Inter-Sectoral Impact Model Intercomparison Project (ISI

Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): Project framework, The. Warszawski, L., Frieler, K., Huber, V., Piontek, F., Serdeczny, O., & Schewe, J. Proceedings of the National Academy of Sciences, 111(9):3228–3232, March, 2014.

Paper doi abstract bibtex

The Inter-Sectoral Impact Model Intercomparison Project offers a framework to compare climate impact projections in different sectors and at different scales. Consistent climate and socio-economic input data provide the basis for a cross-sectoral integration of impact projections. The project is designed to enable quantitative synthesis of climate change impacts at different levels of global warming. This report briefly outlines the objectives and framework of the first, fast-tracked phase of Inter-Sectoral Impact Model Intercomparison Project, based on global impact models, and provides an overview of the participating models, input data, and scenario set-up.

@article{warszawski_inter-sectoral_2014,
	title = {Inter-{Sectoral} {Impact} {Model} {Intercomparison} {Project} ({ISI}–{MIP}): {Project} framework, {The}},
	volume = {111},
	issn = {0027-8424, 1091-6490},
	shorttitle = {The {Inter}-{Sectoral} {Impact} {Model} {Intercomparison} {Project} ({ISI}–{MIP})},
	url = {http://www.pnas.org/lookup/doi/10.1073/pnas.1312330110},
	doi = {10.1073/pnas.1312330110},
	abstract = {The Inter-Sectoral Impact Model Intercomparison Project offers a framework to compare climate impact projections in different sectors and at different scales. Consistent climate and socio-economic input data provide the basis for a cross-sectoral integration of impact projections. The project is designed to enable quantitative synthesis of climate change impacts at different levels of global warming. This report briefly outlines the objectives and framework of the first, fast-tracked phase of Inter-Sectoral Impact Model Intercomparison Project, based on global impact models, and provides an overview of the participating models, input data, and scenario set-up.},
	language = {en},
	number = {9},
	urldate = {2017-07-31},
	journal = {Proceedings of the National Academy of Sciences},
	author = {Warszawski, Lila and Frieler, Katja and Huber, Veronika and Piontek, Franziska and Serdeczny, Olivia and Schewe, Jacob},
	month = mar,
	year = {2014},
	keywords = {Damages, GA, Geography: Global, IAM: Yes, Issue, Method: Process-based, Sector: Other},
	pages = {3228--3232},
}

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