The US Navy Coupled Ocean-Wave Prediction System

Allard, Richard A; Rogers, W. Erick; Martin, Paul J.; Jensen, Tommy G.; Chu, Philip; Campbell, T. J.; Dykes, James D; Smith, T.; Choi, Jei-Kook; Gravois, Uriah

doi:10.5670/oceanog.2014.71

Cited by 32 publications

(12 citation statements)

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“…Numerous validation studies for the system components have been performed for atmosphere-ocean (Allard et al, 2010;Jensen et al, 2015), ocean-wave (Allard et al, 2012), and atmosphere-wave coupling (Chen et al 2014).…”

Section: The Sea: the Science Of Ocean Predictionmentioning

confidence: 99%

“…The ocean component is the Navy Coastal Ocean Model (NCOM) developed by the Naval Research Laboratory for regional and coastal ocean modeling (Martin 2000;Barron 2006;Allard et al 2014;Rowley et al 2014) of ocean temperature, salinity, currents, and sea surface height. The vertical grid levels in NCOM consist of a set number of terrainfollowing sigma levels from the surface down to a user-specified depth, with z-levels below.…”

Section: Appendixmentioning

confidence: 99%

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Coupled ocean-atmosphere forecasting at short and medium time scales

Pullen¹,

Allard²,

Seo³

et al. 2017

j mar res

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Recent technological advances over the past few decades have enabled the development of fully coupled atmosphere-ocean modeling prediction systems that are used today to support short-term (days to weeks) and medium-term (10-21 days) needs for both the operational and research communities. We overview the coupling framework, including model components and grid resolution considerations, as well as the coupling physics by examining heat fluxes between atmosphere and ocean, momentum transfer, and freshwater fluxes. These modeling systems can be run as fully coupled atmosphere-ocean and atmosphere-ocean-wave configurations. Examples of several modeling systems applied to complex coastal regions including Madeira Island, Adriatic Sea, Coastal California, Gulf of Mexico, Brazil, and the Maritime Continent are presented. In many of these studies, a variety of field campaigns have contributed to a better understanding of the underlying physics associated with the atmosphere-ocean feedbacks. Examples of improvements in predictive skill when run in coupled mode versus standalone are shown. Coupled model challenges such as model initialization, data assimilation, and earth system prediction are discussed.

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Section: The Sea: the Science Of Ocean Predictionmentioning

confidence: 99%

Section: Appendixmentioning

confidence: 99%

Coupled ocean-atmosphere forecasting at short and medium time scales

Pullen¹,

Allard²,

Seo³

et al. 2017

j mar res

Self Cite

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“…Because of the strengths and weaknesses of each approach, research continues into physical modeling, data‐driven modeling [including the use of artificial neural networks (ANNs) and comparison with autoregression or Kalman Filters and hybrid models . However, these studies use standard measures of model accuracy such as RMSE, without considering the nature of scheduling offshore wind farm access.…”

Section: Wave Forecasting State Of the Artmentioning

confidence: 99%

An economic impact metric for evaluating wave height forecasters for offshore wind maintenance access

et al. 2015

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This paper demonstrates that wave height forecasters chosen on statistical quality metrics result in sub-optimal decision support for offshore wind farm maintenance. Offshore access is constrained by wave height, but the majority of approaches to evaluating the effectiveness of a wave height forecaster utilize overall accuracy or error rates. This paper introduces a new metric more appropriate to the wind industry, which considers the economic impact of an incorrect forecast above or below critical wave height boundaries. The paper describes a process for constructing a value criteria where the implications between forecasting error and economic consequences are explicated in terms of opportunity costs and realized maintenance costs. A comparison between nine forecasting techniques for modeling and predicting wave heights based on historical data, including an ensemble aggregator, is described demonstrating that the performance ranking of forecasters is sensitive to the evaluation criteria. The results highlight the importance of appropriate metrics for wave height prediction specific to the wind industry, and the limitations of current models that minimize a metric that does not support decision making. With improved ability to forecast weather windows, maintenance scheduling is subject to less uncertainty, hence reducing costs related to vessel dispatch, and lost energy due to downtime

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“…Another recent effort is based on deploying a fully coupled ocean/air/wave modelling system within the Earth System Modelling Framework (ESMF) to complete the US Navy's COAMPS, a globally relocatable modelling system designed for operational time (days) and space (~1-10 km) scales (Allard et al 2014). Test cases with the wave model component are being completed as the final phase of transition to operations.…”

Section: Examples Of Coupled Coastal Systemsmentioning

confidence: 99%