Illustrative Analysis of Probabilistic Sea Level Rise Hazard

• Published in: Journal of Climate
• Main Authors: Thomas, Matthew A., Lin, Ting
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Meteorological Society 2020
• Subjects: Sea Level; Sensitivity Studies; Bayesian Methods; Probability Forecasts/Models/Distribution; Ensembles; Ice Sheet
• Online Access: https://hdl.handle.net/2346/86870; https://doi.org/10.1175/JCLI-D-19-0320.1

© Copyright 2020 American Meteorological Society (AMS). For permission to reuse any portion of this work, please contact [e-mail]. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act (17 U.S. Code §?107) or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC § 108) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a website or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. All AMS journals and monograph publications are registered with the Copyright Clearance Center (https://www.copyright.com). Additional details are provided in the AMS Copyright Policy statement, available on the AMS website (https://www.ametsoc.org/PUBSCopyrightPolicy). Sea level rise results from several contributing physical processes, including ocean thermal expansion and glacier and ice sheet mass loss. Future projections of sea level remain highly uncertain due to several sources of aleatory and epistemic uncertainty. Quantifying different sources of sea level rise involves considering possible pathways of future radiative forcing and integrating models of different sea level rise processes. The probabilistic hazard analysis strategy has been proposed for combining sea level rise prediction models and climate forcing scenarios to examine sea level rise prediction uncertainty and the sources of this uncertainty. In this study we carry out an illustrative probabilistic sea level rise hazard analysis using ensembles of sea level rise predictions and emissions scenarios from the literature. This illustrative analysis allows us to estimate the probability that sea level rise will exceed a specified threshold at a given location and time and highlights how sea level rise uncertainty is sensitive to scenario inputs and sea level rise projection modeling ...