Add DANRA tutorial notebook with pytest-nbmake

Description

Add a hello_world_danra.ipynb notebook to docs/notebooks/ providing a step-by-step guide for running a full model training using DANRA data. This improves onboarding and showcases neural-lam's capabilities.

Note: The COSMO equivalent has been split into a separate issue: #587

Stale PR: #202 (thank you @Jayant-kernel!) Current PR: #577 builds on top of #202

Proposed notebook contents

1. Install Neural-LAM with all dependencies (PDM + ipykernel)
2. Data loading and preprocessing using tests/datastore_examples/mllam/danra.example.yaml
3. Model configuration and HiLAM graph generation
4. Training on CPU (with --flags)
5. Evaluation and visualization using built-in maps and charts + wandb

Additional considerations

• Use a small subset of DANRA data for quick execution
• Include explanations for each step
• Highlight key parameters and their effects
• Provide tips for scaling to larger datasets