What's Happening?
The development of operational multi-risk impact-based forecasting and warning (IbFW) systems faces significant challenges due to the complexity of integrating multiple hazards, such as cascading or compound events. These systems require sophisticated
modeling, dynamic data on exposure and vulnerability, and substantial computational capacity. The scarcity of comprehensive training data, particularly for historical multi-risk impacts, limits the effectiveness of AI-based systems. Despite these challenges, AI offers promising advances in weather forecasting, as demonstrated by the European Centre for Medium-Range Weather Forecasts' data-driven AI Forecasting System.
Why It's Important?
The ability to accurately forecast multi-risk events is crucial for disaster risk reduction and management. Effective IbFW systems can provide more accurate risk assessments and warnings, potentially saving lives and reducing economic losses. The integration of multi-risk perspectives into these systems is essential, as multi-hazard events account for a significant portion of global economic losses. Developing these systems could enhance preparedness and response strategies, particularly in regions prone to complex and interacting hazards.
