dc.contributor.author | Abadie, Luis María | |
dc.contributor.author | Galarraga, Ibon | |
dc.contributor.author | Sainz de Murieta Zugadi, Elisa | |
dc.date.accessioned | 2017-02-23T14:46:26Z | |
dc.date.available | 2017-02-23T14:46:26Z | |
dc.date.issued | 2017-01-17 | |
dc.identifier.citation | Environmental Research Letters 12(1) (2017)//014017 | es |
dc.identifier.issn | 1748-9326 | |
dc.identifier.uri | http://hdl.handle.net/10810/20791 | |
dc.description.abstract | A quantification of present and future mean annual losses due to extreme coastal events can be crucial for adequate decision making on adaptation to climate change in coastal areas around the globe. However, this approach is limited when uncertainty needs to be accounted for. In this paper, we assess coastal flood risk from sea-level rise and extreme events in 120 major cities around the world using an alternative stochastic approach that accounts for uncertainty. Probability distributions of future relative (local) sea-level rise have been used for each city, under three IPPC emission scenarios, RCP 2.6, 4.5 and 8.5. The approach allows a continuous stochastic function to be built to assess yearly evolution of damages from 2030 to 2100. Additionally, we present two risk measures that put low-probability, high-damage events in the spotlight: the Value at Risk (VaR) and the Expected Shortfall (ES), which enable the damages to be estimated when a certain risk level is exceeded. This level of acceptable risk can be defined involving different stakeholders to guide progressive adaptation strategies. The method presented here is new in the field of economics of adaptation and offers a much broader picture of the challenges related to dealing with climate impacts. Furthermore, it can be applied to assess not only adaptation needs but also to put adaptation into a timeframe in each city. | es |
dc.description.sponsorship | The authors acknowledge funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no 603906, Project: ECONADAPT and Horizon 2020 Project RESIN (grant agreement no. H2020-DRS-9-2014). LMA and IG are grateful for the financial support received from the Basque Government for support via project GIC12/177-IT-399-13. LMA also thanks financial support from the Spanish Ministry of Science and Innovation (ECO2015-68023). | es |
dc.language.iso | eng | es |
dc.publisher | Environmental Research Letters | es |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/653522 | |
dc.relation.ispartofseries | BC3 Journal Articles;JA-1233 | |
dc.rights | info:eu-repo/semantics/openAccess | es |
dc.subject | risk measures | es |
dc.subject | coastal flooding | es |
dc.subject | stochastic models | es |
dc.subject | climate change | es |
dc.subject | progressive adaptation | es |
dc.subject | sea-level rise | es |
dc.title | Understanding risks in the light of uncertainty: low-probability, high-impact coastal events in cities | es |
dc.type | info:eu-repo/semantics/article | es |
dc.rights.holder | Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. | |
dc.relation.publisherversion | http://iopscience.iop.org/article/10.1088/1748-9326/aa5254/meta;jsessionid=42998F0B3643975563AD4967E3B48742.c3.iopscience.cld.iop.org | es |
dc.identifier.doi | 10.1088/1748-9326/aa5254 | |
dc.contributor.funder | European Commission | |