Summary of Prithvi Wxc: Foundation Model For Weather and Climate, by Johannes Schmude et al.

Prithvi WxC: Foundation Model for Weather and Climate

by Johannes Schmude, Sujit Roy, Will Trojak, Johannes Jakubik, Daniel Salles Civitarese, Shraddha Singh, Julian Kuehnert, Kumar Ankur, Aman Gupta, Christopher E Phillips, Romeo Kienzler, Daniela Szwarcman, Vishal Gaur, Rajat Shinde, Rohit Lal, Arlindo Da Silva, Jorge Luis Guevara Diaz, Anne Jones, Simon Pfreundschuh, Amy Lin, Aditi Sheshadri, Udaysankar Nair, Valentine Anantharaj, Hendrik Hamann, Campbell Watson, Manil Maskey, Tsengdar J Lee, Juan Bernabe Moreno, Rahul Ramachandran

First submitted to arxiv on: 20 Sep 2024

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Summary difficulty	Written by	Summary
High	Paper authors	High Difficulty Summary Read the original abstract here
Medium	GrooveSquid.com (original content)	Medium Difficulty Summary The research paper introduces Prithvi WxC, a large AI foundation model developed for mid-range forecasting and other weather-related tasks. The 2.3 billion parameter model employs an encoder-decoder architecture, incorporating transformer concepts to capture regional and global dependencies in input data. Trained on MERRA-2 data, the model combines masked reconstruction with forecasting objectives. The authors test Prithvi WxC on challenging downstream tasks like autoregressive rollout forecasting, downscaling, gravity wave flux parameterization, and extreme events estimation. The pre-trained model and associated fine-tuning workflows are publicly released via Hugging Face.
Low	GrooveSquid.com (original content)	Low Difficulty Summary The paper creates a large AI foundation model called Prithvi WxC to help with weather predictions and other tasks. It’s like a super powerful computer that can understand patterns in big datasets. The model is trained on old weather data and then tested on new, harder problems. It does really well at predicting things like future weather patterns and the movements of large waves in the air. The model’s code is now available for others to use and improve.