Minimisation of the Uncertainty in Estimation of Extreme Coastal Wave Heights

You, Zai-Jin; Yin, Baoshu; Ji, Zezhou; Hu, Cong

doi:10.2112/si75-256.1

Cited by 3 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An inherent negative bias in the model has thus been completely removed. It is worth mentioning that the presence of such a negative bias confirms what had been highlighted in previous work [1,3,25,38], i.e., that the weather/wave models underestimate the extremes despite the constant assimilation of satellite measurement, which due to their coarse temporal and spatial resolution are likely to miss the strongest peaks of the storms.…”

Section: Discussionsupporting

confidence: 85%

“…In [23], data produced by SWAVE wave model driven by ECMWF ERA-Interim wind data were used to compute SWH 100 years extreme values in various locations. Joint distribution of the extreme wave height and wind speed are considered in [24].Another important aspect, which has been tackled by many researchers, and which has significant connection with the present paper, is the influence of various factors on the accuracy of EVPD estimates, especially when synthetic rather than experimental data are used: You et al [25] found that the uncertainty is caused mainly by short wave record, missing storm wave data, different methods, high or too low thresholds. The effect of threshold values on the estimates of extreme wave heights is considered in [26][27][28][29].…”

mentioning

confidence: 98%

See 1 more Smart Citation

An Experimental Assessment of Extreme Wave Evaluation by Integrating Model and Wave Buoy Data

Reale¹,

Dentale²,

Furcolo³

et al. 2020

Water

View full text Add to dashboard Cite

Calculating the significant wave height (SWH) in a given location as a function of the return time is an essential tool of coastal and ocean engineering; such a calculation can be carried out by making use of the now widely available weather and wave model chains, which often lead to underestimating the results, or by means of in situ experimental data (mostly, wave buoys), which are only available in a limited number of sites. A procedure is hereby tested whereby the curves of extreme SWH as a function of the return time deriving from model data are integrated with the similar curves computed from buoy data. A considerable improvement in accuracy is gained by making use of this integrated procedure in all locations where buoy data series are not available or are not long enough for a correct estimation. A useful and general design tool has therefore been provided to derive the extreme value SWH for any point in a given area.data raises however various issues: apart from the obvious problem of reliability of the model chains of both the atmospheric and the sea wave parts, an important aspect is the way through which ground truth wave data are assimilated into the analysis. Most of the assimilation procedures are carried out with satellite altimeter data, which are scattered in time (at many hours' intervals) and wide apart in space (tens or hundreds of kilometers), so extreme SWH values may often be missed. It is also worth noting that the sampling time of the models, i.e., the time interval at which data are stored and released, is often higher than the standard sampling time of buoys, thus causing a negative bias on the estimated extreme values [1][2][3].In order to overcome these problems, an integrated procedure [4] was been proposed by some of the authors of the present paper whereby the curves of extreme SWH as a function of the return time T R (in the following: SWH(T R )) deriving from synthetic data are compared and calibrated with the similar curves computed from buoy data in different locations. This provides a way of deriving SWH(T R ) curves for sites where no experimental data are available.The present paper presents an extension of the same technique and provides an experimental authentication of the methodology based on a new large set of reliable data along the coasts of the USA.The determination of the probability of extreme SWH is one of the main problems of coastal, offshore, and marine engineering, so that the relevant literature is not only extensive, but also increasing with time as the technology improves and the requirements become more stringent. Therefore, in the following, only contributions which are connected to the aims of this paper will be considered.All the procedures are substantially based on fitting Extreme Value Probability Distributions (in the following: EVPD) to buoy recorded time series of SWH; references on the general problem date back to many years ago [5], however Goda's textbook [6] is still the most common reference for maritime engineering, even though many authors...

show abstract

Section: Discussionsupporting

confidence: 85%