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The statistical analysis of extreme high sea levels utilising data from the Solent area

The statistical analysis of extreme high sea levels utilising data from the Solent area
The statistical analysis of extreme high sea levels utilising data from the Solent area

The prediction of the tidal component of sea level, particularly at tthe three Solent locations of Portsmouth, Calshot and Southampton, is considered in detail and harmonic constants derived. The effect of shallow water on the shape of the tidal curve is discussed, and spectral techniques are used to investigate the time series of hourly residuals resulting when the predicted hourly heights are subtracted from those observed. Trends in mean sea level are also discussed. Meteorological effects on sea level and the forms of some particular storm surges which have occurred in the Solent area in the recent past are examined. Assumptions attaching to samples of annual maxima sea levels, along with the statistical background to return periods and risk are critically discussed. It is shown that certain useful information may be abstracted from the annual maxima sample prior to any curve-fitting and extrapolation. Frequency analysis of annual maxima sea levels using the generalised extreme-value distribution is discussed in detail and a method for computing approximate confidence intervals for return period heights is presented and investigated. Censored estimation procedures are given which allow the influence of one or more dubious extreme maxima to be examined. The degree of interaction between tide and surge is shown to increase from Portsmouth to Calshot to Southampton, and the problem of deducing a statistical representation for the predicted tide is discussed, both these topics being relevant to joint surge-tide probability estimation. Two rather different methods of computing the joint probabilities, the traditional convolution method and an alternative approach, are applied to Portsmouth, and compared.

University of Southampton
Walden, Andrew Thomas
Walden, Andrew Thomas

Walden, Andrew Thomas (1981) The statistical analysis of extreme high sea levels utilising data from the Solent area. University of Southampton, Doctoral Thesis.

Record type: Thesis (Doctoral)

Abstract

The prediction of the tidal component of sea level, particularly at tthe three Solent locations of Portsmouth, Calshot and Southampton, is considered in detail and harmonic constants derived. The effect of shallow water on the shape of the tidal curve is discussed, and spectral techniques are used to investigate the time series of hourly residuals resulting when the predicted hourly heights are subtracted from those observed. Trends in mean sea level are also discussed. Meteorological effects on sea level and the forms of some particular storm surges which have occurred in the Solent area in the recent past are examined. Assumptions attaching to samples of annual maxima sea levels, along with the statistical background to return periods and risk are critically discussed. It is shown that certain useful information may be abstracted from the annual maxima sample prior to any curve-fitting and extrapolation. Frequency analysis of annual maxima sea levels using the generalised extreme-value distribution is discussed in detail and a method for computing approximate confidence intervals for return period heights is presented and investigated. Censored estimation procedures are given which allow the influence of one or more dubious extreme maxima to be examined. The degree of interaction between tide and surge is shown to increase from Portsmouth to Calshot to Southampton, and the problem of deducing a statistical representation for the predicted tide is discussed, both these topics being relevant to joint surge-tide probability estimation. Two rather different methods of computing the joint probabilities, the traditional convolution method and an alternative approach, are applied to Portsmouth, and compared.

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Published date: 1981

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Local EPrints ID: 459852
URI: http://eprints.soton.ac.uk/id/eprint/459852
PURE UUID: 4a417447-f406-45b0-b68a-1516f3299eb2

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Date deposited: 04 Jul 2022 17:20
Last modified: 04 Jul 2022 17:20

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Author: Andrew Thomas Walden

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