Pacific Hindcast Performance of Three Numerical Wave Models

Abstract

Although mean or integral properties of wave spectra are typically used to evaluate numerical wave model performance, one must look into the spectral details to identify sources of model deficiencies. This creates a significant problem, as basin-scale wave models can generate millions of independent spectral values. To facilitate selection of a wave modeling technology for producing a multidecade Pacific hindcast, a new approach was developed to reduce the spectral content contained in detailed wave hindcasts to a convenient set of performance indicators. The method employs efficient image processing tools to extract windsea and swell wave components from monthly series of nondirectional and directional wave spectra. Using buoy observations as ground truth, both temporal correlation (TC) and quantile-quantile (QQ) statistical analyses are used to quantify hindcast skill in reproducing measured wave component height, period, and direction attributes. An integrated performance analysis synthesizes the TC and QQ results into a robust assessment of prediction skill and yields distinctive diagnostics on model inputs and source term behavior. The method is applied to a set of Pacific basin hindcasts computed using the WAM, WAVEWATCH III, and WAVAD numerical wave models. The results provide a unique assessment of model performance and have guided the selection of WAVEWATCH III for use in Pacific hindcast production runs for the U.S. Army Corps of Engineers Wave Information Studies Program.

A validation of an operational wave and surge prediction system for the Dutch coast

“…To this end, an algorithm will be applied on the total wave spectrum to differentiate between energy that belongs to wind sea and swell. The algorithm will largely follow Portilla et al (2009) and Hanson et al (2009). Here, for simplification we make an assumption that the total energy content in the spectrum only consists of one system of wind sea and one system of swell.…”

“…On a global scale, Hanson et al (2009) presented a skill assessment of three different regional wave models: WAM (Gunther, 2002), WAVE-WATCH III (Tolman, 2009), and WAVAD (Resio and Perrie, 1989). They performed multi-decadal hindcasts for the Pacific Ocean, and found that in general, all three models show good skill, with WAVEWATCH III performing slightly better than the other two.…”

Wave Hindcasting Using WAM and WAVEWATCH III: A Comparison Study Utilizing Oceansat-2 (OSCAT) Winds

“…The remaining source terms such as wave wave interaction and dissipation also have considerable influences in the performance of WAM and WWIII. The wave wave interaction term used the Discrete Interaction Approximation (DIA) of Hasselmann and Hasselmann [20]; in which; away from the spectral peak and in multimodal wave fields the DIA greatly under samples the complex set of nonlinear interactions [21] leading to erroneous estimates of spectral source function, which will potentially result in shapes, deviating from observations. Apart from this, most importantly in both the models, the different representation of swell propagation in model physics could be a possible reason for deviations at the buoy location.…”

Identification of ‘energetic’ swell waves in a tidal strait

“…Methods of partitioning wave spectra have been widely published Voorrips et al, 1997;Phillips, 1999, 2001;Hanson et al, 2009) and have been found to be useful as more information is provided regarding the different components of the wave spectrum. The spectral partitioning scheme designed by Hanson and Phillips (2001) uses the morphology of the wave spectrum to identify separate wave systems from different sources.…”