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Weather
Forecasting Is Really Chaos
By T. Evan Schaeffer
Everyone complains about the inaccuracy of weather forecasts,
but consider the plight of American Airlines and American
Eagle. On April
29, 1995, an unexpected storm dropped hail nearly the size of
footballs on their fleet of jets at the Dallas/Forth Worth
International Airport, damaging the planes and forcing the
airlines to cancel 450 flights over the next week.
Even
though American employed 19 meteorologists, and a new National
Weather Service radar was in place near the site of the storm,
there was no advance warning of the developing hail.
As a result, the airplanes remained on the tarmac,
unprotected and unmoved, monuments to the forecaster’s
seeming ineptitude.
It’s
a sad tale, and one echoed at one time or another by everyone
who can recall the day—or perhaps the hundreds of
days—that the forecasters bungled things enormously,
necessitating a change in the weekend plans, or, in the case
of American and American Eagle, causing damage and lost
profits in excess of $26
million.
Is
there any hope for improving weather forecasts?
According to the National Weather Service, maybe so.
Right now, it’s nearing the end of a $4.5 billion
modernization program that according to the more-optimistic
experts, will improve forecasts and may even usher in a golden
age of weather forecasting.
First
announced in 1989, the modernization program has been
sidetracked by delays, cost overruns, and technical problems.
But it’s not all bad news.
Just a few months ago, for example, the weather service
announced the successful positioning of a new satellite that
for the first time, will offer pictures of developing weather
patterns over the Pacific Ocean.
The
modernization program also includes several other items of
interest:
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A network of Doppler radars that track the speed and position
of moisture in the air.
Computer programs that analyze data from these radars
can tell the amount of rain or snow falling to earth, the
power and path of thunderstorms, and whether tornadoes are
beginning to form.
--
More than 900 new “ASOS” weather stations that
automatically report data on
temperature, dewpoint, wind direction, wind speed, and
barometric pressure.
Eventually, these technological wonders may replace
human observers.
--
Better computers and software.
Already, the machines that run the forecaster’s
weather models are 20 times more powerful than a decade ago.
The models themselves, which extrapolate future weather
events from known conditions, are also much-improved,
affecting the speed and reliability of the forecasting
process.
The phenomenal amount of money
being spent on these improvements is probably justified, given
the way the nation’s economy depends on reliable forecasts.
Each day, tens of thousands of decisions are made on
the basis of the weather by farmers, construction workers,
commodities traders and utility companies.
So important are reliable forecasts, in fact, that a
$150-million a year industry has grown up to provide
supplemental, private weather data to businesses and
individuals.
Paying
the money to get it right makes sense.
The trouble is, despite the money, meteorologists aren’t
getting it right. Even
with the weather service’s ongoing “modernization,”
attempts to forecast the weather past just a few days are
still basically unreliable. What’s the problem?
It’s
the meteorologist’s dirty little secret: though forecasts
have improved over the last two decades, and will continue to
improve slightly, unpredictability is inherent in the weather.
Though it’s not their fault, the meteorologists will never
be able to get it right.
The golden age of weather forecasting?
Forget it.
There’s
a scientific term for this depressing truth: chaos.
The earth’s atmosphere is a “chaotic” system of
the sort first described in a 1963 paper by meteorologist
Edward Lorenz. In
simple terms, this means that unlike “deterministic”
systems such as the planetary orbits around the sun, in which
tiny errors in the starting conditions don’t affect
long-term forecasts, small differences in the weather do just
the opposite—they multiply, quickly throwing even the
simplest predictions into disarray.
The
implications of chaos theory did not fully dawn on the rest of
the scientific community until the mid-1970s.
Twenty years later, for reasons both complex and
profound, chaos theory is now considered meteorology’s great
contribution to 20th century science, with applications
for biologists, physicists, astronomers,
geologists, and physicians.
But
don’t expect to hear about chaos theory during the weather
segment of the evening news.
After all, why should the forecasters reveal their
meteorological fine print to the public—that they can
predict temperatures easily enough, but rain and snow are
constant headaches? That
seven-day forecasts are a pipe dream, and two-week forecasts a
hallucination? That
despite scientific advances and “modernization,” they’re
still not too far removed from soothsayers and
fortune-tellers? That
chaos makes their job impossible?
No,
this would be sheer stupidity.
The fact is, the public is fascinated with weather, and
a good dose of the truth would only spoil the mood.
As this fascination is demonstrated once again by the
public’s interest in spring storms and the success of the
movie “Twister,” the informed weather-watcher
should understand that it’s simply not fair to blame the
meteorologists.
To
paraphrase Edward Lorenz, what’s amazing isn’t that the
meteorologists botch so many forecasts, but that they
occasionally get some right.
Rather than jeer, you should await the results of the
weather service’s probably-modest improvements with an open
mind. And while
you’re waiting, give a kind word to your local forecasters,
and compliment them on their usually-good performance of one
of the toughest jobs on earth—unless, that is, you’re an
executive with American Airlines.
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