Largely because of the lack of precedent, forecasting models are having a very difficult time accurately forecasting extreme weather events. With these extreme events increasing in frequency around the world, this poses several problems in the meteorology community – one of which is how best to warn the public about extreme events if even forecasters do not know it is coming.
In the case of Hurricane Otis, which struck Acapulco in Mexico on October 25, the storm intensified from a tropical storm to a devastating Category 5 hurricane in only 12 hours, striking the city in the middle of the night. Forecast models, with relatively simplified physics built in, were unable to account for the detailed physical intricacies of this extreme event, unanticipated interactions in the atmosphere, and the exact intensification of Otis due to extreme sea surface temperatures off the coast of Mexico—also something not built into current computer forecast models. Most forecast models, and thus the official forecasts from the National Hurricane Center, had predicted intensification of Otis before landfall, but not to the record degree at which it intensified.
In short, current forecasting models are being proven to be inadequate in extreme event scenarios as we are faced with increasingly extreme weather events, due largely to increasingly accelerating climate change.
