Directional Validation of Wave Predictions*

Rogers, W. Erick; Wang, David W. C.

doi:10.1175/jtech1990.1

Cited by 29 publications

(17 citation statements)

References 34 publications

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“…We thus follow the analysis of wave model performances by Rogers and Wang (2007), hereinafter RW2007, and give results for the Lake Michigan, representative of relatively young waves. The model was applied with parameterizations BAJ, TC, TEST437 and TEST441 over the same time frame as investigated by RW2007, September 1 to November 14, 2002.…”

Section: B Lake Michiganmentioning

confidence: 99%

Semiempirical Dissipation Source Functions for Ocean Waves. Part I: Definition, Calibration, and Validation

Ardhuin

Rogers

Babanin

et al. 2010

Journal of Physical Oceanography

781

681

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New parameterizations for the spectral dissipation of wind-generated waves are proposed. The rates of dissipation have no predetermined spectral shapes and are functions of the wave spectrum, in a way consistent with observation of wave breaking and swell dissipation properties. Namely, swell dissipation is nonlinear and proportional to the swell steepness, and wave breaking only affects spectral components such that the non-dimensional spectrum exceeds the threshold at which waves are observed to start breaking. An additional source of short wave dissipation due to long wave breaking is introduced, together with a reduction of wind-wave generation term for short waves, otherwise taken from Janssen (J. Phys. Oceanogr. 1991). These parameterizations are combined and calibrated with the Discrete Interaction Approximation of Hasselmann et al. (J. Phys. Oceangr. 1985) for the nonlinear interactions. Parameters are adjusted to reproduce observed shapes of directional wave spectra, and the variability of spectral moments with wind speed and wave height. The wave energy balance is verified in a wide range of conditions and scales, from the global ocean to coastal settings. Wave height, peak and mean periods, and spectral data are validated using in situ and remote sensing data. Some systematic defects are still present, but the parameterizations probably yield the most accurate overall estimate of wave parameters to date. Perspectives for further improvement are also given.

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Section: B Lake Michiganmentioning

confidence: 99%

Semiempirical Dissipation Source Functions for Ocean Waves. Part I: Definition, Calibration, and Validation

Ardhuin

Rogers

Babanin

et al. 2010

Journal of Physical Oceanography

781

681

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show abstract

“…This simulation is a test in which the dominant conditions are windseas and young seas. It is based on the SWAN model simulation of Rogers and Wang (2007) and was run with a spatial resolution of 4 km. Due to the limited fetch and topography of the lake, older swell does not exist.…”

Section: Lake Michiganmentioning

confidence: 99%

Observation-based source terms in the third-generation wave model WAVEWATCH

et al. 2015

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Measurements collected during the AUSWEX field campaign, at Lake George (Australia), resulted in new insights into the processes of wind wave interaction and whitecapping dissipation, and consequently new parametrizations of the input and dissipation source terms. The new nonlinear wind input term developed accounts for dependence of the growth on wave steepness, airflow separation, and for negative growth rate under adverse winds. The new dissipation terms feature the inherent breaking term, a cumulative dissipation term and a term due to production of turbulence by waves, which is particularly relevant for decaying seas and for swell. The latter is consistent with the observed decay rate of ocean swell. This paper describes these source terms implemented in WAVEWATCH III and evaluates the performance against existing source terms in academic duration-limited tests, against buoy measurements for windsea-dominated conditions, under conditions of extreme wind forcing (Hurricane Katrina), and against altimeter data in global hindcasts. Results show agreement by means of growth curves as well as integral and spectral parameters in the simulations and hindcast.Keywords: wave modelling, wind input, negative input, whitecapping dissipation, swell dissipation 105 ("negative input") is that it is calculated from friction velocity and thus wind speed and does not dissipate swells in absence of wind (Tolman and Chalikov, 1996; Tolman, 2002). The input in TEST451 accounts for swell dissipation due to interaction with the air and thus can become negative (Ardhuin et al., 2010(Ardhuin et al., , 2011a. The dissipation includes a threshold and cumulative term. 110 The outline of the paper is as follows. Section 2 provides detailed description of the wind input term and the dissipation source terms implemented in WAVEWATCH. Section 3 contains description of the setup and results for the idealised academic tests and simulations selected to test the performance of the observation-based source terms. In Section 4 the results are discussed 115 and the conclusions are formulated in Section 5. 6 2. Source terms 2.1. Wind input The wind input function represents the energy flux transferred from wind to waves. This term is due to form drag, i.e. pressure acting on the surface 120 slope of the waves (e.g. Donelan et al., 2006). AUSWEX data analysis and the wind input parameterization reported by Donelan et al. (2005, 2006) and Babanin et al. (2007a) shows dependencies that have not been reported in previous experiments. Measurements of wave growth during AUSWEX were available for a range of wind-forcing conditions including very young waves 125 U 10 /c p = 5.1 − 7.6 (c p is the phase speed at the spectral peak) of varying steepness. This unique dataset revealed a number of new features: (i) full airflow separation with a relative reduction of wind input for conditions of strong winds/steep waves, if compared with its extrapolation from the moderate conditions (Donelan et al., 2006); (ii) dependence of the wave growth rate on 130 w...

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“…Note that, to yield an accurate current vector, this method requires the wave energy spectrum to have significant directional spread. This condition is generally fulfilled under natural sea states (e.g., Rogers and Wang 2007).…”

Section: A Standard Current Retrieval Revisitedmentioning

confidence: 99%

On Shipboard Marine X-Band Radar Near-Surface Current ‘‘Calibration’’

Lund

Graber

Hessner

et al. 2015

Journal of Atmospheric and Oceanic Technology

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The ocean wave signatures within conventional noncoherent marine X-band radar (MR) image sequences can be used to derive near-surface current information. On ships, an accurate near-real-time record of the near-surface current could improve navigational safety. It could also advance understanding of air-sea interaction processes. The standard shipboard MR near-surface current estimates were found to have large errors (of the same order of magnitude as the signal) that are associated with ship speed and heading. For acoustic Doppler current profilers (ADCPs), ship heading errors are known to induce a spurious cross-track current that is proportional to the ship speed and the sine of the error angle. Conventional mechanical gyrocompasses are very reliable heading sensors, but they are too inaccurate for shipboard ADCPs. Within the ADCP community, it is common practice to correct the gyrocompass measurements with the help of multiantenna carrier-phase differential GPS systems. This study shows how a similar multiantenna GPS-based ship heading correction technique stands to improve the accuracy of MR near-surface current estimates. Changes to the standard MR near-surface current retrieval method that are necessary for high-quality results from ships are also introduced. MR and ADCP data collected from R/V Roger Revelle during the Impact of Typhoons on the Ocean in the Pacific (ITOP) program in 2010 are used to demonstrate the MR currents' accuracy and reliability.

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Directional Validation of Wave Predictions*

Cited by 29 publications

References 34 publications

Semiempirical Dissipation Source Functions for Ocean Waves. Part I: Definition, Calibration, and Validation

Semiempirical Dissipation Source Functions for Ocean Waves. Part I: Definition, Calibration, and Validation

Observation-based source terms in the third-generation wave model WAVEWATCH

On Shipboard Marine X-Band Radar Near-Surface Current ‘‘Calibration’’

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