Sandy shorelines are constantly evolving, threatening frequently human assets such as buildings or transport infrastructure. In these environments, sea-level rise will exacerbate coastal erosion to an amount which remains uncertain. Sandy shoreline change projections inherit the uncertainties of future mean sea-level changes, of vertical ground motions, and of other natural and anthropogenic processes affecting shoreline change variability and trends. Furthermore, the erosive impact of sea-level rise itself can be quantified using two fundamentally different models. Here, we show that this latter source of uncertainty, which has been little quantified so far, can account for 20 to 40% of the variance of shoreline projections by 2100 and beyond. This is demonstrated for four contrasting sandy beaches that are relatively unaffected by human interventions in southwestern France, where a variance-based global sensitivity analysis of shoreline projection uncertainties can be performed owing to previous observations of beach profile and shoreline changes. This means that sustained coastal observations and efforts to develop sea-level rise impact models are needed to understand and eventually reduce uncertainties of shoreline change projections, in order to ultimately support coastal land-use planning and adaptation.
Figures 3 and 4 of the article 'Bounding probabilistic sea-level projections within the framework of the possibility theory' display a minimum value for sea level rise of 15 cm by 2100 with respect to the 1986-2005 mean for the RCP 8.5. The value of 15 cm is consistent with sea level rise rates dropping back to velocities observed during the 20th century according to recent studies, but not to the current sea level rise velocity of 3.4 mm yr −1 , as incorrectly stated in the article. This error has no impact on the rest of the article, including its arguments and conclusions, but it is potentially confusing for scientists willing to reproduce the left side of figures 3 and 4. We apologise for any inconvenience caused. ReferencesCazenave A, Dieng H B, Meyssignac B, Von Schuckmann K, Decharme B and Berthier E 2014 The rate of sea-level rise Nat. Clim. Change 4 358-61 Dangendorf S, Marcos M, Wöppelmann G, Conrad C P, Frederikse T and Riva R 2017 Reassessment of 20th century global mean sea level rise Proc. Natl Acad. Sci. 114 5946-51 Hay C C, Morrow E, Kopp R E and Mitrovica J X 2015 Probabilistic reanalysis of twentieth-century sea-level rise Nature 517 481-4 Kopp R E, Horton R M, Little C M, Mitrovica J X, Oppenheimer M, Rasmussen D J and Tebaldi C 2014 Probabilistic 21st and 22nd century sea-level projections at a global network of tide-gauge sites Earth's Future 2 383-406 Le Cozannet G, Manceau J C and Rohmer J 2017 Bounding probabilistic sea-level projections within the framework of the possibility theory Environ. Res. Lett. 12 014012 AbstractDespite progresses in climate change science, projections of future sea-level rise remain highly uncertain, especially due to large unknowns in the melting processes affecting the ice-sheets in Greenland and Antarctica. Based on climate-models outcomes and the expertise of scientists concerned with these issues, the IPCC provided constraints to the quantiles of sea-level projections. Moreover, additional physical limits to future sea-level rise have been established, although approximately. However, many probability functions can comply with this imprecise knowledge. In this contribution, we provide a framework based on extra-probabilistic theories (namely the possibility theory) to model the uncertainties in sea-level rise projections by 2100 under the RCP 8.5 scenario. The results provide a concise representation of uncertainties in future sea-level rise and of their intrinsically imprecise nature, including a maximum bound of the total uncertainty. Today, coastal impact studies are increasingly moving away from deterministic sea-level projections, which underestimate the expectancy of damages and adaptation needs compared to probabilistic laws. However, we show that the probability functions used so-far have only explored a rather conservative subset of sea-level projections compliant with the IPCC. As a consequence, coastal impact studies relying on these probabilistic sea-level projections are expected to underestimate the possibility of large damages and adaptation ...
The dependence between extreme storm surges and wind waves is assessed statistically along the global coasts using the outputs of two numerical models consistently forced with the same atmospheric fields. We show that 55% of the world coastlines face compound storm surge wave extremes. Hence, for a given level of probability, neglecting these dependencies leads to underestimating extreme coastal water levels. Dependencies are dominant in midlatitudes and are likely underestimated in the tropics due to limited representation of tropical cyclones. Furthermore, we show that in half of the areas with dependence, the estimated probability of occurrence of coastal extreme water levels increases significantly when it is accounted for. Translated in terms of return periods, this means that along 30% of global coastlines, extreme water levels expected at most once in a century without considering dependence between storm surges and waves become a 1 in 50‐year event.
International audienceAs sea-level rises, the frequency of coastal marine flooding events is changing. For accurate assessments, several other factors must be considered as well, such as the variability of sea-level rise and storm surge patterns. Here, a global sensitivity analysis is used to provide quantitative insight into the relative importance of contributing uncertainties over the coming decades. The method is applied on an urban low-lying coastal site located in the north-western Mediterranean, where the yearly probability of damaging flooding could grow drastically after 2050 if sea-level rise follows IPCC projections. Storm surge propagation processes, then sea-level variability, and, later, global sea-level rise scenarios become successively important source of uncertainties over the 21st century. This defines research priorities that depend on the target period of interest. On the long term, scenarios RCP 6.0 and 8.0 challenge local capacities of adaptation for the considered site
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