Date of Award

Spring 2018

Document Type

Dissertation - Restricted

Degree Name

Doctor of Philosophy (PhD)

Department

Civil, Construction, and Environmental Engineering

First Advisor

Lin, Ting

Second Advisor

Corliss, George

Third Advisor

Feng, Xizhou

Abstract

Sea-level rise, driven by climate change, puts coastal communities and ecosystems at risk. Major sources that contribute to sea-level rise include ocean thermal expansion, glacier loss, and ice sheet loss. Here we account for uncertainty in modeling these sources, along with climate forcing uncertainty.Ocean thermal expansion uncertainty is modeled using a probabilistic ensemble of climate models and climate forcing scenarios. The ensemble addresses model uniqueness and weights models and scenarios based on their ability to reproduce observed sea-level trends. Glacier sea-level rise is modeled by updating an existing glacier mass balance model with a probabilistic regional covariance model that addresses the scarcity of historical glacier observational data. This model is used to simulate glacier melt and associated patterns of sea-level rise. Ice sheet mass balance change is modeled using a kernel-density-based probabilistic ensemble of perturbed physics ice sheet models. The kernel-density model does not need to assume the shape of the ice sheet sampling space and rewards ice sheet models that reproduce observed ice sheet physics.As the computational cost of climate and ice sheet models can make probabilistic studies difficult, emulation methods are explored for estimating model outputs for forcing scenarios of interest. A nonlinear dual model for emulating climate model thermosteric and dynamic sea-level rise predictions is shown to outperform existing linear methods. Climate forcing is modeled using a probabilistic emissions rate growth model that addresses the impact of international climate agreements and estimates the relative likelihoods of forcing scenarios. Climate agreements have a large influence on the relative likelihoods of low mitigation forcing scenarios.Probabilistic sea-level rise hazard analysis is illustrated using a set of sea-level rise prediction models and forcing scenarios. Deaggregation of hazard analysis results show that ice sheet model projections and climate forcing dominate probabilistic sea-level rise hazard. Probabilistic hazard analysis is a step toward informing decision makers about how to mitigate and adapt to future sea-level rise.

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