Research ArticleGEOLOGY

Tsunamis in the geological record: Making waves with a cautionary tale from the Mediterranean

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Science Advances  11 Oct 2017:
Vol. 3, no. 10, e1700485
DOI: 10.1126/sciadv.1700485
  • Fig. 1 Costs and deaths associated with storms (left) and tsunamis (right) between 1900 and 2015, based on the EM-DAT disaster database.

    The data demonstrate that tsunamis are rare and unpredictable natural hazards but that, cumulatively, storms are deadlier and more costly. The threat of storms and tsunami hazards has been aggravated by global change and sea-level rise, particularly in densely populated coastal areas, which presently account for ~40% of the world’s population (8). In particular, low-lying coastal areas are experiencing rapid and disproportionate demographic growth in comparison to the global average, driven notably by the importance of their natural resources and ocean-related recreation.

  • Fig. 2 Occurrence of storm events and related mortality for the period 1900–2015.

    The data were analyzed using a Loess smoothing (with bootstrap and smoothing of 0.05) and a sinusoidal regression model (phase Free) to detect the periodicity associated with the extreme events. The algorithm used in the model is a “LOWESS” (locally weighted scatterplot smoothing), with a bootstrap that estimates a 95% confidence band (based on 999 random replicates). The sinusoidal regression was used to model periodicities in the time series generated by the Loess smoothing. The “total deaths per year” signal was further investigated using a wavelet transform with Morlet as the basis function. The scalograms are shown as periods on a linear age scale.

  • Fig. 3 Location of sites and references used in this study.
  • Fig. 4 Temporal distribution of high-energy events interpreted as tsunamis, grouped geographically from the Eastern to Western Mediterranean.

    The lower histogram plots tsunami frequency at regular 25-year intervals. The blue line denotes the 1500-year sinusoidal filter fitted to these data (phase = Free; r = 0.839). The list of references and their locations is provided in Materials and Methods. Mediterranean (21) and NW European (49) storm periods are also indicated.

  • Fig. 5 Histogram of detrended tsunami events at 100-year intervals.

    Cluster analysis delineates six periods of high and low tsunami frequency (algorithm, paired group; similarity measure, Euclidean; correlation, 0.72). The hierarchical clustering analysis (descending type, clusters joined on the basis of the average distance) was used to calculate the lengths of tree branches using branches as distances between groups of data. The data were also fitted with a sinusoidal filter, which underscores the strength of the 1500-year periodicity and supports the cluster analysis.

  • Fig. 6 Histogram of tsunami events at 25-year intervals, where overlapping events from the same record were attributed a score of “1” (presence) or “0” (absence).

    The data have been fitted using a 1500-year sinusoidal filter (in dark blue; phase = Free; r = 0.798). The more minor peaks linked to Mediterranean storm phases [in light blue; (21)] are more clearly defined.

  • Fig. 7 Long-term trends in tsunami events, North Atlantic storminess, eastern Mediterranean speleothem data, and NW Mediterranean storminess.

    Sinusoidal regressions (fitted to a 1500-year filter) underscore the periodicity defining the long-term trends in tsunami frequency compared to proxies for North Atlantic and Mediterranean cooling and storm conditions in the NW Mediterranean. The filtered signals were correlated using cross-correlations (P < 0.05). The cross-correlations assess the time alignment of two time series by means of the correlation coefficient. The series have been cross-correlated to ascertain the best temporal match and the potential lag between two selected variables. The correlation coefficient was then plotted as a function of the alignment position. Positive and negative correlation coefficients are considered, focusing on the lag0 value (with +0.50 and −0.50 as significant thresholds).

  • Fig. 8 Tsunami frequency during the last 2000 years compared with evidence for storminess and climate deterioration in the North Atlantic and the Mediterranean.

    All data sets were normalized to regular 25-year intervals using a linear interpolation model. The paleoclimate and storminess records were smoothed using a five-point moving average. The correlations between these paleoclimate series and the tsunami data are indicated by green circles.

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/3/10/e1700485/DC1

    fig. S1. REDFIT spectral analysis and wavelet analyses of the tsunami data set.

    fig. S2. Catalog of Mediterranean tsunami events based on historical records from Maramai et al. (35).

    fig. S3. Spectral analysis, REDFIT analysis, and wavelet analysis of the documentary database of Mediterranean tsunamis.

    table S1. Database of sites and stratigraphic tsunami events used in this study.

    table S2. Matrix of stratigraphic tsunami events by year and site.

    table S3. Annual frequency of tsunami events in the Mediterranean’s geological record based on this study.

    table S4. Data used to produce Fig. 1.

    table S5. Frequency of tsunami events in the geological record at 25-year intervals.

    table S6. Data used to produce Fig. 5.

    table S7. Data used to produce Fig. 6.

    table S8. Data used to produce Fig. 7.

    table S9. Data used to produce Fig. 8.

    table S10. Catalog of Mediterranean tsunamis in historical documents and number of events by year.

  • Supplementary Materials

    This PDF file includes:

    • fig. S1. REDFIT spectral analysis and wavelet analyses of the tsunami data set.
    • fig. S2. Catalog of Mediterranean tsunami events based on historical records from Maramai et al. (35).
    • fig. S3. Spectral analysis, REDFIT analysis, and wavelet analysis of the documentary database of Mediterranean tsunamis.

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    Other Supplementary Material for this manuscript includes the following:

    • table S1 (Microsoft Excel format). Database of sites and stratigraphic tsunami events used in this study.
    • table S2 (Microsoft Excel format). Matrix of stratigraphic tsunami events by year and site.
    • table S3 (Microsoft Excel format). Annual frequency of tsunami events in the Mediterranean’s geological record based on this study.
    • table S4 (Microsoft Excel format). Data used to produce Fig. 1.
    • table S5. Frequency of tsunami events in the geological record at 25-year intervals.
    • table S6 (Microsoft Excel format). Data used to produce Fig. 5.
    • table S7 (Microsoft Excel format). Data used to produce Fig. 6.
    • table S8 (Microsoft Excel format). Data used to produce Fig. 7.
    • table S9 (Microsoft Excel format). Data used to produce Fig. 8.
    • table S10 (Microsoft Excel format). Catalog of Mediterranean tsunamis in historical documents and number of events by year.

    Download Tables S1 to S10

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