Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Modelling covariate effects in extremes of storm severity on the Australian North West Shelf
AU - Randell, D.
AU - Wu, Y.
AU - Jonathan, P.
AU - Ewans, K.
PY - 2013
Y1 - 2013
N2 - Careful modelling of covariate effects is critical to reliable specification of design criteria. We present a spline based methodology to incorporate spatial, directional, temporal and other covariate effects in extreme value models for environmental variables such as storm severity. For storm peak significant wave height events, the approach uses quantile regression to estimate a suitable extremal threshold, a Poisson process model for the rate of occurrence of threshold exceedances, and a generalised Pareto model for size of threshold. Multidimensional covariate effects are incorporated at each stage using penalised tensor products of B-splines to give smooth model parameter variation as a function of multiple covariates. Optimal smoothing penalties are selected using cross-validation, and model uncertainty is quantified using a bootstrap resampling procedure. The method is applied to estimate return values for a large spatial neighbourhood of locations off the North West Shelf of Australia, incorporating spatial and directional effects. Copyright © 2013 by ASME.
AB - Careful modelling of covariate effects is critical to reliable specification of design criteria. We present a spline based methodology to incorporate spatial, directional, temporal and other covariate effects in extreme value models for environmental variables such as storm severity. For storm peak significant wave height events, the approach uses quantile regression to estimate a suitable extremal threshold, a Poisson process model for the rate of occurrence of threshold exceedances, and a generalised Pareto model for size of threshold. Multidimensional covariate effects are incorporated at each stage using penalised tensor products of B-splines to give smooth model parameter variation as a function of multiple covariates. Optimal smoothing penalties are selected using cross-validation, and model uncertainty is quantified using a bootstrap resampling procedure. The method is applied to estimate return values for a large spatial neighbourhood of locations off the North West Shelf of Australia, incorporating spatial and directional effects. Copyright © 2013 by ASME.
KW - Bootstrap resampling procedures
KW - Directional effects
KW - Environmental variables
KW - Model uncertainties
KW - North west shelf of australia
KW - North west shelves
KW - Quantile regression
KW - Significant wave height
KW - Arctic engineering
KW - Uncertainty analysis
KW - Storms
U2 - 10.1115/OMAE2013-10187
DO - 10.1115/OMAE2013-10187
M3 - Conference contribution/Paper
SN - 9780791855324
BT - ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering
PB - ASME
ER -