Temporal changes in dependence between compound coastal and inland flooding drivers around the contiguous United States coastline
Flooding in low-lying coastal zones arises from coastal (storm surge, tides, and waves), fluvial (excessive river discharge), and pluvial (excessive surface runoff) drivers. We analyse changes in compound flooding potential around the contiguous United States (CONUS) coastline stemming from select c...
| Published in: | Weather and Climate Extremes |
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| Main Authors: | , , , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Elsevier
2023
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| Subjects: | |
| Online Access: | https://doi.org/10.1016/j.wace.2023.100594 https://doaj.org/article/0c13dca043c340e985cff8313a428054 |
| Summary: | Flooding in low-lying coastal zones arises from coastal (storm surge, tides, and waves), fluvial (excessive river discharge), and pluvial (excessive surface runoff) drivers. We analyse changes in compound flooding potential around the contiguous United States (CONUS) coastline stemming from select combinations of these flooding drivers using long observational records with at least 55 years of data. We assess temporal changes in the tail (extremal) dependence (χ) using a 30-year sliding time window. Periods of strong tail dependence are found for the windows centered between the 1960s and 1980s/1990s at several locations for surge-discharge (S-Q) and surge-precipitation (S–P) combinations. Changes in dependence are associated with large-scale climate indices such as the Arctic Oscillation (AO) and El Nino Southern Oscillation indices (Niño 1.2 and Niño 3), among others. The significance of potential changes in the dependence structure is subsequently tested using Kullback–Leibler (KL) divergence. We find that changes are mostly not significant. Finally, we perform a complete multivariate statistical analysis exemplarily for one selected pair of variables at one location (S-Q in Washington, DC), allowing for varying dependence strength and structure as well as changes in the marginal distributions. Combined changes with increase in the dependence and marginals exacerbate the predicted compound flood potential. The comprehensive analysis presented here provides new insights into how and where compound flooding potential has changed with time, demonstrates associated links with large-scale climate indices, and highlights the effects of changes in the dependence and marginals in a multivariate statistical framework. |
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