A couple of days ago, we were excited with meteorologist John Morales, who shed tears on television (specifically, on NBC) while offering his predictions about Hurricane Milton, that ended up going viral.
Milton has left 23 dead in Florida.
However, the forecasts also have saved countless lives and belongings and, According to recent studies, They are also related to saving billions of dollars, which demonstrates the importance of investing in science and technology.
What a good prediction saves
Efficient hurricane forecasting is essential for governments, which organize and plan their response, both before the arrival and after the impact of the storm.
Mateos García, a Google Deepmind worker, shared a recent study signed by Renato Molina and Ivan Rudik in X (formerly Twitter), which demonstrates how make better weather forecasts supposes big savings for the annual US budget.
How valuable are better predictions?
Really valuable.
This economic analysis of the impact of better weather forecasts on hurricane costs suggests that the US Hurricane Forecast Improvement project saved $5B per hurricane – more than the annual US weather forecasting budget! pic.twitter.com/AJq8nQjDVD— Juan Mateos Garcia (@JMateosGarcia) October 14, 2024
In The Value of Improving Hurricane Forecasts (The social value of hurricane forecasts), researchers estimate that, between 2007 and 2020, there were notable savings, amounting to 5 billion dollars per hurricane, associated with both prior preparation costs and subsequent damage thanks to prediction models.
To a large extent, the savings are related to a more efficient allocation of emergency funds, which depend on (more precise) predictions of wind speed. Thanks to technology, the errors in the forecasts in the period of time analyzed by the study by Molina and Rudik were reduced by 50%.
Likewise, If forecasts underestimate storm intensity, Damage and government spending increase significantly, while improved forecast accuracy maintains significant cost reductions, locally and nationally.
Absolute value of wind speed forecast error, in miles per hour (1990-2021).
The bases of the study
The study focused on storms that were recorded as Category 3 or higher, or that, at least, They exceeded 20 billion dollars in damages.
In this period (2007-2020), of the 29 hurricanes, 18 met these criteria and they accounted for 90% of the deaths and the main damage to public and private properties.
To carry out the analysis, The research analyzed pre-hurricane preparedness expenditures at the county level (this information was collected from FEMA Public Assistance Program) and county-level hurricane damage (SHELDUSo Spatial Hazard Events and Losses Database).
The main conclusions were that a county that is expected to experience hurricane-force winds receives, on average, 30 million dollars more in backgrounds than one where winds below hurricane force are predicted.
And, at the same time, if the precision is improved (i.e., the standard deviations of the wind speed forecasts are reduced), there is a reduction in $30 million in county-level hurricane spending.
A very, very notable saving.
The reduction in forecast errors has been decreasing by 0.21 m/s year after year (approximately 50%) in these 14 years (2007-2020) and the costs by $700,000 per county or $5 billion per hurricane: 19% less total expenditure associated with aid.
In conclusion, the importance of accurately predicting how a hurricane will affect saves money and resources, being the basic technology in this area. The loss reductions associated with these improvements far exceed the government’s annual spending on weather forecasts. Therefore, it seems clear: Investing in predictive models, AI and technology makes more sense today than ever.
Source: www.elblogsalmon.com
