Modification of the Physics and Numerics in a Third-Generation Ocean Wave Model

Bender, Leslie

doi:10.1175/1520-0426(1996)013<0726:motpan>2.0.co;2

Cited by 37 publications

(21 citation statements)

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“…In the literature, numerical diffusion in wave models is sometimes discussed using terms such as "attenuation" and "dissipation" (e.g., Bender 1996). In the context of gravity waves, these terms imply a loss of energy.…”

Section: Propagation Numericsmentioning

confidence: 92%

The U.S. Navy's Global Wind-Wave Models: An Investigation into Sources of Errors in Low-Frequency Energy Predictions

Rogers¹

2002

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Standard Form 298 (Rev. 8-98)Prescribed by ANSI Std. Z39.18Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Approved for public release; distribution is unlimited. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) SPONSOR / MONITOR'S ACRONYM(S) 9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) SPONSOR / MONITOR'S REPORT NUMBER(S)This report describes an investigation to determine the relative importance of various sources of error in the two global-scale models of windgenerated surface waves used operationally by the U.S. Navy. The investigation is limited to low-frequency wave energy (e.g., less than 0.08 Hz). Sources of error are grouped into three broad categories: (1) wave model propagation numerics and resolution, (2) wave model physical formulations, and (3) wind forcing (provided to the wave model by an atmospheric model and/or data assimulation system). Each of the three is described and studied independently using tests and hindcasts of varying complexity. Based on these studies, it appears that in both of the Navy models, numerics and resolution are not first-order sourcess of error, and further suggests that, at present, more error is due to model forcing than due to physical formulation. The importance of accuately capturing the intensity of high-speed wind events is shown to be paramount. Also, it appears that the practical effect of physical formulations on swell in the two operational models is considerably different, whereas differences associated with the generation (low-frequency wave growth) stage are relatively modest between the two models. UnclassifiedUnclassified Unclassified UL 67

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Section: Propagation Numericsmentioning

confidence: 92%

The U.S. Navy's Global Wind-Wave Models: An Investigation into Sources of Errors in Low-Frequency Energy Predictions

Rogers¹

2002

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“…The WAM model Cycle -IV use Janssen formulation intrinsically for wind-wave growth. The physical basis concerning theoretical development of the growth rate parameter (γ i n ) used in this study is explained in published work of Bender (1996). This parameter essentially controls the wind-wave growth in the governing spectral energy balance equation used in WAM model.…”

Section: Formulation For Wind-wave Growthmentioning

confidence: 93%

Parameterization of rain induced surface roughness and its validation study using a third generation wave model

Kumar

Subrahamanyam

2009

Ocean Sci. J.

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The effect of raindrops striking water surface and their role in modifying the prevailing sea-surface roughness is investigated. The work presents a new theoretical formulation developed to study rain-induced stress on sea-surface based on dimensional analysis. Rain parameters include drop size, rain intensity and rain duration. The influences of these rain parameters on young and mature waves were studied separately under varying wind speeds, rain intensity and rain duration. Contrary to popular belief that rain only attenuates surface waves, this study also points out rain duration under certain condition can contribute to wave growth at high wind speeds. Strong winds in conjunction with high rain intensity enhance the horizontal stress component on the sea-surface, leading to wave growth. Previous studies based on laboratory experiments and dimensional analysis do not account for rain duration when attempting to parameterize sea-surface roughness. This study signifies the importance of rain duration as an important parameter modifying sea-surface roughness. Qualitative as well quantitative support for the developed formulation is established through critical validation with reports of several researchers and satellite measurements for an extreme cyclonic event in the Indian Ocean. Based on skill assessment, it is suggested that the present formulation is superior to prior studies. Numerical experiments and validation performed by incorporating in state-of-art WAM wave model show the importance of treating rain-induced surface roughness as an essential pre-requisite for ocean wave modeling studies.

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“…Bender (1996) compared the original Cycle 3 (Snyder et al 1981;Komen et al 1984) and Cycle 4 physics to independent waverider buoy data over a one-month period (July 1992) and concluded that a wave-forecasting model for the Australian region should be based on the Cycle 3 physics. Although this led to underprediction of wave heights, it was shown that by upgrading the first-order propagation numerics to third-order and increasing the magnitude of the dissipation term by approximately 40%, a good match with the buoy observations could be achieved.…”

Section: Wave Modelmentioning

confidence: 99%

Forecast Divergences of a Global Wave Model

Greenslade

Young

2005

Monthly Weather Review

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One of the main limitations to current wave data assimilation systems is the lack of an accurate representation of the structure of the background errors. One method that may be used to determine background errors is the “NMC method.” This method examines the forecast divergence component of the background error growth by considering differences between forecasts of different ranges valid at the same time. In this paper, the NMC method is applied to global forecasts of significant wave height (SWH) and surface wind speed (U10). It is found that the isotropic correlation length scale of the SWH forecast divergence (LSWH) has considerable geographical variability, with the longest scales just to the south of the equator in the eastern Pacific Ocean, and the shortest scales at high latitudes. The isotropic correlation length scale of the U10 forecast divergence (LU10) has a similar distribution with a stronger latitudinal dependence. It is found that both LSWH and LU10 increase as the forecast period increases. The increase in LSWH is partly due to LU10 also increasing. Another explanation is that errors in the analysis or the short-range SWH forecast propagate forward in time and disperse and their scale becomes larger. It is shown that the forecast divergence component of the background error is strongly anisotropic with the longest scales perpendicular to the likely direction of propagation of swell. In addition, in regions where the swell propagation is seasonal, the forecast divergence component of the background error shows a similar strong seasonal signal. It is suggested that the results of this study provide a lower bound to the description of the total background error in global wave models.

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Modification of the Physics and Numerics in a Third-Generation Ocean Wave Model

Cited by 37 publications

References 0 publications

The U.S. Navy's Global Wind-Wave Models: An Investigation into Sources of Errors in Low-Frequency Energy Predictions

The U.S. Navy's Global Wind-Wave Models: An Investigation into Sources of Errors in Low-Frequency Energy Predictions

Parameterization of rain induced surface roughness and its validation study using a third generation wave model

Forecast Divergences of a Global Wave Model

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