Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Characterizing uncertain sea-level rise projections to support investment decisions
Univ Illinois, Dept Atmospher Sci, Urbana, IL 61801 USA..
RAND Corp, Santa Monica, CA USA..
KTH, School of Architecture and the Built Environment (ABE), Philosophy and History. Penn State Univ, Earth & Environm Syst Inst, University Pk, PA 16802 USA..ORCID iD: 0000-0001-6388-8674
Penn State Univ, Earth & Environm Syst Inst, University Pk, PA 16802 USA.;Penn State Univ, Dept Geosci, University Pk, PA 16802 USA.;Carnegie Mellon Univ, Dept Engn & Publ Policy, Pittsburgh, PA 15213 USA..
2018 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 13, no 2, article id e0190641Article in journal (Refereed) Published
Abstract [en]

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE , 2018. Vol. 13, no 2, article id e0190641
National Category
Medical Ethics
Identifiers
URN: urn:nbn:se:kth:diva-225309DOI: 10.1371/journal.pone.0190641ISI: 000424325300009Scopus ID: 2-s2.0-85041495721OAI: oai:DiVA.org:kth-225309DiVA, id: diva2:1195243
Note

QC 20180404

Available from: 2018-04-04 Created: 2018-04-04 Last updated: 2018-04-04Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Wikman-Svahn, Per

Search in DiVA

By author/editor
Wikman-Svahn, Per
By organisation
Philosophy and History
In the same journal
PLoS ONE
Medical Ethics

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 33 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf