Imagine having a high-definition weather map that doesn't just show today's rain, but explains exactly why a heatwave happened and predicts the next one years in advance. It works like a digital detective, combining massive satellite archives with smart AI to spot patterns the human eye misses. This helps us understand if a specific summer extreme was a fluke or a new trend.
Current climate models often fail to predict regional extremes, leaving businesses and cities unable to prepare for specific, high-impact weather events. This gap creates financial risk and inefficient adaptation strategies.
A prototype operational capability for climate attribution and prediction, including ML-reconstructed temperature datasets and an Open Science Platform for large-scale data analysis.
If you are a crop insurance provider dealing with unpredictable summer heatwaves — this project developed a prototype operational capability for integrated attribution and prediction that allows for more accurate risk pricing based on regional climate extremes.
If you are a grid operator dealing with peak load surges during extreme heat — this project developed tools to analyze large data sets and ML-reconstructed temperature datasets that help forecast long-term infrastructure needs.
If you are a municipal infrastructure firm dealing with urban heat island effects — this project developed a way to quantify mechanisms governing regional climatic changes that informs targeted climate adaptation strategies.
Based on available project data, no pricing is mentioned as the project focuses on an Open Science Platform and peer-reviewed literature.
The project is developing a prototype operational capability, meaning it is moving toward scale but is not yet a fully commercial product.
Based on available project data, the project emphasizes an Open Science Platform and making results available for IPCC reports, suggesting an open-access model.
It develops tools to analyze large data sets hosted in different repositories across institutions, facilitating the use of high-resolution climate models and Earth Observations.
The project runs from 2024-04-01 to 2028-03-31, with early outcomes already appearing in the first 18 months.
The consortium is heavily weighted toward research and academia, with 6 universities and 7 research organizations. Industrial participation is low at 7% (1 SME), indicating that the primary goal is scientific discovery and tool creation rather than immediate commercial productization. The coordination by the Barcelona Supercomputing Center suggests a high capacity for handling the 'massive data assets' required for the project.
Contact the Barcelona Supercomputing Center (BSC) regarding the Open Science Platform.
Contact us to find out how to integrate these climate prediction prototypes into your risk management software.
