Deep Uncertainty Surrounding Coastal Flood Risk Projections: A Case Study for New Orleans

Future sea-level rise drives severe risks for many coastal communities. Strategies to manage these risks hinge on a sound characterization of the uncertainties. For example, recent studies suggest that large fractions of the Antarctic ice sheet (AIS) may rapidly disintegrate in response to rising gl...

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Main Authors: Wong, Tony E., Keller, Klaus
Format: Text
Language:unknown
Published: arXiv 2017
Subjects:
Online Access:https://dx.doi.org/10.48550/arxiv.1705.07722
https://arxiv.org/abs/1705.07722
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spelling ftdatacite:10.48550/arxiv.1705.07722 2023-05-15T13:38:42+02:00 Deep Uncertainty Surrounding Coastal Flood Risk Projections: A Case Study for New Orleans Wong, Tony E. Keller, Klaus 2017 https://dx.doi.org/10.48550/arxiv.1705.07722 https://arxiv.org/abs/1705.07722 unknown arXiv https://dx.doi.org/10.1002/2017ef000607 arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Geophysics physics.geo-ph FOS Physical sciences article-journal Article ScholarlyArticle Text 2017 ftdatacite https://doi.org/10.48550/arxiv.1705.07722 https://doi.org/10.1002/2017ef000607 2022-04-01T10:53:31Z Future sea-level rise drives severe risks for many coastal communities. Strategies to manage these risks hinge on a sound characterization of the uncertainties. For example, recent studies suggest that large fractions of the Antarctic ice sheet (AIS) may rapidly disintegrate in response to rising global temperatures, leading to potentially several meters of sea-level rise during the next few centuries. It is deeply uncertain, for example, whether such an AIS disintegration will be triggered, how much this would increase sea-level rise, whether extreme storm surges intensify in a warming climate, or which emissions pathway future societies will choose. Here, we assess the impacts of these deep uncertainties on projected flooding probabilities for a levee ring in New Orleans, Louisiana. We use 18 scenarios, presenting probabilistic projections within each one, to sample key deeply uncertain future projections of sea-level rise, radiative forcing pathways, storm surge characterization, and contributions from rapid AIS mass loss. The implications of these deep uncertainties for projected flood risk are thus characterized by a set of 18 probability distribution functions. We use a global sensitivity analysis to assess which mechanisms contribute to uncertainty in projected flood risk over the course of a 50-year design life. In line with previous work, we find that the uncertain storm surge drives the most substantial risk, followed by general AIS dynamics, in our simple model for future flood risk for New Orleans. Text Antarc* Antarctic Ice Sheet DataCite Metadata Store (German National Library of Science and Technology) Antarctic The Antarctic Orleans ENVELOPE(-60.667,-60.667,-63.950,-63.950)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Geophysics physics.geo-ph
FOS Physical sciences
spellingShingle Geophysics physics.geo-ph
FOS Physical sciences
Wong, Tony E.
Keller, Klaus
Deep Uncertainty Surrounding Coastal Flood Risk Projections: A Case Study for New Orleans
topic_facet Geophysics physics.geo-ph
FOS Physical sciences
description Future sea-level rise drives severe risks for many coastal communities. Strategies to manage these risks hinge on a sound characterization of the uncertainties. For example, recent studies suggest that large fractions of the Antarctic ice sheet (AIS) may rapidly disintegrate in response to rising global temperatures, leading to potentially several meters of sea-level rise during the next few centuries. It is deeply uncertain, for example, whether such an AIS disintegration will be triggered, how much this would increase sea-level rise, whether extreme storm surges intensify in a warming climate, or which emissions pathway future societies will choose. Here, we assess the impacts of these deep uncertainties on projected flooding probabilities for a levee ring in New Orleans, Louisiana. We use 18 scenarios, presenting probabilistic projections within each one, to sample key deeply uncertain future projections of sea-level rise, radiative forcing pathways, storm surge characterization, and contributions from rapid AIS mass loss. The implications of these deep uncertainties for projected flood risk are thus characterized by a set of 18 probability distribution functions. We use a global sensitivity analysis to assess which mechanisms contribute to uncertainty in projected flood risk over the course of a 50-year design life. In line with previous work, we find that the uncertain storm surge drives the most substantial risk, followed by general AIS dynamics, in our simple model for future flood risk for New Orleans.
format Text
author Wong, Tony E.
Keller, Klaus
author_facet Wong, Tony E.
Keller, Klaus
author_sort Wong, Tony E.
title Deep Uncertainty Surrounding Coastal Flood Risk Projections: A Case Study for New Orleans
title_short Deep Uncertainty Surrounding Coastal Flood Risk Projections: A Case Study for New Orleans
title_full Deep Uncertainty Surrounding Coastal Flood Risk Projections: A Case Study for New Orleans
title_fullStr Deep Uncertainty Surrounding Coastal Flood Risk Projections: A Case Study for New Orleans
title_full_unstemmed Deep Uncertainty Surrounding Coastal Flood Risk Projections: A Case Study for New Orleans
title_sort deep uncertainty surrounding coastal flood risk projections: a case study for new orleans
publisher arXiv
publishDate 2017
url https://dx.doi.org/10.48550/arxiv.1705.07722
https://arxiv.org/abs/1705.07722
long_lat ENVELOPE(-60.667,-60.667,-63.950,-63.950)
geographic Antarctic
The Antarctic
Orleans
geographic_facet Antarctic
The Antarctic
Orleans
genre Antarc*
Antarctic
Ice Sheet
genre_facet Antarc*
Antarctic
Ice Sheet
op_relation https://dx.doi.org/10.1002/2017ef000607
op_rights arXiv.org perpetual, non-exclusive license
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
op_doi https://doi.org/10.48550/arxiv.1705.07722
https://doi.org/10.1002/2017ef000607
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