Ocean Weather Forecasting : An Integrated View of Oceanography

Jacques Verron

ISBN 10: 9048170060 / ISBN 13: 9789048170067

Editore: Springer Netherlands, 2010

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Druck auf Anfrage Neuware - Printed after ordering - Progress in a wide range of ocean research and applications depends upon the prompt and dependable availability of ocean information products. The field of physical oceanography has matured to a point where it is now conceivable to combine numerical models and observations via data assimilation in order to provide ocean prediction products on various spatial and time scales. As a result, many nations have begun large-scale efforts to provide routine products to the oceanographic community. The Global Ocean Data Assimilation Experiment (GODAE) provides a framework for these efforts, i. e. , a global system of observations, communications, modeling, and assimilation that will deliver regular, comprehensive information on the state of the oceans, in a way that will promote and engender wide utility and availability of this resource for maximum benefit to the community. The societal benefit will be an increased knowledge of the marine environment and ocean climate, predictive skills for societal, industrial, and commercial benefit and tactical and strategic advantage, as well as the provision of a comprehensive and integrated approach to the oceans. We therefore considered it timely, given the international context, to bring together leading scientists to summarize our present knowledge in ocean modeling, ocean observing systems, and data assimilation to present an integrated view of oceanography and to introduce young scientists to the current state of the field and to a wide range of applications.

Codice articolo 9789048170067

Dati bibliografici

• Titolo: Ocean Weather Forecasting : An Integrated View of Oceanography
• Editore: Springer Netherlands
• Data di pubblicazione: 2010
• Lingua: Inglese
• ISBN 10: 9048170060
• ISBN 13: 9789048170067
• Rilegatura: Taschenbuch
• Condizione: Neu

Descrizione articolo

Riassunto

This volume covers a wide range of topics and summarizes our present knowledge in ocean modeling, ocean observing systems, and data assimilation. The Global Ocean Data Assimilation Experiment (GODAE) provides a framework for these efforts: a global system of observations, communications, modeling, and assimilation that will deliver regular, comprehensive information on the state of the oceans, engendering wide utility and availability for maximum benefit to the community.

Dalla quarta di copertina

Ocean Weather Forecasting: An Integrated View of Oceanography

 

The field of physical oceanography has matured to a point where it is now conceivable to combine numerical models and observations via data assimilation in order to provide ocean prediction products on various spatial and time scales. As a result, many nations have begun large-scale efforts to provide routine products to the oceanographic community and started to develop operational oceanography systems. The Global Ocean Data Assimilation Experiment (GODAE) provides a framework for these efforts, i.e., a global system of observations, communications, modeling, and assimilation that will deliver regular, comprehensive information on the state of the oceans, in a way that will promote and engender wide utility and availability of this resource for maximum benefit to the community. The societal benefit of this experiment will be an increased knowledge of the marine environment and ocean climate, predictive skills for societal, industrial, and commercial benefit and tactical and strategic advantage, as well as the provision of a comprehensive and integrated approach to the oceans. We therefore considered it timely, given the international context, to bring together leading scientists, system developers, and application providers to present an integrated view of oceanography. The chapters collected in this volume cover a wide range of topics and summarize our present knowledge in ocean modeling, ocean observing systems, and data assimilation.