In this study, scientists wanted to find a cheaper and faster way to predict regional climate patterns. They used a type of artificial intelligence called deep learning to create models that imitate how a high-resolution climate model works. By comparing two different training methods, they found that teaching the model with global climate data alone led to more accurate predictions compared to using a mix of regional and global data. This means that these machine learning models can quickly and effectively predict climate patterns in a specific area without running complex climate simulations, saving time and resources.