Abstract
Climate change is expected to affect health through changes in exposure to weather disasters. Vulnerability to coastal flooding has decreased in recent decades but remains disproportionately high in low-income countries. We developed a new statistical model for estimating future storm surge-attributable mortality. The model accounts for sea-level rise and socioeconomic change, and allows for an initial increase in risk as low-income countries develop. We used observed disaster mortality data to fit the model, splitting the dataset to allow the use of a longer time-series of high intensity, high mortality but infrequent events. The model could not be validated due to a lack of data. However, model fit suggests it may make reasonable estimates of log mortality risk but that mortality estimates are unreliable. We made future projections with and without climate change (A1B) and sea-based adaptation, but given the lack of model validation we interpret the results qualitatively. In low-income countries, risk initially increases with development up to mid-century before decreasing. If implemented, sea-based adaptation reduces climate-associated mortality in some regions, but in others mortality remains high. These patterns reinforce the importance of implementing disaster risk reduction strategies now. Further, while average mortality changes discontinuously over time, vulnerability and risk are evolving conditions of everyday life shaped by socioeconomic processes. Given this, and the apparent importance of socioeconomic factors that condition risk in our projections, we suggest future models should focus on estimating risk rather than mortality. This would strengthen the knowledge base for averting future storm surge-attributable health impacts.
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Notes
Throughout, we use “cyclones” as a general term to refer to any major wind storm that may be associated with a storm surge; e.g., extra-tropical storms, hurricanes, tropical cyclones, typhoons etc.
Abbreviations
- DIVA:
-
Dynamic Interactive Vulnerability Assessment
- EM-DAT:
-
Emergency Events Database
- GCM:
-
General Circulation Model
- GDP:
-
Gross Domestic Product
- HDI:
-
Human Development Index
- LHS:
-
Left-hand side
- RHS:
-
Right-hand side
- SLR:
-
Sea-level rise
- UN:
-
United Nations
- UNDP:
-
United Nations Development Programme
- WPP:
-
World Population Prospects
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Acknowledgments
This project was funded by the Natural Environment Research Council under the QUEST (Quantifying and Understanding the Earth System) project: contract numbers NE/E001874/1 and NE/E001882/1. For the sea level rise projections, we thank the international modelling groups for providing their data for analysis, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) for collecting and archiving the model data, the JSC/CLIVAR Working Group on Coupled Modelling (WGCM) and their Coupled Model Intercomparison Project (CMIP) and Climate Simulation Panel for organising the model data analysis activity, and the IPCC WG1 TSU for technical support. The IPCC Data Archive at Lawrence Livermore National Laboratory is supported by the Office of Science, US Department of Energy. For the flood disaster data, we thank EM-DAT: The OFDA/CRED International Disaster Database at the Université Catholique de Louvain, Brussels, Belgium (www.emdat.be).
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This article is part of a Special Issue on “The QUEST-GSI Project” edited by Nigel Arnell
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Lloyd, S.J., Kovats, R.S., Chalabi, Z. et al. Modelling the influences of climate change-associated sea-level rise and socioeconomic development on future storm surge mortality. Climatic Change 134, 441–455 (2016). https://doi.org/10.1007/s10584-015-1376-4
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DOI: https://doi.org/10.1007/s10584-015-1376-4