It was a tale of two storms. The first consisted of the rain and thunder forecast for Bournemouth by the BBC weather app on the Saturday spring bank holiday. The second came when the first failed to materialise and a tourism manager in the town complained that visitors who stayed away could have come after all and enjoyed sunshine and blue skies. This opportunity to rage at inaccurate forecasting, bash the BBC and highlight the grievances of small businesses did not go to waste. For the Sun, it was a "blunderstorm".
An amusing meme was getting around the Internet this week reminding people to consider their "March Madness" bracket "busts" the next time they ridicule a meteorologist for trying to predict the future. Meteorologists are familiar with cliche statements like "it must be nice to get paid to be wrong 50% of the time." I often wonder why meteorologists seem to bear the brunt of ridicule and angst when so many others professions forecast with varying (and often lesser) degrees of success (economists, demographers, sports analysts, political pundits, investors and some aspects of the medical field). The reality is that modern-day weather forecasts are pretty accurate so I decided to explore reasons people think they are bad. A field goal kicker could make every single kick during football season, but what if he misses the "big one" in the championship bowl game?
As the hurricane season's third tropical storm churns toward the US coast, forecasters lack some key data that helps them predict a hurricane's size, speed, and path. Cruise ships and commercial airlines that collect weather information along their routes are now mostly grounded because of the coronavirus pandemic, forcing meteorologists to rely on satellites that are slightly less accurate than direct measurements of the atmosphere. Federal health officials imposed a "no-sail" order on the cruise ship industry because of infections aboard several liners, while air travel has plummeted since many states imposed lockdowns in mid-March. Airlines canceled thousands of flights, according to figures from the Transportation Safety Administration. As a result, weather centers in the US and Europe have seen a decline of more than 80 to 90 percent in weather flight data.
The National Hurricane Center accurately predicted the path of Hurricane Irma, which struck southwest Florida on Sept. 8. This was not an easy storm to forecast, though, as computer models disagreed with one another on important details right up until landfall. But in general, the European model, which is run by the European Center for Medium-range Weather Forecasting (ECMWF), performed far better than the premiere U.S. model, known as the Global Forecast System (GFS). SEE ALSO: Before and after photos show Hurricane Irma's devastation in the Caribbean Hurricane Irma is one more in a long line of storms to shine a spotlight on problems with the GFS, particularly at intermediate to longer timescales. The issue gained prominence after Hurricane Sandy struck New Jersey in October 2012, which the European model hinted at at least a week in advance.
When Hurricane Sandy made a devastating left hook into the Mid-Atlantic on Oct. 29, 2012, killing nearly 150 people and causing about $70 billion in damage, a narrative took hold in the weather community and the media that made its way to Capitol Hill. U.S. weather models were late in forecasting that storm's bizarre track when compared to the top model from Europe, which locked onto it more than a week in advance. Many in and out of government began to criticize what they saw as a growing modeling gap across the Atlantic Ocean. The weather model wars are continuing, and new evidence has emerged that instead of making a leap forward in forecast accuracy as Congress has directed, the U.S. may be about to take a step back, at least when it comes to high-impact events such as hurricanes and tropical storms are concerned. SEE ALSO: Looking for hope on climate change under Trump?