| one publication added to basket [211444] | Acoustic monitoring of the Ushant Front: a feasibility study
Carriere, O.; Hermand, J.P.; Stephan, Y. (2009). Acoustic monitoring of the Ushant Front: a feasibility study, in: IEEE (Ed.) Oceans '09 IEEE Bremen. Balancing Technology With Future Needs, 11-14 May 2009, Bremen, Germany. Oceans (New York), : pp. 238-242
In: IEEE (Ed.) (2009). Oceans '09 IEEE Bremen. Balancing Technology With Future Needs, 11-14 May 2009, Bremen, Germany. Oceans (New York). IEEE: New York. ISBN 978-1-4244-2522-8. , meer
In: Oceans (New York). IEEE: New York. ISSN 0197-7385, meer
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| Auteurs | | Top |
- Carriere, O., meer
- Hermand, J.P., meer
- Stephan, Y.
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| Abstract |
Oceanic modeling and prediction are highly dependent on the availability of satellite remote sensing and hydrographic in situ measurements to provide reliable and accurate results. In coastal environments the data assimilation is a difficult problem due to the lack of data, the strong coupling between state variables and forcing and the frequent model failures encountered in the modeling. In particular, the scarcity of satellite measurements due to cloud cover makes the operational data assimilation an hard task. Acoustic tomography data can provide valuable environmental informations to complete the standard data set, on temporal and spatial scales suitable to a regional circulation model. This work presents a feasibility test of acoustic data assimilation in a basic feature model of the Ushant thermal front, west off Brittany. The proposed scheme considers the regular measurements of full-field acoustic data on a vertical array of receivers that are assimilated in the feature front model to continuously track time-evolving front parameters. The assimilation scheme is based on Kalman filtering. Nonlinear extensions of Kalman filters are required to deal with the nonlinearity between the front parameters and the acoustic measurements. Simulation results based on realistic environmental scenarios show that the developed scheme is able to track temporally the main parameters of the front. |
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