being done in creating Integrated Assessment Models (IAMs), which focus on examining the human impacts on climate change. Many popular IAMs are created as steady state optimisation models. They typically employ a nested structure of neoclassical production functions to represent the energy-economy system, holding aggregate views on variables, and hence are unable to capture a finer level of details of the underlying system components. An alternative approach that allows modelling populations as a collection of individual and unevenly distributed entities is Agent-Based Modelling, often used in the field of Social Simulation. But simulating huge numbers of individual entities can quickly become an issue, as it requires large amounts of computational resources. The goal of this paper is to introduce a conceptual framework for developing hybrid IAMs. This novel modelling approach allows us to reuse existing rigid, but well-established IAMs, and adds more flexibility by replacing aggregate stocks with a community of vibrant interacting entities. We provide a proof-of-concept of the application of this conceptual framework in form of an illustrative example. Our test case takes the settings of the US. It is solely created for the purpose of demonstrating our hybrid modelling approach; we do not claim that it has predictive powers.

Item Type: Article
Subjects: AP Academic Press > Computer Science
Depositing User: Unnamed user with email support@apacademicpress.com
Date Deposited: 04 Sep 2024 03:48
Last Modified: 04 Sep 2024 03:48
URI: http://info.openarchivespress.com/id/eprint/1822

Actions (login required)

View Item
View Item