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license: cdla-permissive-2.0 |
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tags: |
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- Pytorch |
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- Weather & Climate |
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- Time Series |
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- Foundation Model |
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- NASA |
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- IBM |
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- MERRA2 |
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Prithvi WxC is a 2.3 billion parameter model trained on 160 different variables from MERRA-2 data. It has been pretrained on both forecasting and masked |
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reconstruction objectives. I.e.~the model is capable of reconstructing atmospheric state from partial information as well as propagating state into the |
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future. The model takes data from two timestamps as input and generates a single, possibly future, timestamp as output. Currently Prithvi WxC comes in two flavors: |
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- (This model) `prithvi.wxc.2300m.v1` has been pretrained with a 50% masking ratio. The time delta between input timestamps is variable as is the forecast lead time. |
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During pretraining, the input delta was chosen from [-3, -6, -9, -12] hours while the forecast lead time was chosen from [0, 6, 12, 24] hours. We recommend using |
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`prithvi.wxc.2300m.v1` for generic use cases that do not focus on forecasting. |
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<b> Zero-shot reconstruction </b> |
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<div style="display: flex; justify-content: center;"> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6488f1d3e22a0081a561ec8f/ftaxww2youmdS8XER31RC.png" alt="Reconstruction" width="1024"/> |
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</div> |
