Presenter: Christopher S. Bretherton – Professor – Departments of Atmospheric Science and Applied Mathematics – University of Washington – USA
Moderator: Giovanni Aloisio – Full Professor of Information Processing Systems at the Dept. of Innovation Engineering of the University of Salento – Lecce – Italy and member of CMCC Strategic Council

ABSTRACT:
Machine learning is well suited for problems which have a complex structure that we don’t understand well, but about which we have huge amounts of information. For global weather and climate models, cumulus cloud systems present such a problem. They produce most of the world’s rainfall.
They involve interactions between air motions, clouds, liquid and ice precipitation, all poorly resolved by a typical model horizontal grid spacing of 10-100 km, which we represent with uncertain ‘subgrid parameterizations’.
We can simulate these interactions well with a much finer model grid of 1-5 km that explicitly simulate individual cumulus clouds, but this is too computationally expensive for normal use in a climate model. This webinar explores machine learning for development of new parameterizations of cloud processes for climate models, based on large amounts of training data from 1-5 km models. Our goal is that such parameterizations be easier to develop, more consistent with observations, and more efficient than what we use now.

Chris Bretherton is an atmospheric scientist who studies cloud formation and turbulence and improves how they are simulated in global climate and weather forecast models. His research includes participating in field experiments and observational analyses, three-dimensional modeling of fluid flow in and around fields of clouds, and understanding how clouds will respond to and feedback on climate change. Computer code developed by his research group for simulating cloud formation by atmospheric turbulence is used in the two leading US climate models. He was a lead author of the Intergovernmental Panel on Climate Change Fifth Assessment Report in 2013, Chair of a 2012 National Academy report entitled A National Strategy for Advancing Climate Modeling, and a former director of the University of Washington Program on Climate Change.
In 2012, he received the Jule G. Charney Award, one of the two highest career awards of the American Meteorological Society (AMS), and he is the 2019 AMS Haurwitz Lecturer. He is a Fellow of the AMS and American Geophysical Union.

AGENDA:
03:00 pm – Welcome and intro – Giovanni Aloisio – CMCC
03:05 pm – Presenter’s talk – Chris Bretherton – University of Washington
03:35 pm – Q&A
03:50 pm – End of webinar

Working language: English

HOW TO PARTICIPATE:
The seminar will be broadcasted via Go-to-Webinar. Please, click on the following link for registration:
https://register.gotowebinar.com/register/2509161794872738051
After registering, you will receive a confirmation email containing information about joining the webinar.