---
license: cdla-permissive-2.0
tags:
- Pytorch
- Weather & Climate
- Time Series
- Foundation Model
- NASA
- IBM
- MERRA2
---

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
reconstruction objectives. I.e.~the model is capable of reconstructing atmospheric state from partial information as well as propagating state into the
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:
- (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.
  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
  `prithvi.wxc.2300m.v1` for generic use cases that do not focus on forecasting.

<div style="display: flex; justify-content: center;">
 <b> Zero-shot reconstruction</b>
<img src="https://cdn-uploads.huggingface.co/production/uploads/6488f1d3e22a0081a561ec8f/ftaxww2youmdS8XER31RC.png" alt="Reconstruction" width="1024"/>
</div>