graph_weather

Graph_weather is an open-source software project hosted on GitHub, focusing on advanced weather forecasting using graph neural networks. It provides a PyTorch implementation of the methodology described in Ryan Keisler's 2022 paper, "Forecasting Global Weather with Graph Neural Networks" (arxiv.org/abs/2202.07575).

This project offers tools and models for researchers and developers interested in applying deep learning techniques to meteorological data. It facilitates the exploration and development of next-generation weather prediction systems, leveraging the power of graph structures to model complex atmospheric interactions and provide more accurate forecasts. The repository is a valuable resource for contributing to and utilizing cutting-edge climate modelling and atmospheric science research.