Hurricane forecast busts get a price tag: $133,066 per injury

A study published in Natural Hazards attaches dollar figures to the parts of hurricane forecast value that emergency managers normally treat as unpriceable: injuries, the cost of evacuating, and the long-term consequences of getting the forecast wrong ^[2][3]. That matters because the decision a forecast actually drives is a timing decision, and timing is where the money is: preparing too early can cost millions, and waiting too long puts lives and infrastructure at risk ^[8].

The work was led by Florida International University statistician Sneh Gulati and Buck Sampson, a former meteorologist at the Naval Research Laboratory in Monterey, building on research supported through the Office of Naval Research's Senior Research Fellowship ^[1][3]. Its central move is to widen the loss function beyond damaged buildings and vehicles, which is what conventional forecast-value accounting counts ^[9].

The number most likely to travel is the injury figure. Analyzing decades of hurricane data and accounting for storm intensity and preparedness levels, the researchers put the average economic cost of a single hurricane injury at $133,066 ^[4]. Used as a planning coefficient, that turns a soft argument into an arithmetic one: an intervention credibly expected to prevent 100 injuries carries about $13.3 million in avoided cost ^[10], which is the same order of magnitude as the physical preparations it would pay for. It is an average, so it compresses the difference between a laceration and a permanent disability, and any operator applying it to a specific population should treat it as a central estimate rather than a per-case price.

The model was tested against military bases, which are useful test subjects because their readiness ladders are explicit: as levels rise, preparations move from securing facilities to evacuating personnel and relocating ships and aircraft, each step with a measurable cost that can be set against storm risk ^[5][6]. Estimated savings from the expanded model ran from roughly $200,000 per storm at smaller installations to more than $70 million at larger ones ^[5], a spread of about 350 times ^[11]. That range is the practical finding. The value of a better forecast scales with the value of what has to be moved, which means the same forecast improvement justifies very different spending at a small coastal town than at a fleet concentration.

One caveat on the headline framing. The available summary states that long-term consequences of forecast errors, including erosion of public trust, are incorporated ^[3], but it does not publish the functional form or magnitude of that term. Trust decay is the hardest quantity in this model to validate, since it is measured over multiple seasons and confounded by everything else that shapes whether people evacuate. Anyone adopting the framework should look at that coefficient before relying on it in a public argument.

"These computations can perhaps help the public and government entities realize the importance of storm preparation and accurate forecasting," Gulati said ^[7]. The authors say the approach can be extended to cities, coastal communities and other storm-prone regions ^[12]. That extension is where it either becomes a budgeting tool or stays a paper: a city has no equivalent of a base commander's readiness condition, and no single accounting entity absorbing both the evacuation bill and the injury bill.