On Sampling Between Data of Significant Wave Height for Long-Term Analysis With Equivalent Triangular Storm Model

2013 ◽  
Author(s):  
Felice Arena ◽  
Valentina Laface
Keyword(s):  
Wave Height ◽  
Return Period ◽  
Significant Wave Height ◽  
Significant Wave ◽  
Storm Duration ◽  
The Mean ◽  
Using Data ◽  
Two Parameters ◽  
Mean Time

This work proposes an analysis of storms in Pacific and Atlantic Ocean, which is carried out by applying the Boccotti’s Equivalent Triangular Storm (ETS) model. The ETS model represents any actual storm by means of two parameters. The former gives the storm intensity, which is equal to the maximum significant wave height during the actual storm; the latter represents the storm duration and it is such that the maximum expected wave height is the same in the actual storm and in the equivalent triangular storm. Data from buoys of the NOAA-NDBC (National Data Buoy Center, USA) are used in the applications, by considering different sampling Δt between two consecutive records, which varies between 1 and 6 hours. The sensitivity of the ETS model with the variation of Δt is investigated for the long-term modeling of severe storms. The results show that the structure of storms is strongly modified as Δt increases: both the intensity and the duration may change significantly. The effects of this results for long term statistics are investigated by means of the return period R(Hs > h) of a storm in which the maximum significant wave height exceeds the threshold h, which is evaluated by using data with different sampling Δt between two consecutive records. Finally for different values of the return period R, the return value of significant wave height and the mean persistence Dm(h), giving the mean time during which the significant wave height is greater than fixed threshold (in the storms where the threshold is exceeded), are calculated.

On Long Term Statistics of Ocean Storms Starting From Partitioned Sea States

2017 ◽  
Author(s):  
Valentina Laface ◽  
Felice Arena ◽  
Christophe Maisondieu ◽  
Alessandra Romolo
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wind Waves ◽  
Storm Events ◽  
Significant Wave ◽  
Open Sea ◽  
Storm Duration ◽  
Two Parameters ◽  
Actual Seas

The paper proposes an analysis of ocean storms carried out starting from significant wave height time series of HOMERE sea-states hindcast database based on WAVEWATCH III model. Considering that wave spectra often exhibit multiple peaks due to the coexistence of wind waves and swells, here sea states are described by partitioned sea states that can be interpreted physically as representing independent wave systems. The analysis presented here in the paper deals with the contribution of swells to the storm peaks and on how they influence the long term statistics. The sensitivity of return values of significant wave height to swell contribution is investigated via an application of the Equivalent Triangular Storm Model (ETS). The ETS model provides analytical solution for the calculation of the return period R(Hs>h) of a sea storm whose maximum significant wave height exceeds a given threshold h. The approach of ETS consists in substituting each actual storm with an ETS described by two parameters: the storm intensity, that is the triangle height and it is equal to the maximum significant wave height during the actual storm; the storm duration, that is achieved imposing the equality between the maximum expected wave height of actual and equivalent storms. It has been experimentally proved that the actual storm and associated ETS are statistically equivalent because they have the same maximum significant wave height and the same probability P(Hmax>H) that the maximum wave height exceeds a given threshold H. The sequence of ETSs obtained in this way represents the equivalent sea, while the sequence of actual storms is the actual sea. The equivalent and actual seas present the same wave risk because they are characterized by the same number of storm events, each of them with the same intensity and the same P(Hmax>H). For the proposed analysis a set of four points from open sea to the coast is considered in area of the Gulf of Biscay (France). The results show that the contribution of swells is more significant for the storms of small and medium intensity and decreases for increasing storm intensities. Further return values variability neglecting swell is less than 7% at any point for return periods up to 100 years.

