AbstractSea level rise, as a result of climate change, is expected to drive coastal hazards that could bring significant damages to coastal regions in the future. However, high uncertainties remain in the projections of sea level rise from different climate scenarios and sea level rise prediction models. Quantification and integration of these uncertainties are essential to better inform coastal planning and decision making for climate adaptation, critical for infrastructure sustainability and resilience. This paper advances knowledge cross-cutting structural engineering and climate change in the face of multihazards via a novel framework termed the Probabilistic Sea Level Rise Hazard Analysis (PSLRHA). This study uses the current generation of models and protocols from the climate science research community to better portray the future climate and project sea level rise. The aggregation process produces the probability of exceeding a specific sea level rise threshold at a certain location and facilitates the creation of the global sea level rise hazard map. The relative importance of each climate scenario and sea level rise contributing models are demonstrated via the deaggregation process. We identify the models that have most contribution to extreme sea level rise thresholds, with large fluctuations in the high thresholds among ice sheet models. Finally, we show the practical implementation of PSLRHA results via compound flooding analyses using Houston as an illustrative example.

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