H2020 PROJECT USING ARTIFICIAL INTELLIGENCE TO PROCESS CLIMATE DATASETS IS LAUNCHED
Reducing the impact of extreme climate events, identifying adaptation and mitigation strategies and managing the risks associated with such events is a challenge: climate services, which today can benefit from an incomparable amount of data, are particularly important in supporting strategic decisions.
The CLINT project - CLimate INTelligence, which has just been launched and is funded by the Horizon 2020 programme, aims to provide a tool to better harness the potential of this data. The main objective is the development of an artificial intelligence framework based on machine learning techniques and algorithms capable of processing large climate datasets in order to support climatological studies in the tracking, causal analysis and classification of extreme events such as tropical cyclones, heat waves, tropical nights and extreme droughts, but also of compound events and competing extremes.
Specifically, the framework will support the identification of spatial-temporal patterns and evolutionary dynamics of climatological fields associated with extreme events; the physics-based validation of climate system cause-effect relationships discovered by machine learning algorithms; the quantification of past and future extreme events by greenhouse gas emissions and other man-made forces.
The framework will also study the impact of extreme events on different socio-economic sectors under historical, predicted and projected climate conditions, developing innovative and sectoral climate services powered by artificial intelligence. These services will be tested on different spatial scales, from pan-European – where they will support EU policies related to the water-energy-food nexus (Water-Energy-Food Nexus) – to local, in three different types of climate hotspots.
Lastly, the services that are developed within the project will be made operational according to the most advanced open data and software standards in terms of Climate Services Information Systems and Web Processing Services, as well as a demonstration prototype of some of these services, in order to facilitate the understanding of the project results by public and private research bodies.
The 48 month research project is coordinated by the Politecnico di Milano and led by Professor Andrea Castelletti of the Department of Electronics, Information and Bioengineering, as Scientific Coordinator.
This article was first published on July 21 by Politecnico di Milano.