Using 1° resolution instead of 0.25°
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- Python
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Description
Hi Aurora team,
My lab has access to 1° ERA5 data, but Aurora requires 0.25° in its primary model. Would it be possible to pass this 1° data straight to Aurora, or must we use torch.nn.functional.interpolate(...)?
We are fine-tuning for MJO prediction, so 1° resolution is sufficient for us to calculate RMM indices.
Many thanks for your work!
Kieran
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First steps
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Research direction
Start by tracing Aurora's primary model input resolution and the torch.nn.functional.interpolate(...) path mentioned in the issue. Determine whether 1° ERA5 data can be passed directly while preserving the stated MJO/RMM use case; done should be a documented, tested decision about direct support or required preprocessing.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100