Quasi-linear Theory of Wind-Wave Generation Applied to Wave Forecasting

Janssen, Peter A. E. M.

doi:10.1175/1520-0485(1991)021<1631:qltoww>2.0.co;2

Cited by 789 publications

(630 citation statements)

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“…The European Centre for Medium-Range Weather Forecasts (ECMWF) is the pioneer in the development and implementation of coupling systems. ECMWF developed a coupled atmosphericocean wave model in order to be able to have two-way interaction, based on the quasi-linear theory of Janssen (1989Janssen ( , 1991. The ocean wave model of ECMWF (ECMWF WAM (wave model) or ECWAM) is fully coupled to the integrated forecasting system (IFS), which is the operational global meteorological forecasting model of the ECMWF (IFS Documentation, 2013;Diamantakis and Flemming, 2014).…”

Section: P Katsafados Et Al: a Fully Coupled Atmosphere-ocean Wave mentioning

confidence: 99%

“…Therefore, no interaction takes place between the two models. In parallel, the WAM model considers a wind input source function to the wave spectrum equation based on the quasilinear theory of Janssen (1989Janssen ( , 1991, where the transfer of momentum from the wind to the wave field depends simultaneously on the wind stress and the sea state itself. Hence, the WAM model includes a set of diagnostic equations for modeling the sea surface roughness feedback on the near-surface atmospheric boundary layer (Janssen, 1989).…”

Section: The Theoretical Backgroundmentioning

confidence: 99%

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A fully coupled atmosphere–ocean wave modeling system for the Mediterranean Sea: interactions and sensitivity to the resolved scales and mechanisms

et al. 2016

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Abstract. It is commonly accepted that there is a need for a better understanding of the factors that contribute to air-sea interactions and their feedbacks. In this context it is important to develop advanced numerical prediction systems that treat the atmosphere and the ocean as a unified system. The realistic description and understanding of the exchange processes near the ocean surface requires knowledge of the sea state and its evolution. This can be achieved by considering the sea surface and the atmosphere as a continuously crosstalking dynamic system. Following and adapting concepts already developed and implemented in large-scale numerical weather models and in hurricane simulations, this study aims to present the effort towards developing a new, highresolution, two-way fully coupled atmosphere-ocean wave model in order to support both operational and research activities. A specific issue that is emphasized is the determination and parameterization of the air-sea momentum fluxes in conditions of extremely high and time-varying winds. Software considerations, data exchange as well as computational and scientific performance of the coupled system, the so-called WEW (worketa-wam), are also discussed. In a case study of a high-impact weather and sea-state event, the wind-wave parameterization scheme reduces the resulted wind speed and the significant wave height as a response to the increased aerodynamic drag over rough sea surfaces. Overall, WEW offers a more realistic representation of the momentum exchanges in the ocean wind-wave system and includes the effects of the resolved wave spectrum on the drag coefficient and its feedback on the momentum flux.

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Section: P Katsafados Et Al: a Fully Coupled Atmosphere-ocean Wave mentioning

confidence: 99%

Section: The Theoretical Backgroundmentioning

confidence: 99%

A fully coupled atmosphere–ocean wave modeling system for the Mediterranean Sea: interactions and sensitivity to the resolved scales and mechanisms

et al. 2016

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show abstract

“…The basic principle is to model waves as a function of wind inputs, wave-wave interactions, and dissipa- tion. The WAM is a third-generation system which has been used primarily to model deep water domains, although it can also be applied in shallow water domains [15,16]. The ECMWF WAM model is further described in Janssen [17] and Bidlot et al [18].…”

Section: Data Characteristicsmentioning

confidence: 99%

Probabilistic forecasting of the wave energy flux

Reikard¹,

Bidlot

2012

Applied Energy

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Wave energy will certainly have a significant role to play in the deployment of renewable energy generation capacities. As with wind and solar, probabilistic forecasts of wave power over horizons of a few hours to a few days are required for power system operation as well as trading in electricity markets. A methodology for the probabilistic forecasting of the wave energy flux is introduced, based on a log-Normal assumption for the shape of predictive densities. It uses meteorological forecasts (from the European Centre for Medium-range Weather forecasts -ECMWF) and local wave measurements as input. The parameters of the models involved are adaptively and recursively estimated. The methodology is evaluated for 13 locations around North-America over a period of 15 months. The issued probabilistic forecasts substantially outperform the various benchmarks considered, with improvements between 6 and 70% in terms of Continuous Rank Probability Score (CRPS), depending upon the test case and the lead time. It is finally shown that the log-Normal assumption can be seen as acceptable, even though it may be refined in the future.

