Treatment of unresolved islands and ice in wind wave models

Tolman, Hendrik L.

doi:10.1016/s1463-5003(02)00040-9

Cited by 160 publications

(132 citation statements)

References 10 publications

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“…This diversity means that each beach will respond differently to changes in the wave climate. Moreover, a large fraction (25%) of the beaches in WA are perched, meaning that they are fronted by and/or overlying a shallow rock platform (Stul 2005). Assessing the interaction between an increasing mean sea level, a changing wave climate, the effect of the rock platform and the sediment dynamics is a challenge.…”

Section: Discussionmentioning

confidence: 99%

Inter-annual variability and longer-term changes in the wave climate of Western Australia between 1970 and 2009

2011

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Quantifying the long-term variability in wave conditions incident on a coastline is critical for predicting its resilience to future changes in the wave climate. In this study, a 40-year wave hindcast of the southern Indian Ocean has been created to assess the inter-annual variability and longer-term changes in the wave climate around Western Australia (WA) between 1970 and 2009. The model was validated against measurements from five wave buoys located along the WA coast. Changes in the mean annual significant wave height, 90th percentile wave height, peak period and mean wave direction were assessed, and the tracks of all wave events generating wave heights above 7 m were digitised and analysed for significant changes. Results show strong annual and inter-annual variability in the mean significant wave height, the 90th percentile wave height and the number of large events (wave height>7 m) that impact the WA coastline. A significant positive trend in annual mean wave height was found in the southwest region of WA over the 40-year simulation.

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Section: Discussionmentioning

confidence: 99%

Inter-annual variability and longer-term changes in the wave climate of Western Australia between 1970 and 2009

2011

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“…Maldives, Polynesian, Hawaii, Aleutian, Galapagos, Caribean, Azores, Falkland...) is particularly clear. These arise either through grid-scale variation in model bathymetry, or through WAVE-WATCH's representation of subgrid-scale obstruction by island chains (Tolman, 2003). Further to these static geographic features, the signatures of dynamic weather systems also appear more clearly such as the weather fronts in depressions, orographic wind jets etc.…”

Section: Scaling Analysis For a Global Forecast Snapshotmentioning

confidence: 99%

A quadtree-adaptive spectral wave model

et al. 2010

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A spectral wave model coupling a quadtree-adaptive discretisation of the two spatial dimensions with a standard discretisation of the two spectral dimensions is described. The implementation is greatly simplified by reusing components of the Gerris solver (for spatial advection on quadtrees) and WAVEWATCH III (for spectral advection and source terms). Strict equivalence between the anisotropic diffusion and spatial filtering methods for alleviation of the Garden Sprinkler Effect (GSE) is demonstrated. This equivalence facilitates the generalisation of GSE alleviation techniques to quadtree grids. For the case of a cyclone-generated wave field, the cost of the adaptive method increases linearly with spatial resolution compared to quadratically for constant-resolution methods. This leads to decreases in runtimes of one to two orders of magnitude for practical spatial resolutions. Similar efficiency gains are shown to be possible for global spectral wave forecasting.

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“…Dissipation terms due to whitecapping, depth-induced wave breaking, and quadruplet and triad wave interactions were considered in the simulation. WWIII consists of source terms with different physics package options that consider sea ice and various wind-wave interaction and dissipation effects [6,36,37]. Specifically, the ST2 physics package is based on previously developed wind input and nonlinear interaction source terms and a new dissipation source term consisting of high-and low-frequency constituents [36].…”

Section: Wave Modelsmentioning

confidence: 99%

“…The most popular third-generation phase-average spectral models, such as WAVEWATCH III ® (WWIII) [1], the Wave Action Model (WAM) [2], Simulating WAve Nearshore (SWAN) [3], TOMAWAC [4], and MIKE-21 Spectral Wave (MIKE-21 SW) [5] models, have been widely validated in many coastal waters and open oceans worldwide. For example, the WWIII model has been maintained and used for operational ocean wave forecasts by the National Oceanic and Atmospheric Administration's (NOAA's) National Centers for Environmental Prediction (NCEP) [1,6,7]. The WAM is operated by the European Centre for Medium-Range Weather Forecasts (ECMWF), which provides wave hindcast data over the North Atlantic Ocean.…”

Section: Introductionmentioning

confidence: 99%

Wave Resource Characterization Using an Unstructured Grid Modeling Approach

Yang

Wang

2018

Energies

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Notably, spectral analysis indicates that the ST4 physics package improves upon the ST2 physics package's ability to predict wave power density for large waves, which is important for wave resource assessment, load calculation of devices, and risk management. In addition, bivariate distributions show that the simulated sea state of maximum occurrence with the ST4 physics package matched the observed data better than with the ST2 physics package. This study demonstrated that the unstructured grid wave modeling approach, driven by regional nested grid WWIII outputs along with the ST4 physics package, can efficiently provide accurate wave hindcasts to support wave resource characterization. Our study also suggests that wind effects need to be considered if the dimension of the model domain is greater than approximately 100 km, or O (10 2 km).

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Treatment of unresolved islands and ice in wind wave models

Cited by 160 publications

References 10 publications

Inter-annual variability and longer-term changes in the wave climate of Western Australia between 1970 and 2009

Inter-annual variability and longer-term changes in the wave climate of Western Australia between 1970 and 2009

A quadtree-adaptive spectral wave model

Wave Resource Characterization Using an Unstructured Grid Modeling Approach

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