Leonardo Innovation Award 2018: two CMCC PhD students among the winners

Third Place PhD students award to Paola Vesco and Gabriele Accarino with a project that explores the predictive potential offered by artificial intelligence tools to forecast future migration flows while identifying the most probable countries of origin and arrival in the medium-to-long term […]

Machine learning and cloud process parameterization for weather and climate models

It well suited for problems which have a complex structure that we don’t understand well, but about which we have huge amounts of information. This is the case, for example, of cumulus cloud systems for weather and climate models. Prof. Christopher S. Bretherton, University of Washington, USA, explored this issue in a CMCC webinar for the development of new parameterizations of cloud processes for climate models. Watch the video […]