AI model in the real world - analysis of the operational performance of a high-resolution AI weather model for Iceland

The development of various AI models in recent years has been very promising; the models’ ability to train from reanalysis datasets and evaluate on various metrics opened the door for a variety of new applications. However, the real stress test of any new model is its operational performance - applying predictions to data that weren't available during the model development and assessing the model’s capabilities for predicting real-world scenarios previously unseen. 

In August 2025, we deployed our first high-resolution AI-based model for Iceland and it has been providing us with continuous predictions since then. Here we evaluate forecast skill against surface observations and benchmark against NWP models from the United Weather Centres (UWC) in Denmark and Iceland and our local operational NWP model for Iceland. We analyze the model’s strengths and weaknesses in predicting various weather events and discuss how these characteristics may influence the future model design.