The US Navy Coupled Ocean-Wave Prediction System

Oceanography, 2014

Geoscientific Model Development Discussions

This paper describes the implementation of a coupling between a three-dimensional ocean general circulation model (NEMO) and a wave model (WW3) to represent the interactions of the upper oceanic flow dynamics with surface waves. The focus is on the impact of such coupling on upper-ocean properties (temperature and currents) and mixed-layer depths (MLD) at global eddying scales. A generic coupling interface has been developed and the NEMO governing equations and boundary conditions have been adapted to include wave-induced terms following the approach of McWilliams et al. (2004) and Ardhuin et al. (2008). In particular, the contributions of Stokes-Coriolis, Vortex and surface pressure forces have been implemented on top of the necessary modifications of the tracer/continuity equation and turbulent closure scheme (a 1-equation TKE closure here). To assess the new developments, we perform a set of sensitivity experiments with a global oceanic configuration at 1/4 o resolution coupled with a wave model configured at 1/2 o resolution. Numerical simulations show a global increase of wind-stress due to the interaction with waves (via the Charnock coefficient) particularly at high latitudes, resulting in increased surface currents. The modifications brought to the TKE closure scheme and the inclusion of a parameterization for Langmuir turbulence lead to a significant increase of the mixing thus helping to deepen the MLD. This deepening is mainly located in the Southern Hemisphere and results in reduced sea-surface currents and temperatures. 1 Introduction An accurate representation of ocean surface waves has long been recognized as essential for a wide range of applications ranging from marine meteorology to ocean and coastal engineering. Waves also play an important role in the short-term forecasting of extratropical and tropical cyclones by regulating sea-surface roughness (

Proceedings of OCEANS 2005 MTS/IEEE, 2005

Large vessels such as the Panamax LMSR classes, the smaller Flickertail state and Cape D classes, the post Panamax container ships and MPF(F) all have natural periods in heave, pitch and roll that are out in the 12 to 18 second range. When a swell component is present, large amplitude motions occur. They are relatively slow in terms of velocity and accelerations but of relatively large amplitude compared to when these large vessels are excited but shorter period waves of the same height.

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Weather and Forecasting, 2002

The monthly exchange of ocean wave model data has successfully been taking place among five operational weather centers. The data are compared with observations obtained from moored buoys and platforms. The analysis of 3 yr of data has helped to quantify the global and regional skills, strengths, and weaknesses of the different ocean wave forecasting systems. Since the quality of ocean wave forecasts is intrinsically linked to the quality of the forcing wind fields, it is not surprising to find that the center with the lowest wind speed errors also has the lowest wave height errors. The benefit of using a third-generation Wave Model (WAM), for example, is not so tangible in terms of wave height statistics but it is definitively evident in terms of peak periods. Even though WAM has proved to be well suited for global wave forecasting, it is also clear that research is still needed to reduce the model tendency to underpredict some storms when it is forced by operational global wind fields. It appeared that assimilating altimeter wave heights has a positive impact on the model performance. It is also argued that the height of the wind speed observations should be taken into account when assimilating the data or simply when evaluating model performance since it might otherwise introduce a systematic negative bias into the analysis. Last, this exchange of data should continue and possibly extend to other forecasting centers as a tool for model developers but also as a continuous reference for marine forecasters.

Ocean Dynamics, 2017

Following the 14th International Workshop on Wave Hindcasting and Forecasting and 5th Coastal Hazards Symposium in November 2014 in Key West, Florida, a topical collection has appeared in recent issues of Ocean Dynamics. Here, we give a brief overview of the 16 papers published in this topical collection as well as an overview of the widening scope of the conference in recent years. A general trend in the field has been towards closer integration between the wave and ocean modelling communities. This is also seen in this topical collection, with several papers exploring the interaction between surface waves and mixed layer dynamics and sea ice.

SafeThessaloniki 2022 - 9th International Conference on Civil Protection & New Technologies, 2022

This paper presents a new Operational Forecast Platform (OFP) for prevailing sea conditions at very important ports worldwide (project Accu-Waves; http://accuwaves.eu/). The OFP produces reliable, high-resolution, predictions of wave characteristics in and around harboured coastal areas. Its goals are to support safer navigation, assist vessel approaching, enhance management of towing services, and bolster secure ship manoeuvring in busy ports around the globe. Hence, port managers and authorities can be assisted in timely predicting possible port downtime. Accu-Waves OFP is based on integrated, high-resolution, spectral wave modelling over the continental shelf and in coastal areas that incorporates data from global-and regional-scale, open-sea, wave forecasts as boundary conditions. The models' setup, coupling, validation, and application are presented and discussed, concerning 50 selected areas near and inside significant port basins. The platform provides three-day forecasts at three-hourly intervals. Exceptional cases of very high waves and rough sea conditions in representative ports are discussed reflecting the performance of the prediction system.

2005