TY - JOUR

T1 - The effect of non-stationarity on extreme sea-level estimation.

AU - Dixon, M. J.

AU - Tawn, J. A.

PY - 1999

Y1 - 1999

N2 - The sea-level is the composition of astronomical tidal and meteorological surge processes. It exhibits temporal non-stationarity due to a combination of long-term trend in the mean level, the deterministic tidal component, surge seasonality and interactions between the tide and surge. We assess the effect of these non-stationarities on the estimation of the distribution of extreme sea-levels. This is important for coastal flood assessment as the traditional method of analysis assumes that, once the trend has been removed, extreme sea-levels are from a stationary sequence. We compare the traditional approach with a recently proposed alternative that incorporates the knowledge of the tidal component and its associated interactions, by applying them to 22 UK data sites and through a simulation study. Our main finding is that if the tidal non-stationarity is ignored then a substantial underestimation of extreme sea-levels results for most sites. In contrast, if surge seasonality and the tide–surge interaction are not modelled the traditional approach produces little additional bias. The alternative method is found to perform well but requires substantially more statistical modelling and better data quality.

AB - The sea-level is the composition of astronomical tidal and meteorological surge processes. It exhibits temporal non-stationarity due to a combination of long-term trend in the mean level, the deterministic tidal component, surge seasonality and interactions between the tide and surge. We assess the effect of these non-stationarities on the estimation of the distribution of extreme sea-levels. This is important for coastal flood assessment as the traditional method of analysis assumes that, once the trend has been removed, extreme sea-levels are from a stationary sequence. We compare the traditional approach with a recently proposed alternative that incorporates the knowledge of the tidal component and its associated interactions, by applying them to 22 UK data sites and through a simulation study. Our main finding is that if the tidal non-stationarity is ignored then a substantial underestimation of extreme sea-levels results for most sites. In contrast, if surge seasonality and the tide–surge interaction are not modelled the traditional approach produces little additional bias. The alternative method is found to perform well but requires substantially more statistical modelling and better data quality.

KW - Annual maximum method • Extreme sea-levels • Extreme value theory • Joint probabilities method • Return level

U2 - 10.1111/1467-9876.00145

DO - 10.1111/1467-9876.00145

M3 - Journal article

VL - 48

SP - 135

EP - 151

JO - Journal of the Royal Statistical Society: Series C (Applied Statistics)

JF - Journal of the Royal Statistical Society: Series C (Applied Statistics)

SN - 0035-9254

IS - 2

ER -