Comparison of Design Wave Approach and Short Term Approach With Increased Wave Height in the Evaluation of Whipping Induced Bending Moment

2012 ◽  
Author(s):  
Quentin Derbanne ◽  
Fabien Bigot ◽  
Guillaume de Hauteclocque
Keyword(s):  
Wave Height ◽  
Return Period ◽  
Significant Wave Height ◽  
Bending Moment ◽  
Short Term ◽  
Sea State ◽  
Significant Wave ◽  
Non Linear ◽  
Term Analysis

The evaluation of extreme bending moment corresponding to a 25 years return period requires very long simulations on a large number of sea states. This long term analysis is easy to do with a linear model of the ship response, but is impractical when using a time consuming model including non linear and slamming loads. In that case some simplified methods need to be applied. These methods are often based on Equivalent Design Waves (EDW) which are calibrated on the extreme linear value. The general practice is to define the EDW as a regular wave. A very simple method is to compute the non linear bending moment applying the pressure correction on the hull without recomputing the ship motions. A better method is to recompute in time domain the non linear ship response on this Design Wave. It is even possible to define a more realistic Design Wave, taking into account the frequency and directional content of the sea states used in the long term analysis: those waves are called Response Conditioned Wave and Directional Response Conditioned Waves. The different methods are applied to an Ultra Large Container Ship (ULCS). Hydro-structure calculations are carried out on a severe design sea state, taking into account Froude-Krylov pressure correction, slamming forces and whipping response. Results of a very long computation are compared to the results of the Design Wave approaches. Another method is proposed to compute very rare events. It is based on an artificial increase of the significant wave height of the sea state, and the assumption of the independence of the non linear effects to the significant wave height. Using this method it is possible, with a simulation of only a few hours, to predict a very rare short term event, corresponding to a very long return period. The results are compared to the Design Wave results and appear to be much more precise.

Statistical Uncertainty in Long-Term Distributions of Significant Wave Height

1996 ◽  
Vol 118 (4) ◽  
pp. 284-291 ◽  
Author(s):  
C. Guedes Soares ◽  
A. C. Henriques
Keyword(s):  
Probability Distribution ◽  
Wave Height ◽  
Significant Wave Height ◽  
Data Sets ◽  
Monthly Basis ◽  
Significant Wave ◽  
Fitting Procedure ◽  
The One ◽  
Homogeneous Data

This work examines some aspects involved in the estimation of the parameters of the probability distribution of significant wave height, in particular the homogeneity of the data sets and the statistical methods of fitting a distribution to data. More homogeneous data sets are organized by collecting the data on a monthly basis and by separating the simple sea states from the combined ones. A three-parameter Weibull distribution is fitted to the data. The parameters of the fitted distribution are estimated by the methods of maximum likelihood, of regression, and of the moments. The uncertainty involved in estimating the probability distribution with the three methods is compared with the one that results from using more homogeneous data sets, and it is concluded that the uncertainty involved in the fitting procedure can be more significant unless the method of moments is not considered.

scholarly journals Long-Term and Seasonal Trends in Global Wave Height Extremes Derived from ERA-5 Reanalysis Data

2020 ◽  
Vol 8 (12) ◽  
pp. 1015
Author(s):  
Alicia Takbash ◽  
Ian R. Young
Keyword(s):  
Southern Hemisphere ◽  
Wave Height ◽  
Significant Wave Height ◽  
Reanalysis Data ◽  
Extreme Value Analysis ◽  
Winter Storms ◽  
Value Analysis ◽  
Weather Forecasts ◽  
Significant Wave

A non-stationary extreme value analysis of 41 years (1979–2019) of global ERA5 (European Centre for Medium-Range Weather Forecasts Reanalysis) significant wave height data is undertaken to investigate trends in the values of 100-year significant wave height, Hs100. The analysis shows that there has been a statistically significant increase in the value of Hs100 over large regions of the Southern Hemisphere. There have also been smaller decreases in Hs100 in the Northern Hemisphere, although the related trends are generally not statistically significant. The increases in the Southern Hemisphere are a result of an increase in either the frequency or intensity of winter storms, particularly in the Southern Ocean.

