PHOTO: NATIONAL OCEANIC & ATMOSPHERIC ADMINISTRATION
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Hurricanes and tropical storms are back in the public
mind, especially in North and Central America, where
they did more than US $100 billion in damages last year.
Some see the inescapable side effects of global warming,
noting that 2005 was the worst year for Atlantic
hurricanes in recorded history. Others see a financial
opportunity: online gambling establishments have opened
betting pools on this year’s storms—you can wager on how
many hurricanes will hit the United States, how many
will hit Florida, and even on what the storms’
Saffir-Simpson intensity categories will be.
While it sometimes feels like storm forecasting is
one bad bet after another, hurricane forecasting, and
weather forecasting in general, have actually improved
enormously in the half century since John von Neumann
and Jules Charney used 24 hours of ENIAC computing time
to produce the first 24-hour numerical weather forecast.
And according to our authors Robert Gall and David
Parsons from the U.S. National Center for Atmospheric
Research, in Boulder, Colo. [“ It’s
Hurricane Season: Do You Know Where
Your Storm Is?”], it’s going to get
significantly better very soon.
Why? Supercomputing power, sophisticated sensors,
weather-specific satellites, advances in modeling
techniques, and better understanding of how weather
works will converge and dramatically improve our
ability to know precisely what’s coming our way, and when.
Collecting weather data is a complicated business.
Meteorologists gather readings from instruments on
balloons, planes, ships, satellites, and terrestrial
weather stations. The amount of data is staggering and
getting bigger all the time; it will increase by a
factor of 10 000 in the next decade, thanks to the
deployment of new sensing devices and the launch of
several new weather satellites. Six alone were launched
last April in a joint venture between the United States
and Taiwan. The European Union and several Asian nations
also have ambitious plans on the launchpad. Forty-four
countries are now developing plans to share their
combined collected weather data as part of the Global
Earth Observation System of Systems, or GEOSS.
More data means better weather models, but these
mushrooming measurements also call for lots of computing
power if they are going to be analyzed in anything
resembling real time. Supercomputers now make possible a
technique called ensemble forecasting. A weather
prediction system runs the same weather model over and
over again but tweaks the initial state each
time—relative humidity might be increased by a fraction
of a percent and so on. A range of forecasts emerges,
and as the iterations continue, one pops up more
frequently than the rest. As a result of international
efforts to coordinate modeling, large supercomputing
grids will be able to run larger and larger
data-encompassing ensembles even before 10- or
20‑teraflop computers come online.
What it will all mean is that when the TV
meteorologist says take your umbrella, you’d better do
it. And more important, when she says Hurricane Zelda is
going to hit Tampa on Wednesday at 3:00 p.m. EST, it
undoubtedly will.
Ensemble modeling makes obvious another difficulty in
predicting the weather. Weather is dynamic, while
current weather prediction technologies aren’t—they
can’t adapt to changing weather conditions, which makes
things like predicting a storm’s changing intensity
virtually impossible. The ultimate challenge will be to
create forecasting systems that can react to their own
changing measurements and observations in real time.
In North and Central America, the 2006 Hurricane
season is now upon us—August to October is peak season.
The U.S. National Oceanic & Atmospheric
Administration expects a busy one, predicting 13 to 16
named storms, with 8 to 10 becoming hurricanes. How much
damage and human misery these storms bring with them
will depend on how strong they are and whether or not
they make landfall in heavily populated areas. How
valuable it would be to understand how they will behave
days or even weeks in advance, so people would really
know when to prepare for the worst and when to continue
business as usual.
For the time being, however, getting the weather
right will still require a large dose of good fortune.
But continued improvements in our weather predicting
capabilities will eventually take the guessing out of
storm prediction and bring us to the moment when
wagering on the weather will be a safe bet indeed.
The editorial content of IEEE Spectrum magazine
does not reflect official positions of the IEEE or
its organizational units. Please address comments to
Forum at n.hantman@ieee.org.