Data and Climate Modelling (Data & Sustainability, Episode 2)

Following the remarkable success of our inaugural event in the “Data and Sustainability” series, BCN Analytics is thrilled to present the topic of our next session: “Data and Climate Modelling”.

The goal of this series of events is to encourage prestigious researchers and industry leaders to inspire our community's passion for forging a sustainable future. Through talks and discussions, they will explore the transformative potential of data-driven solutions for a more sustainable world, spanning topics such as decarbonization, predictive climate modelling, the blue economy, and beyond.

The first talk of the afternoon will be given by Francisco Doblas-Reyes and Rachel Lowe, from the Barcelona Supercomputing Center. They will cover how the BSC is using data and computation to make climate projections based on different emission scenarios.

In the second talk, Ignacio Villanueva from RavenWits will explain how Deep Learning's expansion into weather prediction will not only popularize and enhance the forecasting of weather-related variables but also extend to improving predictions for renewable energy production.

Finally Ferran Alet, Research Scientist at Google DeepMind, will show that GNNs trained on large-scale dataset can predict global weather forecasting at a state-of-the-art level, improving on physics-based models that have been developed for decades. Predictions translate to real world impact like better extreme temperature predictions as well as better.

Agenda:

• Climate prediction at Barcelona Supercomputer Center (Francisco Doblas Reyes, Rachel Lowe)
• Deep Learning in meteorology-related variables prediction (Ignacio Villanueva)
• Graph Neural Networks for skilfull weather prediction (Ferran Alet)

➡️ Access Control (IMPORTANT!)

• 🛂 The security access control requires an attendee list (full name) and a means of identification (DNI, NIE, passport) otherwise you will be removed from the list.