scholarly journals ON LONG-TERM STATISTICS FOR OCEAN AND COASTAL WAVES

1978 ◽  
Vol 1 (16) ◽  
pp. 2 ◽  
Author(s):  
Michel K. Ochi
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Contingency Table ◽  
Statistical Properties ◽  
Significant Wave ◽  
Coastal Waves ◽  
Normal Probability ◽  
Log Normal ◽  
Confidence Domain

This paper discusses the statistical properties of long-term ocean and coastal waves derived from analysis of available data. It was found from the results of the analysis that the statistical properties of wave height and period obey the bi-variate log-normal probability law. The method to determine the confidence domain for a specified confidence coefficient is presented so that reliable information in severe seas where data are always sparse can be obtained from a contingency table. Estimation of the extreme significant wave height expected in the long-term is also discussed.

Uncertainties in Extreme Wave Height Estimates for Hurricane-Dominated Regions

2007 ◽  
Vol 129 (4) ◽  
pp. 300-305 ◽  
Author(s):  
Philip Jonathan ◽  
Kevin Ewans
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Small Data ◽  
Extreme Wave ◽  
Significant Wave ◽  
Wave Characteristics ◽  
Height Estimates ◽  
Wave Heights ◽  
Using Data ◽  
High Percentile

Inherent uncertainties in estimation of extreme wave heights in hurricane-dominated regions are explored using data from the GOMOS Gulf of Mexico hindcast for 1900–2005. In particular, the effect of combining correlated values from a neighborhood of 72 grid locations on extreme wave height estimation is quantified. We show that, based on small data samples, extreme wave heights are underestimated and site averaging usually improves estimates. We present a bootstrapping approach to evaluate uncertainty in extreme wave height estimates. We also argue in favor of modeling supplementary indicators for extreme wave characteristics, such as a high percentile (95%) of the distribution of 100-year significant wave height, in addition to its most probable value, especially for environments where the distribution of 100-year significant wave height is strongly skewed.

scholarly journals Projected sea level rise and changes in extreme storm surge and wave events during the 21st century in the region of Singapore

2015 ◽  
Vol 12 (6) ◽  
pp. 2955-3001
Author(s):  
H. Cannaby ◽  
M. D. Palmer ◽  
T. Howard ◽  
L. Bricheno ◽  
D. Calvert ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Wave Height ◽  
21St Century ◽  
Significant Wave Height ◽  
Quantitative Assessment ◽  
Climate Model ◽  
Mean Sea Level ◽  
Significant Wave

Abstract. Singapore is an island state with considerable population, industries, commerce and transport located in coastal areas at elevations less than 2 m making it vulnerable to sea-level rise. Mitigation against future inundation events requires a quantitative assessment of risk. To address this need, regional projections of changes in (i) long-term mean sea level and (ii) the frequency of extreme storm surge and wave events have been combined to explore potential changes to coastal flood risk over the 21st century. Local changes in time mean sea level were evaluated using the process-based climate model data and methods presented in the IPCC AR5. Regional surge and wave solutions extending from 1980 to 2100 were generated using ~ 12 km resolution surge (Nucleus for European Modelling of the Ocean – NEMO) and wave (WaveWatchIII) models. Ocean simulations were forced by output from a selection of four downscaled (~ 12 km resolution) atmospheric models, forced at the lateral boundaries by global climate model simulations generated for the IPCC AR5. Long-term trends in skew surge and significant wave height were then assessed using a generalised extreme value model, fit to the largest modelled events each year. An additional atmospheric solution downscaled from the ERA-Interim global reanalysis was used to force historical ocean model simulations extending from 1980–2010, enabling a quantitative assessment of model skill. Simulated historical sea surface height and significant wave height time series were compared to tide gauge data and satellite altimetry data respectively. Central estimates of the long-term mean sea level rise at Singapore by 2100 were projected to be 0.52 m (0.74 m) under the RCP 4.5 (8.5) scenarios respectively. Trends in surge and significant wave height 2 year return levels were found to be statistically insignificant and/or physically very small under the more severe RCP8.5 scenario. We conclude that changes to long-term mean sea level constitute the dominant signal of change to the projected inundation risk for Singapore during the 21st century. We note that the largest recorded surge residual in the Singapore Strait of ~ 84 cm lies between the central and upper estimates of sea level rise by 2100, highlighting the vulnerability of the region.

