Making early warning systems (EWS) multi-hazard:
- Implementing a multi-hazard approach (marine submersion, flash floods, landslides storms, tropical cyclones, earthquakes and tsunamis for coastal regions, liquefaction, etc.) also from an observational network perspective and given that many hazards are consecutive/cascading/compound events and have spatio-temporal dependencies;
- Harmonising multi-hazard impact estimations coming from hazard-specific algorithms and analyses; Multi-hazard EWS (MHEWS) for man-made (air quality, atmospheric accidental pollution, oil spills), nat-tech and biological hazards, agriculture-related and health-related hazards (looking at the correlations between food chain and health, from climate to short term);
- Capturing cascading effects of a hazard (e.g. volcanic eruption that provokes underwater landslides that can trigger tsunamis) vs. simultaneous hazards or all hazards vs. multiple hazards;
- Considering different time scales from real time to a seasonal perspective (tsunami warnings vs El Niño-la Niña SOPs);
- Estimating the reduction or increase of vulnerability to a hazard caused by a prior hazard/disaster event; and
- Making hazard-specific EWS interoperable and integrating them to become a reliable MHEWS.