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“…In this study we have used the wave model WAM, described by the WAMDI Group [1988] with a coupling to the atmospheric boundary layer following Janssen [1991]. This version of WAM, referred to as Cycle-4, was implemented on a 1.0 ø x 1.0 ø latitude-longitude grid that covers the northwest Atlantic extending from 25øN to 70øN and from 80øW to 15øW and includes 2318 water points.…”

Section: Wammentioning

confidence: 99%

The effect of assimilating ERS‐1 fast delivery wave data into the North Atlantic WAM model

Dunlap¹,

Olsen²,

Wilson³

et al. 1998

J. Geophys. Res.

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Abstract. The launch of the European ERS satellites has provided a new source of wave information that is particularly suitable for use in improving wave forecasts in the open ocean. We have implemented and tested a simple system for assimilating corrections to model wave fields produced by the WAM model, where the corrections are derived from inverted synthetic aperture radar (SAR) image spectra from ERS-1. Corrections are applied to significant wave height, mean period and direction for wave modes that are detectable in both the model and the SAR data. The system has been tested in a storm situation and in moderate conditions using buoy data and altimeter data, as well as SAR observations for verification. Overall, it is demonstrated that the net effect of assimilating SAR data is beneficial but very small. The small impact is due at least partly to relatively small spatial and temporal coverage of the SAR wave mode data. Locally larger impacts were found in the storm situation in individual cases where SAR observations were collocated with independent buoy observations. IntroductionUp until a few years ago, ocean wave models were run without the use of any wave observations. Model simulations of wave growth, propagation, and decay were obtained using marine winds as input, either as a series of analyses ("hindcast mode") or as forecast winds from an atmospheric model ("forecast mode"). Wave observations were not used for two reasons. First, wave models have been shown to simulate the wave field quite well if they are driven by a consistent highquality wind field [Graber et al., 1994]. Second, so few wave observations were available that they could not be expected to have a significant impact on regional or ocean basin scale wave simulations. With the launch of ERS-1 in July 1991 the spatial and temporal coverage of wave observations increased dramatically, making their use to initialize wave models operationally practical. ERS-1 (and recently ERS-2) wave observations are available in two forms, wave heights from the radar altimeter, and estimates of the two-dimensional (2-D) wave spectrum from the active microwave instrument (AMI) operating in synthetic aperture radar (SAR) mode. The latter offers the opportunity of obtaining real-time wave observations that are the most complete and consistent with the output of a wave model, an estimate of the two-dimensional spectral wave energy.The general purpose of data assimilation is to change a model's estimate of the state of its geophysical variables toward their true state, using information obtained from observations. Both model and data are assumed to contain errors, which must be accounted for in the assimilation procedure. With remotely sensed observations it is often the case that the geophysical variable is not directly observed; its values must be inferred or estimated. The raw SAR mode data from ERS-1•ASA Consulting Ltd., Halifax, Nova Scotia, Canada. . Variational assimilation will probably be the optimal methodology in wave assimilation as well, but it i...

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Quasi-linear Theory of Wind-Wave Generation Applied to Wave Forecasting

Cited by 789 publications

References 0 publications

A fully coupled atmosphere–ocean wave modeling system for the Mediterranean Sea: interactions and sensitivity to the resolved scales and mechanisms

A fully coupled atmosphere–ocean wave modeling system for the Mediterranean Sea: interactions and sensitivity to the resolved scales and mechanisms

Probabilistic forecasting of the wave energy flux

The effect of assimilating ERS‐1 fast delivery wave data into the North Atlantic WAM model

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