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Forecasting Made Accessible: AI Weather Models on Google Colab

Forecasting Made Accessible: AI Weather Models on Google Colab

Author: Keven Blackman

Dr. Jacob Radford (GSL/CIRA) has done an outstanding job creating a comprehensive series of Google Colab notebooks that enable users to run Artificial Intelligence (AI) Weather Prediction (AIWP) models using free resources. The flagship notebook, Running_AIWP.ipynb – Colab, provides an in-depth overview of AIWP models, including how to assess forecast accuracy and the overall run time of these models. Building on the foundational work of the European Centre for Medium-Range Weather Forecasts (ECMWF)’s ai-models Python package, Dr. Radford meticulously guides users through various models such as FourcastNet, Pangu-weather, Graphcast, and Aurora, offering an interactive tutorial to execute them on Google Colab. With an estimated run time of 70 minutes, this resource is a testament to Dr. Radford’s dedication to advancing innovative approaches in scalable AIWP.

In addition to providing a detailed introduction to each model, Dr. Radford has ensured that the notebook is user-friendly, making it accessible to both beginners and experienced practitioners in the field. The inclusion of practical examples and step-by-step instructions helps users to quickly grasp complex concepts and apply them effectively. Furthermore, Dr. Radford’s thoughtful integration of visualizations and performance metrics allows users to better understand the models’ capabilities and limitations.

The series also includes valuable insights into the computational requirements and optimization techniques that can enhance model performance. By leveraging free Google Colab resources, Dr. Radford has democratized access to advanced AI tools, enabling a wider audience to experiment with and benefit from cutting-edge weather prediction technology. His work not only facilitates learning and innovation but also fosters a collaborative spirit within the scientific and software communities.

EPIC is immensely grateful for Dr. Radford’s commitment and contribution to the field. His efforts exemplify the power of open-source collaboration and the impact it can have on advancing technology and knowledge sharing.