eprintid: 14470 rev_number: 16 eprint_status: archive userid: 353 dir: disk0/00/01/44/70 datestamp: 2017-03-14 08:33:53 lastmod: 2021-08-27 17:28:43 status_changed: 2017-03-14 08:33:53 type: monograph metadata_visibility: show item_issues_count: 1 creators_name: Kovalevskiy, D. creators_name: Shchiptsova, A. creators_name: Rovenskaya, E. creators_name: Hasselmann, K. creators_id: 2049 creators_id: 8206 creators_orcid: 0000-0002-2761-3443 corp_creators: Pavel Kabat, Director General and CEO, IIASA title: Narrowing Uncertainty of Projections of the Global Economy-Climate System Dynamics via Mutually Compatible Integration within Multi-Model Ensembles ispublished: pub divisions: prog_asa abstract: Any model used to derive projections of future climate or assess its impact constitutes a particular simplification of reality. To date, no model building process can guarantee full “objectivity” in the choice of model assumptions and parameterization. In this connection, researchers have introduced a number of stylized integrated assessment models, which attempt to represent the full time-dynamic non-linear causal loop between accumulated emissions, economy and climate, yet in a aggregated, simplified fashion to enable extensive uncertainty analysis with respect to both structural and parametric uncertainty. In this work, we put forward a simplified system dynamics integrated assessment model which simulates the global economic growth, corresponding emissions, global warming and caused by its secondary effects economic losses. While generally our model follows the same logic as DICE and other models of this kind, it pays more attention to the mechanism of the emission reduction. Mitigation is assumed to be done through the allocation of a certain fraction of the total output into enhancing carbon and energy efficiency. The model enables exploring effects of mitigation scenarios defined via carbon tax. We explore the structural sensitivity by examining five alternative climate sensitivity functions and use the "mutual compatibility integration" approach to synthesize the information from the five alternative model versions. date: 2016-09 date_type: published publisher: WP-16-015 creators_browse_id: 280 creators_browse_id: 260 full_text_status: public monograph_type: working_paper place_of_pub: IIASA, Laxenburg, Austria projects: Knowledge Based Climate Mitigation Systems for a Low Carbon Economy (COMPLEX, FP7 308601) coversheets_dirty: FALSE fp7_project: yes fp7_project_id: info:eu-repo/grantAgreement/EC/FP7/308601/EU/Knowledge Based Climate Mitigation Systems for a Low Carbon Economy/COMPLEX fp7_type: info:eu-repo/semantics/book access_rights: info:eu-repo/semantics/openAccess citation: Kovalevskiy, D., Shchiptsova, A. , Rovenskaya, E. ORCID: https://orcid.org/0000-0002-2761-3443 , & Hasselmann, K. (2016). Narrowing Uncertainty of Projections of the Global Economy-Climate System Dynamics via Mutually Compatible Integration within Multi-Model Ensembles. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-16-015 document_url: https://pure.iiasa.ac.at/id/eprint/14470/1/WP-16-015.pdf