Wave climate variability in the North-East Atlantic Ocean over the last six decades

Dodet, Guillaume; Bertin, Xavier; Taborda, Rui

doi:10.1016/j.ocemod.2009.10.010

Cited by 291 publications

(235 citation statements)

References 28 publications

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“…The most (least) energetic winters are associated with positive (negative) NAO indices, and the winter NAO itself shows a weak 5-year cyclicity. Such linkage between winter wave conditions and winter NAO has previously been demonstrated by Dodet et al (2010) and Woolf et al (2002).…”

Section: Discussionsupporting

confidence: 71%

“…The winter period between December and March exhibits the strongest inter-decadal variability and is strongly related to storm track (Osborne, 2006). Positive NAO index values are typically associated with stronger westerly dominated winds across the northeast Atlantic (Dodet et al, 2010). It can be suggested that, through its control on the wind and wave conditions, NAO may affect inter-annual beach behaviour; however, evidence to date has been unconvincing (e.g., Thomas et al, 2012).…”

Section: Link Between Winter Nao and Wave Climatementioning

confidence: 99%

“…This NAO index follows Jones et al (1997) and is the difference between the normalised pressures at Gibraltar and Reykjavik (southwest Iceland), and a positive NAO index means that the pressure differential is larger than normal (e.g., deep low pressure cells around Iceland). The associated wave forcing over this period was obtained from a 57-year hindcast ) of the North East Atlantic wave climate with version 3.14 of the third-generation spectral wave model WAVEWATCH III (WWIII; Tolman, 2009), forced with re-analysed wind fields (Dodet et al, 2010). Figure 7 shows the 4-month winter-averaged (December-March) time series of hindcast wave heights for offshore location 50.10˚N 60.10˚W, 70 km to the southwest of Perranporth (water depth > 50 m).…”

Section: Link Between Winter Nao and Wave Climatementioning

confidence: 99%

“…Significant correlations (r = 0.64 and 0.51) between winter NAO regional atmospheric forcing and winter-averaged H s and Ω were identified (Figure 7). These relationships are examined further by Dodet et al, (2010) Autocorrelation analysis of both wave H s (winter) and winter NAO identified weak, but significant correlations (r = 0.2) at lags of 4-5 years (Figure 7 -upper-right panel) and this multi-annual cyclical behaviour is also evident in the 5-year low-pass filtered time series of winter NAO (Figure 7 -upper-left panel). It is clearly important to consider these identified longer-term inter-annual cycles in key forcing variables linked to beach change when interpreting the representativeness of short-term datasets of beach change.…”

Section: Link Between Winter Nao and Wave Climatementioning

confidence: 99%

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

et al. 2014

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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

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Section: Discussionsupporting

confidence: 71%

Section: Link Between Winter Nao and Wave Climatementioning

confidence: 99%

Section: Link Between Winter Nao and Wave Climatementioning

confidence: 99%

Section: Link Between Winter Nao and Wave Climatementioning

confidence: 99%

See 2 more Smart Citations

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

et al. 2014

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“…The climate cycle has a broad range of frequencies that overshadows other tested indices in the Atlantic. The results show decreasing strength of the AO from north to south as reported by Bauer [2001], Woolf et al [2002], and Dodet et al [2010]. Previous studies have focused on the inter-annual variability of the oscillation, but these time scales are only slightly larger than those of a white noise process making the results sensitive to the time period analyzed [Stephenson et al, 2000].…”

Section: Teleconnections Across Basinssupporting

confidence: 51%

Periodicity and patterns of ocean wind and wave climate

Stopa

Cheung

2014

JGR Oceans

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The Climate Forecast System Reanalysis (CFSR) provides a wealth of information spanning 1979-2009 for investigation of ocean wind and wave climate. Preprocessing of the data is necessary to remove the dominant seasonal signals and to create time series of semimonthly averaged wind speed and significant wave height over a 0.5 global grid. We perform an empirical orthogonal function (EOF) analysis to extract the dominant space-time patterns. The results for the three major ocean basins show strong zonal structures in the winds and saturation of the swells corroborating prior works with various data sets. We reexamine the CFSR data in the frequency domain to identify periodic signals associated with published climate indices. The Fourier transform of the preprocessed time series generates spectra ranging from 1 month to 15 years period for an EOF analysis. The results demonstrate the spatial structures and periods of climate phenomena. The Arctic Oscillation dominates the Atlantic basin with a broad range of intra-annual signals off the European coasts. The Indian and Pacific Oceans are strongly influenced by inter-annual cycles of the El Niño Southern Oscillation (ENSO) and the Antarctica Oscillation. The Indian Ocean also has strong intra-annual components ranging from 50 to 80 days period. The ENSO proves to be a ubiquitous signal around the globe, and in particular, saturates the Pacific with strong influences in the equatorial region and the Southern Hemisphere Westerlies. A commonality of all basins is that the magnitude and the spatial structure of the intra-annual and inter-annual signals are similar suggesting a wide range of periods in each of the climate cycles examined.

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Historical wave height trends in the South and East China Seas, 1911–2010

Feng

2014

JGR Oceans

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This study reconstructs 6 hourly significant wave heights (H s ) in the South and East China Seas for the period 1871-2010, using the Twentieth Century Reanalysis ensemble of mean sea level pressure (SLP) fields and a multivariate regression model to represent the H s -SLP relationship in each study area. The regression model was calibrated and validated using the ERA-Interim reanalysis of H s and SLP for the period 1981-2010. These reconstructions were found to reproduce reasonably well the seasonal mean and maximum H s climates as represented by the ERA40 and ERA-Interim wave reanalyses. For each study area, an ensemble of 56 members of 6 hourly H s was reconstructed for each grid point. The regional mean series of the ensemble mean of the reconstructed consecutive monthly mean H s was tested for temporal homogeneity, which identified a few discontinuities in the pre-1946 period and led to the exclusion of the reconstructed H s for 1871-1910 from trend analysis (due to data uncertainty and inhomogeneity). Each 6 hourly H s time series for the period 1911-2010 was homogenized for the identified discontinuities, before being used to derive annual and seasonal mean and maximum H s for trend analysis. The trend analysis results show that, in both study areas, the 1911-2010 wave height trends are dominantly negative, with the exception that the seasonal maximum significant wave heights seem to have increased in summer and spring in the central South China Sea and in summer in the East China Sea.

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Wave climate variability in the North-East Atlantic Ocean over the last six decades

Cited by 291 publications

References 28 publications

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

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

Periodicity and patterns of ocean wind and wave climate

Historical wave height trends in the South and East China Seas, 1911–2010

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