Unknown

Dataset Information

0

Non-linear interaction modulates global extreme sea levels, coastal flood exposure, and impacts.


ABSTRACT: We introduce a novel approach to statistically assess the non-linear interaction of tide and non-tidal residual in order to quantify its contribution to extreme sea levels and hence its role in modulating coastal protection levels, globally. We demonstrate that extreme sea levels are up to 30% (or 70?cm) higher if non-linear interactions are not accounted for (e.g., by independently adding astronomical and non-astronomical components, as is often done in impact case studies). These overestimates are similar to recent sea-level rise projections to 2100 at some locations. Furthermore, we further find evidence for changes in this non-linear interaction over time, which has the potential for counteracting the increasing flood risk associated with sea-level rise and tidal and/or meteorological changes alone. Finally, we show how accounting for non-linearity in coastal impact assessment modulates coastal exposure, reducing recent estimates of global coastal flood costs by ~16%, and population affected by ~8%.

SUBMITTER: Arns A 

PROVIDER: S-EPMC7174334 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

altmetric image

Publications

Non-linear interaction modulates global extreme sea levels, coastal flood exposure, and impacts.

Arns Arne A   Wahl Thomas T   Wolff Claudia C   Vafeidis Athanasios T AT   Haigh Ivan D ID   Woodworth Philip P   Niehüser Sebastian S   Jensen Jürgen J  

Nature communications 20200421 1


We introduce a novel approach to statistically assess the non-linear interaction of tide and non-tidal residual in order to quantify its contribution to extreme sea levels and hence its role in modulating coastal protection levels, globally. We demonstrate that extreme sea levels are up to 30% (or 70 cm) higher if non-linear interactions are not accounted for (e.g., by independently adding astronomical and non-astronomical components, as is often done in impact case studies). These overestimates  ...[more]

Similar Datasets

| S-EPMC6006144 | biostudies-literature
| S-EPMC7162943 | biostudies-literature
| S-EPMC6739477 | biostudies-literature
| S-EPMC4367969 | biostudies-literature
| S-EPMC10987583 | biostudies-literature
| S-EPMC7393110 | biostudies-literature
| S-EPMC6416275 | biostudies-literature
| S-EPMC3948227 | biostudies-literature
| S-EPMC8847277 | biostudies-literature
| S-EPMC8213734 | biostudies-literature