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Data assimilation experiments using diffusive back-and-forth nudging for the NEMO ocean model

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Academic year: 2021

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Figure 1 shows the global error, R err , for different win- win-dow sizes. The errors grow linearly with the winwin-dow size for all variables
Figure 3. Sea level errors after one forward–backward model inte- inte-gration. The time window is 10 days.
Figure 5. Figure shows the gradient of the cost function after each inner iteration (left) and the reduction of the relative error for zonal velocity for the DBFN experiment (right).
Figure 7. Forecast rms errors on SSH (top panel), zonal velocity (middle panel) and temperature (bottom panel) from DBFN, 4Dvar, ONDG (Nudg_dir) and the free run
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