Harald E. Krogstad

Probability distributions of surface gravity waves during spectral changes

Simulations have been performed with a fairly narrow band numerical gravity wave model (higher-order nls type) and a computational domain of dimensions

Evolution of a narrow-band spectrum of random surface gravity waves

128\times 128

Probability distributions for maximum wave and crest heights

typical wavelengths. The simulations are initiated with

Satellite wave measurements for coastal engineering applications

\thicksim6\times10^{4}

Height and period distributions of extreme waves

fourier modes corresponding to truncated jonswap spectra and different angular distributions giving both short- and long-crested waves. A development of the spectra on the so-called benjamin–feir timescale is seen, similar to the one reported by dysthe et al. ( J. Fluid Mech. vol. 478, 2003, p.1). The probability distributions of surface elevation and crest height are found to fit theoretical distributions found by tayfun ( J. Geophys. Res. Vol. 85, 1980, p. 1548) very well for elevations up to four standard deviations (for realistic angular spectral distributions). moreover, in this range of the distributions, the influence of the spectral evolution seems insignificant. for the extreme parts of the distributions a significant correlation with the spectral change can be seen for very long-crested waves. For this case we find that the density of large waves increases during spectral change, in agreement with a recent experimental study by onorato et al. ( J. Fluid Mech. 2004 submitted).

Methods for intercomparison of wave measurements

Numerical simulations of the evolution of gravity wave spectra of fairly narrowbandwidth have been performed both for two and three dimensions. Simulationsusing the nonlinear Schr¨odinger (NLS) equation approximately verify the stabilitycriteria of Alber (1978) in the two-dimensional but not in the three-dimensional case.Using a m odified NLS equation (Trulsen et al. 2000) the spectra ‘relax’ towards aquasi-stationary state on a timescale (

High-Resolution Directional Wave Spectra from Horizontally Mounted Acoustic Doppler Current Meters

The paper discusses short- and long-term probability models of ocean waves. The Gaussian theory is reviewed, and nonlinear short-term probability distributions are derived from a narrow band second-order model. The nonlinearity has different impact on different measurement techniques, and this is further demonstrated for wave data from the WAVEMOD Crete measurement campaign and laser data from the North Sea. Finally, we give some examples on how the short-term statistics may be used to estimate the probability distributions for the maximum waves during individual storms as well as in a wave climate described by long-term distributions.

Assimilation of ERS SAR wave spectra in an operational wave model

Measurements from the GEOSAT, ERS-1 and 2 and Topex/Poseidon satellites have now accumulated to over 15 years of global ocean wave and wind data. Extraction of wave height, wind speed and wave period from the satellite altimeters and directional wave spectra from the synthetic aperture radars are reviewed along with recent validation and calibration efforts. Applications of the data to a variety of problems illustrate the potential of satellite wave measurements.

Wave Crest Sensor Intercomparison Study: An Overview of WACSIS

The paper derives probability distributions for height and period for the highest wave occurring at a fixed location when the sea state varies. Short-term distributions of height and period are derived using a data base of waverider data from the Norwegian Sea. The derived theoretical relationships are illustrated by various examples of measured long-term statistics of the sea state.

Spatial Extreme Value Analysis of Nonlinear Simulations of Random Surface Waves

The paper reviews methods for quality assessment and intercomparison of ocean wave data. The sampling variability for conventional time series recordings is summarized and compared to less common area measuring measurements. The sampling variability affects the scatter seen in simultaneous observations, and variability in excess of the sampling variability signifies real differences between the instruments. Various means of intercomparing wave parameters and spectra are discussed and two somewhat unconventional ways of deriving regression and calibration relationships are also shown. The methods are illustrated using data from SCAWVEX, focusing mainly on wave data from the HF radars and Directional Waveriders.