[Paper & Dataset] Verification against in-situ observations forData-Driven Weather Prediction
jacobbieker opened this issue · 3 comments
Arxiv/Blog/Paper Link
https://arxiv.org/pdf/2305.00048.pdf
Detailed Description
Dataset is available through Huggingface here: https://huggingface.co/datasets/excarta/madis2020
This paper goes more into verifying how well data driven model perform, specifically against real observations as well, compared to the common benchmark of ERA5 reanalysis. The data in the dataset is from MADIS.
Context
It would be good to compare what these models can do against observations.
I see a very strange results in this paper: the errors is not increase respect to lead time
The good idea is using the NOAA-ISD dataset for this verification - it is globally and contains the quality control checks
https://www.ncei.noaa.gov/data/global-hourly/
If this issue is still open, I would like to take it on. I have perused the paper and what I understand is that the methods evaluation of DDWPs tests how well the model can replicate the data it has ingested. However, the real
world has unforeseen circumstances and thus, what is required here is to evaluate DDWPs with real-world scenarios.
Yes, it is! And yeah, happy to have you take it!