Coastal vulnerability across the Pacific dominated by El Niño/Southern Oscillation

Journal name:
Nature Geoscience
Volume:
8,
Pages:
801–807
Year published:
DOI:
doi:10.1038/ngeo2539
Received
Accepted
Published online

Abstract

To predict future coastal hazards, it is important to quantify any links between climate drivers and spatial patterns of coastal change. However, most studies of future coastal vulnerability do not account for the dynamic components of coastal water levels during storms, notably wave-driven processes, storm surges and seasonal water level anomalies, although these components can add metres to water levels during extreme events. Here we synthesize multi-decadal, co-located data assimilated between 1979 and 2012 that describe wave climate, local water levels and coastal change for 48 beaches throughout the Pacific Ocean basin. We find that observed coastal erosion across the Pacific varies most closely with El Niño/Southern Oscillation, with a smaller influence from the Southern Annular Mode and the Pacific North American pattern. In the northern and southern Pacific Ocean, regional wave and water level anomalies are significantly correlated to a suite of climate indices, particularly during boreal winter; conditions in the northeast Pacific Ocean are often opposite to those in the western and southern Pacific. We conclude that, if projections for an increasing frequency of extreme El Niño and La Niña events over the twenty-first century are confirmed, then populated regions on opposite sides of the Pacific Ocean basin could be alternately exposed to extreme coastal erosion and flooding, independent of sea-level rise.

At a glance

Figures

  1. Study site locations.
    Figure 1: Study site locations.

    Locations of the 16 study sites (grouped into six regions) within the Pacific Ocean basin where co-located wave, water level and shoreline change data were analysed. Mean significant wave heights from 1996 to 2005 are shown39.

  2. Shoreline erosion anomalies.
    Figure 2: Shoreline erosion anomalies.

    Annual shoreline erosion for the top five climate index events, relative to the mean, during winter (DJF) from 1979 to 2012 (see Supplementary Fig. 3 for annual/DJF time periods for all 12 indices).

  3. Wave energy flux and direction anomalies.
    Figure 3: Wave energy flux and direction anomalies.

    Divergence from the mean for the top five climate index events during winter (DJF) from 1979 to 2012. a, Wave energy flux. b, Wave direction. (See Supplementary Figs 4 and 5 for annual/DJF time periods and mean/upper 5% values for all 12 indices.)

  4. Water level anomalies.
    Figure 4: Water level anomalies.

    Average water level anomalies for the top five climate index events during winter (DJF) from 1979 to 2012. (See Supplementary Fig. 6 for annual/DJF time periods for all 12 indices.)

  5. Wave metrics and MEI correlations.
    Figure 5: Wave metrics and MEI correlations.

    Correlation (R) between MEI and wave energy flux, upper 5% energy flux, and direction from sites across the Pacific Ocean basin for boreal winter (DJF), spring (MAM), summer (JJA) and fall (SON). Black outlines indicate significant correlations above the 95% confidence interval. (see Supplementary Fig. 7 for plots of all 12 indices).

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Author information

Affiliations

  1. United States Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, California 95060, USA

    • Patrick L. Barnard,
    • Sean Vitousek &
    • Evan Randall-Goodwin
  2. University of Sydney School of Geosciences, Sydney, New South Wales 2006, Australia

    • Andrew D. Short
  3. University of Ferrara, Department of Physics and Earth Sciences, Via Saragat 1, 44122 Ferrara, Italy

    • Mitchell D. Harley
  4. UNSW Australia, Water Research Laboratory, School of Civil and Environmental Engineering, Sydney, New South Wales 2093, Australia

    • Mitchell D. Harley,
    • Kristen D. Splinter &
    • Ian L. Turner
  5. Oregon Department of Geology and Mineral Industries, Coastal Field Office, Newport, Oregon 97365, USA

    • Jonathan Allan
  6. Port and Airport Research Institute, Nagase 3-1-1, Yokosuka, Kanagawa 239-0826, Japan

    • Masayuki Banno &
    • Yoshiaki Kuriyama
  7. University of Waikato, Private Bag 3105, Hamilton 3240, New Zealand

    • Karin R. Bryan
  8. Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California 92093, USA

    • André Doria
  9. University of Western Australia, School of Earth and Environment, 35 Stirling Highway Crawley, Western Australia 6009, Australia

    • Jeff E. Hansen
  10. Toyohashi University of Technology, Aichi 441-8580, Japan

    • Shigeru Kato
  11. University of California, Santa Cruz, Department of Ocean Sciences, Santa Cruz, California 95060, USA

    • Evan Randall-Goodwin
  12. Oregon State University, College of Earth, Ocean, and Atmospheric Sciences, Corvallis, Oregon 97331, USA

    • Peter Ruggiero
  13. University of Victoria, Coastal Erosion and Dune Dynamics (CEDD) Laboratory, Department of Geography, Victoria, British Columbia V8P 5C2, Canada

    • Ian J. Walker &
    • Derek K. Heathfield

Contributions

P.L.B. and A.D.S. developed the original concept for this study. P.L.B. directed the analysis and wrote the original version of this paper. M.D.H., S.V. and E.R.-G., analysed the data. All authors contributed to interpreting results and improvement of this paper.

Competing financial interests

The authors declare no competing financial interests.

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