openclimatefix / openclimatefix/metnet
[Paper] MetNet Global
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- Dominant language
- Python
- Stars
- 305
- Forks
- 64
- Avg merge
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Description
Arxiv/Blog/Paper Link
https://arxiv.org/pdf/2510.13050
Detailed Description
This is the global MetNet paper, using satellite imagery for 0.5km and 15 minutely precipitation forecasts globally, up to 12 hours.
There are a few interesting points in it. The main targets are CORRA precipitation from GPM, with auxiliary targets being precipitation radar outputs from Japan, Europe, and the US, as well as GPM IMERG Final precipitation estimates.
They use 7 geostationary satellites, the 3 EUMETSAT ones + GK-2A, Himawari9, GOES-19/GOES-18, and blend them into a single mosaic using satpy.
Similar to MetNet-2 on the lead time conditioning, as well as some other architectural tricks to save memory (cropping the feature maps for example as you go through the residual blocks)
Contributor guide
No contributing guide indexed for this repository
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
Start by reading the linked arXiv paper, then inspect the repository's current MetNet and MetNet-2 implementation. The issue does not name files, tests, a requested entry point, or acceptance criteria, so the intended change and definition of done need to be clarified before work begins.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100