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- Make observations sparse (50% grid coverage) instead of 100% dense, demonstrating 4D-Var's ability to propagate information via dynamics - Extend assimilation window from 20 steps (30min) to 100 steps (2.5h) - Add observation mask visualization - Increase optimizer maxiter from 200 to 500 for better convergence - Update cost function with proper sparse observation operator H - Tone down ECMWF comparison in summary; add honest discussion of simplifications (diagonal B, small grid, single outer loop) - Clear stale outputs https://claude.ai/code/session_015hk7HYttY5wQ7zvkqix1Fy
The pressure field has a ~50000 mean, making spatial variations (~1-10) invisible when plotting absolute values on a shared colorscale. Now plots forecast errors (forecast - truth) which clearly show where and how much the analysis forecast improves over the background forecast. Also extends forecast to 2x the assimilation window to test whether the improved IC retains its advantage beyond the observation period. https://claude.ai/code/session_015hk7HYttY5wQ7zvkqix1Fy
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