Machine learning for weather predictions at ECMWF

P. Dueben, ECMWF (UK)

Abstract: The talk outlined how machine learning, and in particular deep learning could help to improve weather predictions in the coming years and presented an overview of the work on machine learning methods that is ongoing at the European Centre for Medium-Range Weather Forecasts. Weather prediction requires modelling the Earth System -- a huge system that consists of many individual components and shows chaotic behaviour for which conventional tools are often struggling to provide satisfying results. On the other hand, a huge amount of data is available from both observations and modelling. Therefore, a large number of machine learning applications are currently tested in order to improve the different components across the workflow of numerical weather predictions. However, whether these approaches will succeed is still unclear as there are also a number of challenges for the application of machine learning tools in weather predictions that were discussed in the talk.