TerraDT develops new Digital Twin Components (DTCs) for land ice, sea ice, aerosols and the land surface, together with impact models that translate climate information into actionable knowledge for decision making. A central feature of TerraDT's approach is a modular, generic coupling interface that allows physics-based model components to be complemented, and in some cases replaced, by emulators built using artificial intelligence (AI) and machine learning (ML). Such ML-based emulators can reproduce the behaviour of computationally demanding processes at a fraction of the cost, making it feasible to run the high-resolution, multi-decadal simulations required by DestinE's Climate Digital Twin.
Organised under TerraDT's communication and engagement activities, this webinar opens the TerraDT Tech Talks, a new strand within the project's public webinar programme dedicated specifically to the more technical aspects of TerraDT's work. It offers a first, accessible overview of how machine learning is applied across the project, from the construction of high-resolution land-use datasets to the assessment of urban climate impacts, and looks ahead to a forthcoming in-person workshop in Ostrava, where these themes will be examined in greater technical depth.
| Time | Item | Speaker |
| Welcome and introduction: the role of machine learning in TerraDT | Devaraju Narayanappa, CSC |
11:10 -11:20
| Machine learning for urban impact assessment: carbon sequestration and climate extremes | Inês Girão, CoLAB +ATLANTIC |
| 11:20-11:30 | Constructing the high-resolution, time-varying land-use dataset with machine learning | Amirpasha Mozaffari, BSC |
| 11:30-11:40 | Looking ahead: machine learning for Earth system model coupling | Benjamin Rodenberg, DKRZ |
| 11:40-12:00 | Panel discussion with other EU-funded projects on machine learning and digital twin developments | Moderator: Maria Giuffrida, Trust-IT; panellists from other EU-funded projects (to be confirmed) |
| 12:00-12:15 | Questions and answers, closing remarks |
Devaraju Narayanappa
Technical coordinator of the TerraDT project. Climate scientist and experienced researcher with a demonstrated history of working in the research Institutions. Skilled in Ecosystem-Climate interactions, Climate Change, Mathematical Modeling, Large Data Analysis using Python.
Inês Girão
Geospatial Analyst at +ATLANTIC (Collaborative Laboratory for the Atlantic Ocean) with a background in geography. In TerraDT, Inês works on connecting km-scale climate simulations with local, city-level applications, helping planners and policymakers understand how climate change affects urban environments (e.g. heat stress, air quality, livability) and how to adapt effectively for a more resilient urban environment.
Maria Giuffrida
Maria Giuffrida is part of the TerraDT team at Trust-IT Services, where she co-leads stakeholder engagement, communication, and dissemination activities for the project. She holds an MSc in International Management from Bocconi University and a PhD in Management Engineering from Politecnico di Milano.
Within TerraDT, she plays a key role in shaping how the project engages with its stakeholders and communicates its results, ensuring that scientific developments are translated into clear, accessible, and impactful narratives for diverse audiences.
