Adaptation to climate change: a comparative analysis of modelling methods for heat-related mortality

Gosling, Simon N. and Hondula, David M. and Bunker, Aditi and Ibarreta, Dolores and Liu, Junguo and Zhang, Xinxin and Sauerborn, Rainer (2017) Adaptation to climate change: a comparative analysis of modelling methods for heat-related mortality. Environmental Health Perspectives, 125 (8). 087008/1-087008/14. ISSN 1552-9924

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Background: Multiple methods are employed for modelling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known on the relative sensitivity of impacts to “adaptation uncertainty” (i.e. the inclusion/exclusion of adaptation modelling), relative to using multiple climate models and emissions scenarios.

Objectives: (1) Compare the range in projected impacts that arises from using different adaptation modelling methods; (2) compare the range in impacts that arises from adaptation uncertainty to ranges from using multiple climate models and emissions scenarios; (3) recommend modelling method(s) to use in future impact assessments.

Methods: We estimated impacts for 2070-2099, for 14 European cities, applying six different methods for modelling adaptation; also with climate projections from five climate models, run under two emissions scenarios to explore the relative effects of climate modelling and emissions uncertainty.

Results: The range of the difference (%) in impacts between including and excluding adaptation, irrespective of climate modelling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modelling and emissions uncertainty.

Conclusions: Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modelling. We recommend absolute threshold shifts and reductions in slope.

Item Type: Article
Additional Information: Reproduced with permission from Environmental Health Perspectives
Schools/Departments: University of Nottingham, UK > Faculty of Social Sciences > School of Geography
Identification Number: 10.1289/EHP634
Depositing User: Eprints, Support
Date Deposited: 07 Nov 2016 09:18
Last Modified: 30 Nov 2017 18:43

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