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| one publication added to basket [211134] |
Estimating the Lagrangian residual circulation in the Iroise Sea
Muller, H.; Blanke, B.; Dumas, F.; Lekien, F.; Mariette, V. (2009). Estimating the Lagrangian residual circulation in the Iroise Sea. J. Mar. Syst. 78: S17-S36. dx.doi.org/10.1016/j.jmarsys.2009.01.008
In: Journal of Marine Systems. Elsevier: Tokyo; Oxford; New York; Amsterdam. ISSN 0924-7963; e-ISSN 1879-1573
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| Trefwoord |
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| Author keywords |
Iroise Sea; Lagrangian residual circulation; Regional ocean modeling; |
| Auteurs | | Top |
- Muller, H.
- Blanke, B.
- Dumas, F.
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| Abstract |
In this study, the Lagrangian residual circulation in the Iroise Sea is estimated by a numerical method where the trajectories of the particles released in any given velocity field are calculated by a diagnostic tool. From their knowledge, the residual Lagrangian currents are computed over a whole number of M2 tidal cycles. The Lagrangian residual circulation is mapped from sea surface currents measured by HF radars and from the surface currents computed with the Model for Applications at Regional Scales (MARS), a regional 3D ocean model forced, here, by the Weather Research and Forecasting (WRF) regional meteorological model. In order to overcome inconvenient space- and time-variations in radar coverage, the measured radar data are interpolated, extrapolated and filtered by Open-Boundary Modal Analysis (OMA). The estimated Lagrangian residual currents are compared with real drifts derived from subsurface and surface Lagrangian drifters released in the Iroise Sea in 2005 and 2007. The residual currents are analysed in the light of the physical processes (tides, atmospheric forcing and density-driven currents) known to govern long-term transport in the Iroise Sea. The similarities between drifter trajectories and the Lagrangian residual circulation inferred from either HF radar surface current measurements or modelled velocities confirm the interest of the methodological approach and make it a reasonable candidate for adaptation to the operational forecast of long-term transport. |
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