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A discussion of statistical methods used to estimate extreme wind speeds
SMHI, Research Department.
2006 (English)In: Journal of Theoretical and Applied Climatology, ISSN 0177-798X, E-ISSN 1434-4483, Vol. 85, no 3-4, p. 203-215Article in journal (Refereed) Published
Abstract [en]

Wind speeds in extra-tropical latitudes are known to be approximately Weibull distributed. Hence a Weibull distribution fitted to all available data is often used to predict extreme winds. The most extreme values then, however, have little influence on the estimated parent Weibull distribution, and the accuracy of the extreme value predictions obtained in this manner may be questioned. In the present paper such a "Weibull method" is compared to a method based on statistical extreme value theory, "the annual maxima method". The comparison is based on 30 years of 10 minute wind speed averages measured hourly at 12 meteorological stations located at airports in Sweden. Results show that the Weibull method generates incorrect estimates of the tails of the distributions of wind speeds and of the distribution of yearly maximum wind speed, and that serial dependence of individual measurements has to be taken into account. In addition, it is inherent in the Weibull method that it does not provide any confidence bounds for the estimates. The annual maxima method avoids these problems. The measurements were rounded, first to entire knots, and then to m/s. A further, "technical", result is that if this rounding were disregarded in the estimation procedure, then the computed standard errors of the parameter estimates would be erroneously low. Hence, if rounding is done, it should be taken into account in the estimation procedure. We also believe this to be a clear indication that rounding of the data decreases estimation accuracy.

Place, publisher, year, edition, pages
2006. Vol. 85, no 3-4, p. 203-215
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
URN: urn:nbn:se:smhi:diva-797DOI: 10.1007/s00704-005-0187-3ISI: 000239002200006OAI: oai:DiVA.org:smhi-797DiVA, id: diva2:807031
Available from: 2015-04-22 Created: 2015-04-22 Last updated: 2017-12-04Bibliographically approved

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