Early Warning Systems (EWS) are one of the most effective tools for risk reduction and one of the most urgent measures to be implemented to limit damage to people and property, as the UN Secretary General himself recently explained during the celebration of World Meteorological Day (23 March 2022):
Today, one third of the world’s people, mainly in least developed countries and small island developing states, are still not covered by early warning systems. This is unacceptable, particularly with climate impacts sure to get even worse. Early warnings and action save lives. To that end, today I announce the United Nations will spearhead new action to ensure every person on Earth is protected by early warning systems within five years
The idea behind an Early Warning System is based on the ability to identify precursors capable of anticipating the event and its impacts, so that the affected population can be warned and appropriate mitigation actions can be activated. However, the forecasting and monitoring techniques currently in use are based on a few hazard indicators, and rarely provide a quantification of the impacts of the event. However, the forecasting and monitoring techniques currently in use are based on a few hazard indicators, and rarely provide a quantification of the impacts of the event.
The programme aims to develop complete operational chains for real-time observation and forecasting of the main weather-related hazards (floods, forest fires and droughts), starting from meteorological prediction and ending with the quantification of impacts.
With regard to flood risk, the programme refines the tools for two-dimensional hydraulic modelling, expanding them to consider not only flash-floods but also localised flooding events (pluvial flooding). It is also intended to integrate existing nowcasting tools into the forecast chain, possibly adapting them to the need for impact forecasting. The extension of the forecasting chain envisages the characterisation of the exposed areas not only in terms of their vulnerability, so as to allow the economic quantification of losses as well, but also in terms of their functionality, whose unavailability triggers dangerous cascading effects (e.g. food security, displacement, etc).
For forest fire risk, the transition from hazard to risk is tackled: in the forecast phase, by integrating the elements of exposure and vulnerability in the forecast of hazard indices; during the event, starting from the point of ignition through real-time propagation modelling for the delimitation of the potentially affected area.
For the drought risk, a monitoring chain must be completed that correlates the anomaly indices of some hazard parameters with greater precursive capacity with those closest to the impact in the different sectors, starting with agriculture.
Such tools find a natural application not only in the forecasting and monitoring phases, but also in the immediate post-event phase for quantitative damage estimation (early assessment).
CIMA Research Foundation’s expertise in real-time sensing (open-source Acronet stations) together with the use of drones and satellite data (detection of burned/flooded areas, estimation of exposure, vulnerability and damage, phenological status, etc.) integrate the modelling chains favouring the promotion and implementation of ‘all inclusive’ solutions.
Finally, there are plans to extend, albeit experimentally, the range of forecasting (from nowcasting to seasonal forecasting), toward the creation of “seamless prediction systems,” to meet the needs of different sectors and users, in addition to civil defense, including the agricultural, hydropower, insurance and transportation sectors.