Questions on CAMS experiments
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question
- Dominant language
- Python
- Stars
- 1k
- Forks
- 174
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Description
Hi authors and @wesselb!
It is great to see such a powerful foundation model for air quality. Thank you for making the codebase available. I had a few questions about the CAMS experiments.
- In Figure 2 (Aurora outperforms operational CAMS across many targets) of the paper, what was the ground truth to compute the RMSE of CAMS and Aurora and show that Aurora has, at best, 30% better RMSE? For example, the Integrated Surface Database (ISD) was used as the ground truth for meteorology.
- Do you have more insights on using or not using emission inventory as input to Aurora? Did you do any small/large scale experiments with/without emission inventory as an input and know whether it is useful? The question is more from an ML point of view on intuitions about the usefulness of emission inventory.
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 implementation files or tests are named. Start by reviewing Figure 2 of the paper and the stated CAMS, Aurora, and Integrated Surface Database methodology, then investigate the discussion of emission inventory inputs; done means documenting authoritative answers to both experimental questions.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- machine-learning, python
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100