README.md

metadata

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.

Zero-shot reconstruction