10-minute level multi-layer meteorological parameter forecast
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- Dominant language
- Python
- Stars
- 1k
- Forks
- 174
- PR merge metrics
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Description
Hi maintainers!
I’d like to know whether Aurora (or its flexible variant) can be fine-tuned to meet the following requirements:
Spatial resolution: 0.25° × 0.25°
Temporal resolution: 10 minutes
44 vertical levels (pressure or hybrid coordinates)
Predictands: 3-D temperature, specific humidity, and wind components (u, v).
Specific questions:
Does the architecture allow arbitrary numbers of vertical levels without a full re-training?
Are there recommended preprocessing scripts to re-grid ERA5/HRES to 0.25° / 10 min?
Any memory/compute estimates for fine-tuning on ~1 year of data at this spatio-temporal density?
Thanks in advance!
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
No files, tests, or entry points are named. Start by reviewing Aurora’s architecture and fine-tuning and data-preprocessing entry points to determine whether the requested vertical levels and spatio-temporal resolution are supported; done means answering the feasibility, preprocessing, and compute questions with concrete guidance.
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
- 18/100