Summer School

The CLINT Summer School offers a succinct education on sound research in the field of detectioncausation, and attribution of extreme events . It is open to all PhD students and researchers in any area of science or engineering at any level (junior or senior) who wish to learn and discuss recent advances in climate science, machine learning, impact, and climate services.

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Our mission

The main objective of CLINT is the development of an Artificial Intelligence framework composed of Machine Learning techniques and algorithms to process big climate datasets for improving Climate Science in the detection, causation, and attribution of Extreme Events (EEs), namely tropical cyclones, heatwaves and warm nights, droughts, and floods. The CLINT AI framework will also cover the quantification of the EE impacts on a variety of socio-economic sectors under historical, forecasted, and projected climate conditions, and across different spatial scales (from European to local), ultimately developing innovative and sectorial AI-enhanced Climate Services. Finally, these services will be operationalized into Web Processing Services, according to the most advanced open data and software standards by Climate Services Information Systems, and into a Demonstrator to facilitate the uptake of project results by public and private entities for research and Climate Services development.

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