Latest news
Harnessing the Power of AI in Climate Science: Opportunities, Risks, and the Road Ahead
May 12, 2025Artificial Intelligence (AI) is rapidly transforming many sectors, and climate science is no exception. From improving short-term weather forecasts to enabling long-range climate projections, AI is opening new pathways for understanding and responding to climate extremes. Yet, alongside this potential...
Unlocking Precision: How Hybrid Hydrological Models Transform Streamflow Predictions
May 2, 2025As the impacts of climate change become increasingly pronounced, accurately predicting water flux dynamics is more critical than ever. Traditional hydrological models, while foundational to our understanding of water resources, often face limitations when dealing with complex, non-linear hydrometeorological processes,...
When the River Runs Dry: Rethinking Drought Through Nature’s Lens
April 14, 2025A new global review led by Celia Ramos-Sánchez and colleagues raises critical concerns about how freshwater ecosystems are addressed in drought risk management. The study, published in Environmental Research Letters, analyzed 26 drought management instruments across 25 countries, revealing a...
CLINT Webinar series
Video
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.
