ai weather models are faster but can they replace physics?
ai weather models from google and nvidia outpace traditional methods but face strict limitations in predictability and data dependence.
companies like google, nvidia, and microsoft have developed machine learning models for weather forecasting that offer significant speed advantages over traditional numerical methods by skipping complex physics calculations. despite these efficiency gains, the technology faces inherent limitations regarding data quality, generalization to unseen scenarios, and a lack of internal transparency. major weather centers are now exploring hybrid approaches to leverage these speed benefits while mitigating the risks of relying on black-box algorithms.