|Author(s)||Nichols C. Reid1, Wright Lynn D.2, Bainbridge Scott J.3, Cosby Arthur4, Henaff Alain5, Loftis Jon D.6, Cocquempot Lucie5, Katragadda Sridhar6, Mendez Gina R.4, Letortu Pauline5, Le Dantec Nicolas7, 8, Resio Donald9, Zarillo Gary10|
|Affiliation(s)||1 : Marine Informat Resources Corp, Ellicott City, MD USA.
2 : Southeastem Univ Res Assoc, Washington, DC 20005 USA.
3 : Australian Inst Marine Sci, Townsville, Qld, Australia.
4 : Mississippi State Univ, Social Sci Res Ctr, Starkville, MS USA.
5 : Univ Bretagne Occidentale, LGO UMR CNRS UBO 6538, Plouzane, France.
6 : Virginia Inst Marine Sci, Gloucester Point, VA 23062 USA.
7 : Univ Bretagne Occidentale, LETG UMR CNRS UBO 6554, Plouzane, France.
8 : Cerema Eau Mer & Fleuves, Margny Les Compiegne, France.
9 : Univ North Florida, Taylor Engn Res Inst, Jacksonville, FL USA.
10 : Florida Inst Technol, Melbourne, FL 32901 USA.
|Source||Frontiers In Marine Science (Frontiers Media Sa), 2019-07 , Vol. 6 , N. 404 , P. 16p.|
|WOS© Times Cited||14|
|Keyword(s)||coastal observations, numerical models, coastal flooding, big data, collaboration, community vulnerability, climate change, urban coasts|
Impacts from natural and anthropogenic coastal hazards are substantial and increasing significantly with climate change. Coasts and coastal communities are increasingly at risk. In addition to short-term events, long-term changes, including rising sea levels, increasing storm intensity, and consequent severe compound flooding events are degrading coastal ecosystems and threatening coastal dwellers. Consequently, people living near the coast require environmental intelligence in the form of reliable short-term and long-term predictions in order to anticipate, prepare for, adapt to, resist, and recover from hazards. Risk-informed decision making is crucial, but for the resulting information to be actionable, it must be effectively and promptly communicated to planners, decision makers and emergency managers in readily understood terms and formats. The information, critical to forecasts of extreme weather and flooding, as well as long-term projections of future risks, must involve synergistic interplay between observations and models. In addition to serving data for assimilation into models, the observations are also essential for objective validation of models via hind casts. Linked observing and modeling programs that involve stakeholder input and integrate engineering, environmental, and community vulnerability are needed to evaluate conditions prior to and following severe storm events, to update baselines, and to plan for future changes over the long term. In contrast to most deep-sea phenomena, coastal vulnerabilities are locally and regionally specific and prioritization of the most important observational data and model predictions must rely heavily on input from local and regional communities and decision makers. Innovative technologies and nature-based solutions are already helping to reduce vulnerability from coastal hazards in some localities but more focus on local circumstances, as opposed to global solutions, is needed. Agile and spatially distributed response capabilities will assist operational organizations in predicting, preparing for and mitigating potential community-wide disasters. This white paper outlines the rationale, synthesizes recent literature and summarizes some data-driven approaches to coastal resilience.
Nichols C. Reid, Wright Lynn D., Bainbridge Scott J., Cosby Arthur, Henaff Alain, Loftis Jon D., Cocquempot Lucie, Katragadda Sridhar, Mendez Gina R., Letortu Pauline, Le Dantec Nicolas, Resio Donald, Zarillo Gary (2019). Collaborative Science to Enhance Coastal Resilience and Adaptation. Frontiers In Marine Science, 6(404), 16p. Publisher's official version : https://doi.org/10.3389/fmars.2019.00404 , Open Access version : https://archimer.ifremer.fr/doc/00637/74921/