Simulation of Jack-Up Overturning Using the Monte Carlo Method With Artificially Increased Significant Wave Height

2010 ◽  
Author(s):  
Jo̸rgen Juncher Jensen
Keyword(s):  
Monte Carlo ◽  
Wave Height ◽  
Time Domain ◽  
Significant Wave Height ◽  
Reliability Index ◽  
Form Analysis ◽  
Significant Wave ◽  
The Mean ◽  
The Time Domain ◽  
Jack Up

It is well known from linear analyses in stochastic seaway that the mean out-crossing rate of a level r is given through the reliability index, defined as r divided by the standard deviation. Hence, the reliability index becomes inversely proportional to the significant wave height. For non-linear processes the mean out-crossing rate depends non-linearly on the response level r and a good estimate can be found using the First Order Reliability Method (FORM), see e.g. Jensen and Capul (2006). The FORM analysis also shows that the reliability index is strictly inversely proportional to the significant wave height irrespectively of the non-linearity in the system. However, the FORM analysis only gives an approximation to the mean out-crossing rate. A more exact result can be obtained by Monte Carlo simulations, but the necessary length of the time domain simulations for very low out-crossing rates might be prohibitive long. In such cases the property mentioned above for the FORM reliability index can be assumed valid in the Monte Carlo simulations making it possible to increase the out-crossing rates and thus reduced the necessary length of the time domain simulations by applying a larger significant wave height than relevant from a design point-of-view. The mean out-crossing rate thus obtained can then afterwards be scaled down to the actual significant wave height. Some previous results using this property have been presented by Tonguc and So¨ding (1986), albeit in a more empirical way. In the present paper the usefulness of this property to estimate extreme wave loads will be evaluated considering the overturning of a jack-up rig.

A Parameterization of DNV GL Storm Profile for Long-Term Analysis of Ocean Storms: Trapezoidal Storm Model

2019 ◽  
Author(s):  
Valentina Laface ◽  
Elzbieta M. Bitner-Gregersen ◽  
Felice Arena ◽  
Alessandra Romolo
Keyword(s):  
Wave Height ◽  
Return Period ◽  
Model Development ◽  
Closed Form Solution ◽  
Form Solution ◽  
Storm Intensity ◽  
Storm Duration ◽  
Storm Evolution ◽  
Fixed Constant

Abstract The paper introduces a parameterization of the DNV GL storm profile for developing an analytical model for calculations of the return period of a storm whose peak exceeds a given threshold. The DNV GL storm evolution is represented via an isosceles trapezoidal shape in which the minor base represents the storm peak duration, the major base the total storm duration and the height is half of the highest significant wave height in the actual storm. In this representation, the storm duration is not related to the storm intensity and it is fixed constant and equal to 42 hours, while the peak duration is assumed to be 6 hours. The parameterization proposed in the paper consists in expressing the peak duration as a fraction of the total storm duration allowing to investigate the effects of storm peak duration on long term estimates. The analytical solution for the return period is derived by following the classical approach of Equivalent Storm Models that is referring to the equivalent storm sequence, with the only difference that all the Trapezoidal Storm durations are identical whatever the storm intensity is. This assumption leads to significant simplification on the model development and potential employment as well. Further, a closed form solution is achieved for the return period which is also a generalization of the triangular shape. Finally, data analysis with NDBC buoys data is carried out for validating the model and elucidating analogies and differences with respect to classical Equivalent Storm approach. Results have shown that the Trapezoidal Model can be thought as a triangular one with a prudential factor on the storm peak duration which results in a reasonable overestimation of maximum expected wave height and return values.

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