Please see the schedule below for more information.
The event will be held via Zoom. The link and joining instructions will be sent to all MPE-CDT staff and students. External participants please email firstname.lastname@example.org to register your interest for the event.
Date: Wednesday 10th February 2021 13:00 – 15:30
Key Speaker and Guests:
Peter Dueben (Royal Society Fellow, Research Department, Earth System Modelling Section, Numerical Methods Group)
Rosella Arcucci (Research Fellow at Data Science Institute. ICL)
So Takao (Research Assistant at Mathematics Department, ICL)
Programme Schedule :
13:00- 14:00 : Seminar Peter Dueben on “Machine Learning for Weather Predictions”
14:00- 14:10 : Introductions from new MPE PhD students
14:10 – 14:30 : Break
14:30- 15:30 – Panel on “The Future of Machine Learning for Environmental Modelling”: Peter Deuben, Rosella Arcucci, So Takao
Title: Machine Learning for Weather Predictions
Abstract: The talk outlines how machine learning, and in particular deep learning could help to improve weather predictions in the coming years and presents 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.