The six-hourly averaged current fields, derived by ROMS and used in the LPTM to simulate the movement of the drifting buoy, have demonstrated to be underestimated.
This is the result of the aforementioned underestimation of the NCEP wind data, compared to those registered by the Gascony station (1.20–1.25 times higher).
Calibration of these NCEP wind data using this information, to estimate new current fields by ROMS, has resulted in high correlation between the LPTM output and the locations of the tracked buoy (Figs. 6 and 7).
The figures show the trajectory followed by the drifting buoy and that predicted by the LPTM (Fig. 6), together with location errors in the trajectories (in the X and Yaxes, and the total error) during 26 days from January 1st 2003 (Fig. 7).
The errors were within the ±40 km, with some variations likely to be related to wave effects on the buoy movements.
From the results obtained, the wind influence on oil dispersion at the sea surface is high.
Therefore, a more accurate representation of wind input to the hydrodynamic model will result in an improved forecast of surface current patterns and oil dispersion trajectories.
The six-hourly averaged current fields, derived by ROMS and used in the LPTM to simulate the movement of the drifting buoy, have demonstrated to be underestimated.
This is the result of the aforementioned underestimation of the NCEP wind data, compared to those registered by the Gascony station (1.20–1.25 times higher).
Calibration of these NCEP wind data using this information, to estimate new current fields by ROMS, has resulted in high correlation between the LPTM output and the locations of the tracked buoy (Figs. 6 and 7).
The figures show the trajectory followed by the drifting buoy and that predicted by the LPTM (Fig. 6), together with location errors in the trajectories (in the X and Yaxes, and the total error) during 26 days from January 1st 2003 (Fig. 7).
The errors were within the ±40 km, with some variations likely to be related to wave effects on the buoy movements.
From the results obtained, the wind influence on oil dispersion at the sea surface is high.
Therefore, a more accurate representation of wind input to the hydrodynamic model will result in an improved forecast of surface current patterns and oil dispersion trajectories.
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