scholarly journals Integrating new sea‐level scenarios into coastal risk and adaptation assessments: An ongoing process

Author(s):  
Robert J. Nicholls ◽  
Susan E. Hanson ◽  
Jason A. Lowe ◽  
Aimée B. A. Slangen ◽  
Thomas Wahl ◽  
...  
2018 ◽  
Vol 6 (4) ◽  
pp. 141
Author(s):  
Roshanka Ranasinghe ◽  
Ruben Jongejan

Projected climate change driven variations in mean sea level (i. [...]


2021 ◽  
Author(s):  
Luis Germano Biolchi ◽  
Silvia Unguendoli ◽  
Lidia Bressan ◽  
Beatrice Maria Sole Giambastiani ◽  
Andrea Valentini

<p>The low lying and sandy coastal areas of the Emilia-Romagna region are heavily threatened by sea storms, often leading to flooding and coastal erosion events with severe impacts on citizens’ quality of life, damages to the cultural heritage and effects on economic activities (e.g. aquaculture, fisheries, tourism, beach facilities). Climate change projections reinforce the need of strategies and tools to prevent damages and promptly react to extreme events. In this context and in the framework of non-structural mitigation measures, the Hydro-Meteo-Climate Service of Arpae Emilia-Romagna (Arpae-SIMC) developed and operationally manages a Coastal Early Warning System (EWS) for the Emilia-Romagna Region (Northeast Italy).</p><p>The EWS was developed during the EU Project FP7-MICORE and it is a state-of-the-art coastal forecasting system that follows a chain of operational numerical models: the meteorological model COSMO, the wave model SWAN-MEDITARE, the ocean model AdriaROMS, and the morphodynamic model XBeach. The latter is currently implemented on a series of cross-shore beach profiles covering eight locations distributed along the Emilia-Romagna shore. Deterministic daily forecasts (72-hours) are generated and Storm Impact Indicators (SIIs) used to assess sea-storm induced coastal risk along the region’s littoral (geo.regione.emilia-romagna.it/schede/ews). </p><p>It is widely known that among the limitations of deterministic approaches, the lack of uncertainty estimation is often problematic as decision-makers might be misled if the only forecast available underestimates (or overestimates) incoming conditions. Hence, following the success of probabilistic forecasting in meteorological applications, storm surge EWSs following ensemble frameworks have been recently developed, allowing for more information available to sustain the decision-making process. Towards the new paradigm change, one of the foreseen outputs of the European Interreg Italy-Croatia CBC Programme project Strategic development of flood management (STREAM) involves the development of a “probabilistic EWS for coastal risk implemented and tested on at least one location along the Emilia-Romagna Coast”. </p><p>The initial implementation of the (semi-)probabilistic framework benefits from the EU ADRION I-STORMS (Integrated Sea Storm Management Strategies) project outcomes, in which wave and sea level multi-model ensembles were developed for the Adriatic Sea giving origin to the Transnational Multi-Model Ensemble (TMES). The TMES was made available as one of the six Integrated Web System (IWS) components, combining five wave and six sea level forecasting systems as means to provide 48-hour forecasts in terms of sea level and wave characteristics (Hs, Tm and Dm). Ensemble mean and standard deviation (SD) are calculated based on different forecasting systems’ results. In the initial approach, four TMES combinations have been tested as XBeach forcing: the TMES mean; the mean minus one SD; the mean plus one SD; the mean plus two SDs. Two months were analyzed together with the already implemented deterministic system for two profiles along the region’s coast.</p><p>The methodology followed for the test period will be shown as well as the results. Furthermore, the methodology under development will be also shown as means to enhance the discussion involving storm surge ensemble applications.</p>


2015 ◽  
Vol 5 (3) ◽  
pp. 188-190 ◽  
Author(s):  
Jochen Hinkel ◽  
Carlo Jaeger ◽  
Robert J. Nicholls ◽  
Jason Lowe ◽  
Ortwin Renn ◽  
...  

2017 ◽  
Vol 88 (1) ◽  
pp. 389-414 ◽  
Author(s):  
Annette Grilli ◽  
Malcolm L. Spaulding ◽  
Bryan A. Oakley ◽  
Chris Damon

2016 ◽  
Vol 3 ◽  
Author(s):  
Begoña Pérez-Gómez ◽  
Fernando Manzano ◽  
Enrique Alvarez-Fanjul ◽  
Carlos González ◽  
Juan V. Cantavella ◽  
...  

2018 ◽  
Vol 8 (1) ◽  
pp. 121-129
Author(s):  
H. Bâki Iz

Abstract Predicting sea level rise is essential for current climate discussions. Empirical models put in use to monitor and analyze sea level variations observed at globally distributed tide gauge stations during the last decade can provide reliable predictions with high resolution. Meanwhile, prediction intervals, an alternative to confidence intervals, are to be recognized and deployed in sea level studies. Predictions together with their prediction intervals, as demonstrated in this study, can quantify the uncertainty of a single future observation from a population, instead of the uncertainty of a conceivable average sea level namely a confidence interval, and it is thereby, better suited for coastal risk assessment to guide policy development for mitigation and adaptation responses.


2015 ◽  
Vol 104 ◽  
pp. 22-35 ◽  
Author(s):  
Guido Benassai ◽  
Gianluigi Di Paola ◽  
Pietro Patrizio Ciro Aucelli

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1220 ◽  
Author(s):  
Luis Maria Abadie ◽  
Elisa Sainz de Murieta ◽  
Ibon Galarraga

Iberian coastal cities are subject to significant risks in the next decades due to climate change-induced sea-level rise. These risks are quite uncertain depending on several factors. In this article, we estimate potential economic damage in 62 Iberian coastal cities from 2020 to 2100 using regional relative sea-level rise data under three representative concentration pathways (RCP 8.5, RCP 4.5 and RCP 2.6). We analyze the expected accumulated damage costs if no adaptation actions take place and compare this scenario to the investment cost of some adaptation strategies being implemented. The results show that some adaptation strategies are less costly than the potential damage under inaction. In other words, it is economically rational to invest in adaptation even in a context of high uncertainty. These calculations are very relevant to inform climate change adaptation decisions and to better manage the risk posed by sea-level rise. Moreover, our findings show the importance of a good understanding of the shape of the sea-level rise and damage cost distributions to calculate the expected damage. We show that using the 50th percentile for these calculations is not adequate as it leads to a serious underestimation of expected damage and coastal risk.


Author(s):  
N. B. Avsar ◽  
S. Jin ◽  
S. H. Kutoglu

<p><strong>Abstract.</strong> Sea level rise causes devastating effects on coastal habitats. For example, coastal erosion and saltwater intrusion are major threats for the Black Sea coasts. So, determining sea level changes in the Black Sea is important in terms of coastal risk assessment and coastal planning. In this study, present-day sea level change in the Black Sea is estimated from satellite altimetry and gravity measurements. Altimetry data demonstrate that the Black Sea level has risen at an average rate of 2.5&amp;thinsp;&amp;plusmn;&amp;thinsp;0.5&amp;thinsp;mm/year from January 1993 to May 2017. During this period, inter-annual variability of the non-seasonal sea level change is quite strong. Furthermore, mass contribution to this change for the period 2002–2017 has been detected as 2.3&amp;thinsp;&amp;plusmn;&amp;thinsp;1.0&amp;thinsp;mm/year from the Gravity Recovery And Climate Experiment (GRACE) mascon solutions.</p>


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