Data and information management

The renewed Sava Forecasting and Warning System will not only ensure insight into flood risks but also provide the region with important information during hydrological droughts particularly relevant to the inland navigation along the Sava River basin.

Damage surveys provide crucial information about when, where and how strong U.S. tornadoes are to better understand disaster risk

Scientists have developed a new tool for improved wildfire prediction using machine learning (ML). The collection and integration of higher-quality data can significantly improve the accuracy and reliability of wildfire predictions.

New research led by CMCC researcher Marie-Lou Bachèlery, harnesses the power of artificial intelligence (AI) to predict extreme Atlantic Niño and Benguela Niño events up to 3 months in advance.

Mutual insurer MAIF (Mutuelle assurance des Instituteurs de France) is strengthening its climate risk modeling capabilities with access to a comprehensive suite of Moody's high-definition risk models.

HiFlo-DAT compiles 175 years of flood data in Kullu, India, improving DRR through historic analysis. It reveals monsoon-driven flood trends, key impact zones, and vulnerable groups, promoting data-based planning across the Himalayan region.

Nonprofit introduces the Strong Homes Scale to help homeowners evaluate resilience and explore customized strengthening options for six different disaster types.

Yokahu, a leading innovator in parametric insurance, today announced the launch of cat-risk.com, the first independent, many-to-many parametric exchange for the London re/insurance market.