Articles | Volume 17, issue 3
https://doi.org/10.5194/nhess-17-357-2017
https://doi.org/10.5194/nhess-17-357-2017
Research article
 | 
08 Mar 2017
Research article |  | 08 Mar 2017

Efficient bootstrap estimates for tail statistics

Øyvind Breivik and Ole Johan Aarnes

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Manuscript not accepted for further review
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Cited articles

Aarnes, O. J., Breivik, Ø., and Reistad, M.: Wave Extremes in the Northeast Atlantic, J. Climate, 25, 1529–1543, https://doi.org/10.1175/JCLI-D-11-00132.1, 2012.
Beirlant, J., Goegebeur, Y., Segers, J., and Teugels, J.: Statistics of extremes: theory and applications, John Wiley & Sons, 99–123, 2006.
Breivik, Ø., Gusdal, Y., Furevik, B. R., Aarnes, O. J., and Reistad, M.: Nearshore wave forecasting and hindcasting by dynamical and statistical downscaling, J. Marine Syst., 78, S235–S243, 2009.
Breivik, Ø., Aarnes, O. J., Bidlot, J.-R., Carrasco, A., and Saetra, Ø.: Wave Extremes in the Northeast Atlantic from Ensemble Forecasts, J. Climate, 26, 7525–7540, 2013.
Breivik, Ø., Aarnes, O., Abadalla, S., Bidlot, J.-R., and Janssen, P.: Wind and Wave Extremes over the World Oceans From Very Large Ensembles, Geophys. Res. Lett., 41, 5122–5131, https://doi.org/10.1002/2014GL060997, 2014.
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Return values can be estimated from large data sets stemming from numerical models. The question explored here is how much of the original data must be kept in order to compute unbiased return estimates. We find that retaining only a small fraction is usually enough. This offers huge storage and computational savings. We provide a set of examples to demonstrate how this can be done.
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