Ucla Researcher Develops A Python Library Called Climatelearn For Accessing State-of-the-art Climate Data And Machine Learning Models In A Standardized And Straightforward Way

Climate change has caused an increase in extreme weather events, and scientists use general circulation models (GCMs) to forecast the weather and climate in the future. However, these models require significant computational power and fine-tuning with a lot of training data. Machine learning techniques have proven to be useful in weather forecasting and spatial downscaling, as they can be analogous to a variety of computer vision tasks.