Shape Mismatch Between Input Batch and Predicted Output
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- Dominant language
- Python
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Description
I noticed that when running Aurora with ERA5 at 0.25° (but also with HRES T0 at 0.1°), the shape of the input batch tensors is 721×1440 (or 1801×3600), while the shape of the predicted outputs is 720×1440 (or 1800×3600). It seems that the South Pole is missing, as the metadata containing the latitude coordinates does not include the latitude of the North Pole (lat = -90°). Perhaps I’m missing something, but I wonder: in what kind of grid should we consider the model’s predictions to be represented if we want to validate the prediction? Is it a grid that is staggered relative to the one specified in the latitude and longitude metadata? Thanks
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Research direction
No file or test is named. Reproduce the ERA5 0.25° and HRES T0 0.1° cases, compare input and output tensor shapes with the latitude metadata, and establish which grid represents predictions for validation; done means the pole omission and alignment are explained.
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Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100