Validation and uncertainty quantification of metocean models for assessing hurricane risk

Abstract

A reliable metocean model, with its uncertainty quantified and its accuracy validated for conditions appropriate to assessing risk, is essential to understand the risk posed by hurricanes to offshore infrastructure such as offshore wind turbines. In this paper, three metocean models are considered, with the seastate predicted using the commercial software Mike 21, and the meteorological forcing defined by three conditions. The three conditions include (1) reanalysis data within and surrounding the hurricane, (2) predictions from the empirical Holland model within the hurricane and reanalysis data surrounding the hurricane, and (3) predictions from the empirical Holland model within the hurricane and wind-free conditions surrounding the hurricane. The accuracy of the first metocean model is validated with (1) measurements of wind speed, wave height, wave period, and storm surge during 23 historical hurricanes from 1999 to 2012 and(2) a comparison to hindcast data from WaveWatch III, another numerical metocean model. The prediction performance of the second and third metocean models is then compared with that of the first to evaluate the impact of meteorological conditions on model predictions, as the third metocean model is necessary for risk analysis, where reanalysis data of meteorological conditions is not available. This study shows that the inconsistency between the modeling of meteorological conditions for risk assessment and for validation is influential for hurricanes with low maximum wind speeds, when model predictions are significantly better if the meteorological conditions surrounding the hurricane wind field are included. This study also shows that this inconsistency is effectively diminished when considering only events with high maximum wind speeds.Since high wind speeds are what is relevant to risk assessments, the third metocean model can be reasonably used to assess hurricane risk. Finally, the uncertainties, biases, and correlations of uncertainties in the model predictions for wind speed, wave height, wave period, and storm surge are quantified for the third metocean model, and a numerical example is constructed to illustrate the impact of including uncertainty on the assessment of risk to offshore infrastructure during hurricanes. The example demonstrates how uncertainty and correlation of uncertainty influence the size and shape of a 50-year environmental contour of wind speed and wave height. KEYWORDSnumerical model validation, offshore hurricane multi-hazard, risk analysis, uncertainty quantification

Ensemble Neural Networks for the Development of Storm Surge Flood Modeling: A Comprehensive Review

“…Some systems are adept at computing random, short-crested waves in coastal regions using third-generation wave models, such as WAVEWATCH III, WAM, or SWAN, or coupling them with other finite-element-based hydrodynamic models [35,36], such as ADCIRC. Atmospheric and tidal forcing is commonly applied to high-resolution wave models such as ADCIRC or SWAN [37,52] to simulate the behavior of ocean waves under different storm conditions and generate synthetic storm datasets that can be used for assessing flood risk and improving coastal management strategies [11].…”

“…The interdependency of these different factors make it notoriously hard to predict the timing and intensity of the hydrodynamic response (e.g., water levels and currents) [6][7][8][9]. Parametric models conventionally incorporate historical or synthetic hurricanes using storm size, intensity, and track, allowing for the prediction of storm surge heights and overland flooding [10,11].…”