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More tornadoes in the most extreme U.S. tornado outbreaks

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Science  16 Dec 2016:
Vol. 354, Issue 6318, pp. 1419-1423
DOI: 10.1126/science.aah7393
  • Fig. 1 Numbers of tornadoes per outbreak.

    (A) Annual 20th, 40th, 60th, and 80th percentiles of the number of E/F1+ tornadoes per outbreak (6 or more E/F1+ tornadoes), 1954 to 2015 (solid lines), and quantile regression fits to 1965 to 2015, assuming linear growth in time (dashed lines). (B) Linear growth rates as a function of percentile probability. Error bars are 95% bootstrap confidence intervals and indicate linear trends that are statistically significantly different from zero.

  • Fig. 2 Extreme outbreaks.

    (A) Annual number of extreme outbreaks (12 or more E/F1+ tornadoes). (B) Annual 20th, 40th, 60th, and 80th percentiles of the number of E/F1+ tornadoes per extreme outbreak, 1965 to 2015 (jagged solid lines), along with quantile regression lines (dashed lines) and percentiles of the GP distribution with a linear trend in the scale parameter (solid lines). (C) Quantile regression linear growth rates (slopes), along with 95% confidence intervals (blue) and corresponding growth rates of a GP distribution with linear trend in the scale parameter as functions of percentile probability (solid red line). (D) Annual maxima (black line), along with GP return levels as functions of year for return periods of 2, 5, and 25 years (solid colored lines), and 90% bootstrap confidence intervals (dashed lines).

  • Fig. 3 Extreme environments.

    Percentiles of (A) CAPE and (B) SRH conditional on the proxy for the number of E/F1+ tornadoes per outbreak (see methods for definition) exceeding 12. (C) Percentiles of the proxy for the number of tornadoes per extreme outbreak. (D) Linear growth rate (ordinary least-squares estimates of slope and 95% confidence intervals) of the extreme outbreak proxy percentiles as a function of percentile.

  • Table 1 Generalized Pareto distribution parameters.

    Distributions are fitted to the number of E/F1+ tornadoes per outbreak for outbreaks with 12 or more E/F1+ tornadoes. The negative log likelihood (NLL), maximum likelihood estimates, and their standard errors are indicated for each model. The likelihood ratio (LR) test P value compares nonstationary models with the stationary distribution.

    Embedded ImageEmbedded ImageEmbedded ImageEmbedded Image
    Stationary (NLL = 1449)
    Maximum likelihood estimates7.60.3
    Standard error estimates0.6210.067
    Embedded Image (NLL = 1440)
    LR P value = 2 × 10−5
    Maximum likelihood estimates4.730.120.26
    Standard error estimates0.7360.0290.062
    Embedded Image (NLL = 1447)
    LR P value = 0.04
    Maximum likelihood estimates7.48–0.130.0066
    Standard error estimates0.610.0880.0031
    Embedded Image (NLL = 1442)
    LR P value = 2 × 10−4
    Maximum likelihood estimates8.188.480.28
    Standard error estimates0.65312.20090.0626
    Embedded Image (NLL = 1449)
    LR P value = 0.3
    Maximum likelihood estimates7.71–0.520.29
    Standard error estimates0.630.540.067
    Embedded Image
    (NLL = 1444)
    LR P value = 0.001
    Maximum likelihood estimates8.311.620.28
    Standard error estimates0.700.520.065

Supplementary Materials

  • More tornadoes in the most extreme U.S. tornado outbreaks

    Michael K. Tippett, Chiara Lepore, Joel E. Cohen

    Materials/Methods, Supplementary Text, Tables, Figures, and/or References

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    • Materials and Methods
    • Figs. S1 to S5
    • Tables S1 and S2
    • References

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