I would like to know if the fine-tuning process necessarily requires ERA5 data. Can it be done if I only use local area surface data for the fine-tuning?
Open
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 1k
- Forks
- 174
- PR merge metrics
- No merged PRs in 30d
Description
I want to leverage the capabilities of the Aurora model to perform end-to-end reasoning for my local data.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue does not name files, tests, or an entry point. Start by locating Aurora's fine-tuning workflow and checking where ERA5 data requirements are enforced; determine whether local-area surface data alone is supported and document the required changes or constraints.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100