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Open coast storm surge water levels consist of a wind shear forcing component generally referred to as a wind setup; a wave setup component caused by wind induced waves transferring momentum to the water column; an atmospheric pressure head component due to the atmospheric pressure deficit over the spatial extent of the storm system; a Coriolis forced component due to the effects of the rotation of the earth acting on the wind driven alongshore current at the coast; and, if astronomical tides are present, an astronomical tide component (although the tide is not really a direct part of the meteorological driven component of storm surge). Typically, the most important component of a storm surge is the wind setup component, especially on the East Coast of the US and in the Gulf of Mexico. The importance of bathymetry to this wind setup storm surge component is considered herein with special reference to the coastline of Florida where eight Florida transects consisting of a cross-section of bathymetric data perpendicular to the shoreline were investigated. Effects of Coriolis, wave setup, atmospheric pressure head, and astronomical tide are not considered herein but will be addressed in future papers. The present study findings show that the wind setup component can vary over an order of magnitude for the same wind speed depending on the bathymetry leading up to the coast.

A simple empirical model is proposed for predicting extreme wave run-up on natural beaches during severe wave events (deep water wave heights H₀ ≳8 m or return periods of about 50 years). The new model departs from traditional approaches that use the slope of the beach face β_f and the Iribarren number ξ₀ as parameters for predicting run-up and instead uses the distance offshore x_h to water depth h to estimate a near-shore profile slope as S = h/x_h, where the depth of closure is the proposed choice for h. Extreme run-up R_x is then expressed in terms of S as R_x/H₀ = CS^2/3. Observations from recent severe storm events in South Africa are used to estimate the dimensionless coefficient C≃7.5. The data are also compared with those of Holman [1986] and the results verify his regression equations and confirm they are valid for significant wave heights extending to 8.5 m for beach-face slopes around 0.1. The run-up predictions of Holman [1986], Nielsen and Hanslow [1991] and Stockdon et al. [2006] are compared to those of the proposed new model. The results suggest that the new model reduces the uncertainties in predicting wave run-up on natural beaches compared with previous models, and thus enables improved estimates of extreme wave run-up and the upper limit of beach change for coastal planning and management.

Bangladesh has been identified as one of the countries most vulnerable to climate change and rising sea-level. This is because it is located at the northern end of the funnel-shaped Bay of Bengal, and as a consequence it has experienced a number of severe storm surges in the last three decades. The inhabitants of the coastal region are very poor, and the surges have pushed them to a "tipping-point"; that is, the point of desperation which is exacerbating the socio-economic threats to their existence. The study reported here aimed to explore the perceptions of coastal communities with regard to vulnerability and adaptation (V & A) strategies in four different areas of Bangladesh in order to reduce their vulnerability to future storm surges. After reviewing the impact assessment guidelines of the Intergovernmental Panel on Climate Change (IPCC), United States Country Studies Program (USCSP) and United Nations Environment Programme (UNEP), the researchers applied the Participatory Rapid Appraisal (PRA) method (a behavioural environmental decision-making tool) to survey 160 participants in four case-study areas, with 20 participants in two sessions in each case. The evaluation of V & A was implemented and prioritised in this study by a measuring scale, called the "weighted matrix index". This study not only considered the integrated assessment of V & A but it also classified the levels of vulnerability and adaptation in different categories. Additionally, it provides a comparative picture of the vulnerabilities for similar risks in different types of communities. These key aspects demonstrate and emphasise that adaptation policy needs to be implemented immediately in Bangladesh in order to reduce and manage future vulnerability in the coastal region under the potential climate change regimes.

During the late summer and early autumn of 2011, the Catskill Mountains in south-central New York State experienced devastating flooding associated with former Hurricane Irene and former Tropical Storm Lee. Even in this particularly flood-prone region, the events of fall 2011 are perceived to be unique in the known history of the region and marked a turning point in the perceptions of residents about climate change. Here, precipitation and stream gage records are analyzed to determine just how unusual this season was. The historical precipitation gage record requires careful analysis due to the changing availability of stations. After a set of stations is developed that is appropriate for this analysis, events of lengths 1 day, 5 days, and 60 days are analyzed to identify regionally significant events (as opposed to events localized to one basin) since the early 20th century and to evaluate Irene and Lee in that historical context. Gage record results corroborate the perceptions of local residents that the period between 1996 and 2011, and in particular the events of fall 2011, were unprecedented in the last 100 years and as inferred from analyses of regional tree rings, probably in the last 500 years.

A methodology to estimate storm-induced morphodynamic risks is presented. The storm-induced coastal response is separately assessed in terms of inundation, beach profile and transport potential. Inundation is calculated by means of the run-up Ru_2% at the peak of the storm. Erosion is characterized by the eroded volume from a beach profile and, overall sediment transport is parameterized in function of the integrated wave power during the storm impact. These three parameters are used to calculate the resulting risk by estimating their probabilities of occurrence using the event and response methods. In the first one, the probability of occurrence is assigned from the extreme wave distribution (events) which is used to calculate the corresponding morphodynamic processes. In the response approach, storm wave data are used to build a data set of storm-induced responses which are later fitted to an extreme distribution. These two methods have been applied to characterize storm wave-induced morphodynamic risks at Costa Brava (NE Spanish Mediterranean coast). Results show that for this case, the use of the event approach significantly under-predicts the morphodynamic response for any probability of occurrence and, in consequence, its use will under-predict storm risks.