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Model
This deep learning model, based on the Adaptive Fourier Neural Operator framework (AFNO), predicts 6-hour maximum 3-second wind gusts given 20 atmospheric variables plus invariants.
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| Field | Response |
|---|---|
| Intended Application & Domain: | Weather, Energy Forecasting |
| Model Type: | Adaptive Fourier Neural Operator (AFNO) |
| Intended User: | Weather and energy scientists or practitioners accelerating predictions using AI. |
| Output: | Tensor (1 variable - maximum 3-second wind speed gust). |
| Describe how the model works: | AFNO decodes input variables into a latent space and learns coupling with the output variable - 3-meter maximum wind gust. |
| Name the adversely impacted groups this has been tested to deliver comparable outcomes regardless of: | N/A |
| Technical Limitations: | The model may perform poorly for systems that are not similar to those in the training data, namely for rare weather phenomena or weather behavior outside of the 1980-2016 training dataset. There is no mechanism to enforce physical consistency for predictions. |
| Verified to have met prescribed NVIDIA quality standards: | Yes |
| Performance Metrics: | Root Mean Square Error (RMSE), Accuracy (ACC), and Bias (mean error). |
| Potential Known Risks: | This model may inaccurately predict wind gusts given technical limitations noted above. |
| Licensing: | NVIDIA Community Model License |