openclimatefix / openclimatefix/metnet
[Paper] Thunderstorm nowcasting with deep learning:a multi-hazard data fusion model
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- Dominant language
- Python
- Stars
- 305
- Forks
- 64
- Avg merge
- 5d 4h
- Merged PRs (30d)
- 1
Description
https://arxiv.org/pdf/2211.01001.pdf
Detailed Description
This paper describes ML models for predicting thunderstorms, taking in very similar data to MetNet, and dealing with certain modalities dropping out while still working, and gives probabilistic forecasts. Its forecasting 60min ahead at 5 minute intervals.
They did find the satellite data and radar were the most important inputs to the model:
Context
This seems like its trying to do a similar thing to MetNet/MetNet-2, with similar inputs, so might be helpful with expanding MetNet or adding it as a new option.
Possible Implementation
Code: https://github.com/MeteoSwiss/c4dl-multi
Data: https://zenodo.org/record/6802292
Pretrained models: https://zenodo.org/record/7157986
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 paper and reviewing the MeteoSwiss/c4dl-multi code, Zenodo data, and pretrained models. The issue does not name a file, test, implementation scope, or acceptance criterion, so the first step would be defining whether this should expand MetNet or add a new option and what completion means.
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