G
Guns Guns Guns
Guest
Expert meteorologists are forced to arbitrage a torrent of information to make their predictions as accurate as possible.
After receiving weather forecasts generated by supercomputers, they interpret and parse them by, among other things, comparing them with various conflicting models or what their colleagues are seeing in the field or what they already know about certain weather patterns — or, often, all of the above.
Weather also has two additional properties that make forecasting even more difficult. First, weather is nonlinear, meaning that it abides by exponential rather than by arithmetic relationships.
Second, it’s dynamic — its behavior at one point in time influences its behavior in the future.
The one area in which our predictions are making extraordinary progress, however, is perhaps the most unlikely field.
When weather.gov says that there’s a 20 percent chance of rain in Central Park, it’s because the National Weather Service recognizes that our capacity to measure and predict the weather is accurate only up to a point.
Unfortunately, this cautious message can be undercut by private-sector forecasters.
Catering to the demands of viewers can mean intentionally running the risk of making forecasts less accurate.
For many years, the Weather Channel avoided forecasting an exact 50 percent chance of rain, which might seem wishy-washy to consumers.
Instead, it rounded up to 60 or down to 40.
In what may be the worst-kept secret in the business, numerous commercial weather forecasts are also biased toward forecasting more precipitation than will actually occur. In the business, this is known as the wet bias.
For years, when the Weather Channel said there was a 20 percent chance of rain, it actually rained only about 5 percent of the time.
The National Weather Service, on the other hand, which Ulysses S. Grant created under the War Department, remains true to those roots.
Many of its meteorologists have a background in the armed services, and virtually all speak with the precision of former officers.
In 1972, the service’s high-temperature forecast missed by an average of six degrees when made three days in advance.
Now it’s down to three degrees.
More stunning, in 1940, the chance of an American being killed by lightning was about 1 in 400,000.
Today it’s 1 in 11 million.
Why are weather forecasters succeeding when other predictors fail?
It’s because long ago they came to accept the imperfections in their knowledge.
That helped them understand that even the most sophisticated computers, combing through seemingly limitless data, are painfully ill equipped to predict something as dynamic as weather all by themselves.
http://www.nytimes.com/2012/09/09/magazine/the-weatherman-is-not-a-moron.html?pagewanted=all