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Provedor de dados:  ArchiMer
País:  France
Título:  Collaborative Science to Enhance Coastal Resilience and Adaptation
Autores:  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
Data:  2019-07
Ano:  2019
Palavras-chave:  Coastal observations
Numerical models
Coastal flooding
Big data
Community vulnerability
Climate change
Urban coasts
Resumo:  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.
Tipo:  Text
Idioma:  Inglês

Editor:  Frontiers Media Sa
Formato:  application/pdf
Fonte:  Frontiers In Marine Science (Frontiers Media Sa), 2019-07 , Vol. 6 , N. 404 , P. 16p.
Direitos:  info:eu-repo/semantics/openAccess

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