Role of wave forcing, storms and NAO in outer bar dynamics on a high-energy, macro-tidal beach

Abstract

Outer sand bar dynamics on a high-energy macro-tidal beach were investigated using long-term (multi-year) field datasets of intertidal morphology and offshore bathymetry. Utilising a 15-year time-series of Argus video images, five distinct outer bar types were identified: Mega Rip, Longshore, Crescentic, Crescentic Attached and Welded. The most common classification was Crescentic Attached, with the outer bar oscillations being out of phase with the inner bar oscillations, as would be expected for the shore-normal wave approach at this site. The outer bar had a typical amplitude of 0.5-1 m and a longshore wavelength of 600 m. Changes in outer bar morphology were related to measured and modelled nearshore wave data. However, the outer bar morphology changed over a much longer time scale (monthly-to-annual) than the daily-to-weekly variations in wave height and period. An extended duration of energetic wave action was required to bring about an upstate bar transition to the Longshore or Mega Rip state, where the bar then remained arrested for a significant amount of time, requiring several months of low wave conditions to induce a down state transition through Crescentic to Welded. This slow morphological response is explained by extended relaxation times attributed to the large tidal range at the study site where the outer bar morphology is only active for part of the tidal cycle (several hours around low tide). The configuration and position of the outer bar were related: the more upstate (downstate) bar types being associated with a more offshore (onshore) bar position. The detrended outer bar position was significantly related to a forcing term based on wave power and disequilibrium of the dimensionless fall velocity with offshore (onshore) bar migration occurring when wave conditions were more (less) energetic that the antecedent conditions. The upstate end member (Longshore or Mega Rip) was attained sometime during the winter months for 14 out of the 16 years of monitoring; the outer bar remained attached to the low tide shoreline over the winter 2005/2006 and 2010/2011. These two winters with incomplete upstate cycles were characterised by the lowest winter wave conditions and negative winter North Atlantic Oscillation (NAO) indices, suggesting that the winter NAO is correlated with both beach state and nearshore bar configuration. KEYWORDS

Contribution of storms to shoreline changes in mesotidal dissipative beaches: case study in the Gulf of Cádiz (SW Spain)

“…wave heights over 2.5 m and a minimum duration of 12 h; storm groups with calm periods of less than 24 h between them were considered a single storm-group event. The threshold above for significant wave height coincides with the 0.95 quantile defined by Masselink et al (2014) and with the minimum wave height threshold proposed by Ribera et al (2011).…”

Observations and Predictions of Wave Runup, Extreme Water Levels, and Medium-Term Dune Erosion during Storm Conditions

“…Consistent with this assumption, many studies have suggested that the North Atlantic Oscillation (NAO) may control the occurrence of storm events in the Atlantic, and thus potentially influence coastal morphological changes. The role of the NAO in coastal morphological dynamics has been suggested by Masselink et al [48] to explain medium-term outer sand bar dynamics in the southwest of England (Perranporth). It was also suggested by Thomas et al, after analyzing beach rotation at South Sands Tenby in West Wales [49,50] and O'Connor et al [51] concerning long-term shoreline and ebb channel evolution in northwest Ireland.…”

Spatial and Temporal Clustering Analysis of Extreme Wave Events around the UK Coastline

“…First, temporal trends of events were analysed by looking at both monthly and inter-annual changes. We compared the inter-annual changes of events with different atmospheric oscillations (NAO, EA, SCAND and WEPA), as done in previous wave climate studies on the west coast of Europe, e.g., [27,[32][33][34]. Second, the temporal clustering was evaluated by comparing the time between consecutive events.…”