This event takes part in the context of the IYBSSD2022.

Climate extreme are the source of most of the climate related risks that can affect society and ecosystem. The machine learning techniques could help the more traditional dynamical and statistical methods to detect them, attribute the extremes to global warming and to have a more accurate future projection.

The ability to correctly communicate how global warming is connected with changes in extremes and the role of machine learning in this  is of crucial importance for the society for developing and planning mitigation and adaptation capacity.

Speakers at the event will be:

Robert Vautard, Institute Pierre-Simon Laplace, Paris, France and Dim Coumou, Vrije Universiteit, Amsterdam, Netherlands.

Prof. Vautard is a meteorologist and climatologist who focuses on the phenomenon of atmospheric blocking. He progressed his work in several directions: atmospheric dynamics and its predictability, the modelling of atmospheric pollution, regional climate modelling and the study of extreme weather-climate events.

Prof. Coumou's prime research interest is understanding how global warming affects the number and intensity of extreme weather events like heat waves, heavy rainfall, storms and persistent droughts. He uses a variety of methods, including advanced statistical analyses, climate models and novel machine learning techniques, to gain new insights.

To register in advance for this webinar:
https://zoom.us/webinar/register/WN_7EvqeZ09QgevrQhZ_Y0UUQ

To follow the streaming on Youtube ICTP:
https://youtu.be/A5R4IY18Rt0