Probabilistic Sea Level Rise Hazard Analysis Based on the Current Generation of Data and Protocols
Publication: Journal of Structural Engineering
Volume 149, Issue 3
Abstract
Sea 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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Data Availability Statement
Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request. CMIP6 model simulation data can be retrieved from https://esgf-node.llnl.gov/search/cmip6/. The R codes of Gaussian process emulator that is used to generate the ice sheets’ and glaciers’ projections are accessible on https://github.com/tamsinedwards/emulandice. The FaIR model 500-member ensemble data for both Tier-1 and Tier-2 scenarios are accessible on https://doi.org/10.5281/zenodo.3588880.
Acknowledgments
We acknowledge the World Climate Research Programme (2011)’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank the editor and the reviewers for their careful review and insightful comments that have helped us improve this manuscript. This work is supported in part by the Edward E. Whitacre, Jr., College of Engineering at Texas Tech University under research salary and travel funds awarded to the Principal Investigator T.L.—corresponding (second) author. The funds provide research assistantship support, conference participation, and programming bootcamp training for the lead student author X.L., along with the tuition scholarship from Department of Civil, Environmental, and Construction Engineering. Additional awards from the Innovation Hub and the Office of Research & Innovation to the Principal Investigator T.L. are gratefully acknowledged. Analyses presented herein were performed using the Red Raider computing cluster at Texas Tech University. We thank the team at the High-Performance Computing Center (HPCC) for their generous support. In addition, the equipment support from the Vice President for Research & Innovation for T.L.’s Multi-Hazard Sustainability (HazSus) Research Group is gratefully acknowledged.
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Published In
Journal of Structural Engineering
Volume 149 • Issue 3 • March 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Feb 16, 2022
Accepted: Aug 29, 2022
Published online: Dec 20, 2022
Published in print: Mar 1, 2023
Discussion open until: May 20, 2023
ASCE Technical Topics:
- Bodies of water (by type)
- Climate change
- Climates
- Coastal engineering
- Coastal management
- Coastal processes
- Coasts, oceans, ports, and waterways engineering
- Data analysis
- Disaster risk management
- Disasters and hazards
- Engineering fundamentals
- Environmental engineering
- Mathematics
- Methodology (by type)
- Natural disasters
- Ocean currents
- Probability
- Research methods (by type)
- Sea level
- Seas and oceans
- Water and water resources
- Water management
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