DISASTERSWhy Do Disasters Still Happen, Despite Early Warnings? Because Systems Are Built to Wait for Certainty
Uncertainty cannot be eliminated. The challenge is to decide how much uncertainty is acceptable when lives and livelihoods are at stake. Systems designed to wait for certainty are more likely to deliver warnings that arrive too late to feel like warnings at all. If resilience to future climate risks is to be sustainable, warning systems must be designed to learn, adapt, and act earlier on credible risk.
After major disasters, public debate often treats them as unexpected or unprecedented. This reaction is not necessarily about the absence of warnings. It reflects how societies process shock – and how authorities often explain disruption as unavoidable, rather than the result of earlier choices.
Extreme weather is rarely unpredictable. Days, sometimes weeks, in advance, scientists are able to warn of an increased risk of storms, floods, droughts or other hazards. Yet the cycle repeats.
To understand why this is, colleagues and I reconstructed the scientific warnings and the official responses to major floods in Luxembourg in July 2021 – my home country’s most damaging disaster on record. Those floods caused far more damage than they would have done if early action was taken, but Luxembourg isn’t an outlier: many other countries suffer from the same problems we identify.
As the UN targets “early warning for all” by 2027, it’s worth noting the issue is not that warnings were missing. It is that warning systems are often designed to act on certainty rather than probability – and that’s not how forecasting works. By the time warnings become visible to the public, it is often too late.
Weather forecasts may look definitive on your phone, but they are probabilistic by nature. They are created by running a series of computer simulations of the future weather. The level to which the outcomes of different simulations agree with each other provides the likelihood of hazardous conditions, not guaranteed outcomes. These allow forecasters to identify elevated risk well before impacts occur, even if the precise location of an event and their size remain uncertain.
Crucially, uncertainty is usually greatest further ahead, when preventative action would be most effective. Acting early therefore almost always means acting without certainty. This is not a weakness of science, but an inherent feature of anticipating complex systems under changing conditions. The real challenge lies in how institutions are organized to interpret, trust and act on those probabilities.
Acting on Certainty
Most warning systems rely on predefined procedural thresholds: alert levels, activation protocols and emergency plans that kick in once specific criteria are met. Forecasting may indicate that flooding is increasingly likely, for example, but measures such as evacuations or road closures can only be triggered after formal thresholds are crossed.
Before that point, risk information passes through many layers of interpretation and judgment, where early signals are often noted but not acted upon.
