Experts Saw Storm--With Limited Vision

When the “Blizzard of ‘93” pounded the East Coast over the weekend, spinning off tornadoes and snowstorms, it evolved on a path and a timetable precisely forecast by meteorologists.

Satellite photos showed three squalls merge into a single superstorm in the Gulf of Mexico on Thursday, and meteorologists knew immediately that an unusual bend in the jet stream would sweep it up the Eastern Seaboard and into an area of record low pressure over New England.

The National Weather Service warned last Thursday that a “major winter storm” was coming, and Pennsylvania State University meteorologists tipped New York Times readers Friday that the storm “will produce weather of memorable proportions in the East this weekend.”

The only people surprised by the blizzard were those who hadn’t seen the forecasts--or chose to ignore them.

But if this storm amply demonstrated just how accurate weather forecasting can be, it also pointed out the inherent limitations of the system. Because although they were able to give a couple of days’ warning of trouble, forecasters did not anticipate this century’s greatest storm until after it formed and was just starting its deadly rampage in the Gulf of Mexico.

Powerful computers and sophisticated computer models now routinely permit National Weather Service meteorologists to anticipate the movement of weather fronts and atmospheric pressure 36 hours in advance with 95% accuracy.

Local forecasters, in turn, can use that information to tell if the weather generally will be sunny, rainy, overcast or clear six or seven days into the future--and do it as reliably as puny three-day “outlooks” of just a generation ago.

But even the best forecasters are not much better than their grandfathers at predicting the weather next summer--or even next month. And if they forecast rain tomorrow, they still cannot say for sure if we will get a bothersome drizzle or disastrous downpour.

Last winter in Los Angeles, for example, forecasters were caught off guard by the ferocity of what had been forecast as an unremarkable thunderstorm--and could not issue flood warnings until after dozens of cars were already swamped with water in the Sepulveda Basin park.

“If all you care about is whether to carry an umbrella to work tomorrow, they’re very good at that,” said Dean Churchill, assistant professor of meteorology at the University of Miami. “But if you’re a commodities broker and you want to find out what crop yields might be in the Midwestern grain belt three months from now, you’re out of luck.”

The reason is simple: Complexity.

Weather is governed by well-understood physical laws. But those laws govern an almost unimaginably vast and complex set of variables, from the evaporation rate over Antarctica to the cloud cover over the local forecast office.

Currently, only the most obvious and easy-to-measure variables, such as the atmosphere’s temperature, moisture content and density, are used in computer models at the National Meteorological Center in Camp Spring, Md.

Wayman Baker, who helps develop the models, said the simulations start with current global conditions. They then mathematically project how such phenomena as convection and condensation will move warm, moist air masses; cold, dry air masses, and other major weather factors in 15-minute increments. It repeats the same calculations hundreds of times until a desired 48-hour or 10-day model is complete.

The models, which forecast weather influences only in broad terms and are not yet useful in predicting the processes that created last weekend’s superstorm, are distributed electronically to regional weather offices. Local forecasters--in Los Angeles, they’re on the 11th floor of the Westwood Federal Building--combine the model data with radar and satellite images to estimate how local conditions may change.

While this process produces reasonably accurate forecasts for a few days, scientists said it is practically useless to look ahead a few weeks. This is because models can only consider what meteorologists can afford to tell them. After several days, they said, the influence of subtle phenomena--such as mid-ocean sea-surface temperatures and the gravity-wave drag that slows wind flow over mountains--begin to compound one another.

These influences are not included in current computer models because they are difficult to measure and would greatly complicate the calculations. Eventually such factors multiply to the point where they significantly distort the expected behavior of storms and other obvious weather components.

“Errors multiply, and those small errors you made early on--which don’t really matter in short-term forecasts--get compounded and multiply to the point where you can’t . . . do better than to guess based on the season,” said Dan Cayan of the Scripps Institute at UC San Diego.

To get around this problem, some meteorologists are looking for new ways of making forecasts that might avoid the mathematical morass of current models.

One theory, by David Baumhefner of the National Center for Atmospheric Research in Boulder, Colo., is called “ensemble forecasting.” To factor out “observational errors,” he assumes that field reports only approximate actual conditions. He makes a range of 10 to 40 different 30-day forecasts by plugging in slightly different values for each condition. He then looks for a consensus.

Others hope for help from the new science of “chaos theory,” which seeks to show that mathematical order underlies such apparently random phenomena as curling smoke, turbulent rivers or, well, weather.

For now, however, most atmospheric scientists are focusing on improving the tools they already have, taking better measurements, creating better models, buying better computers--and presenting their forecasts in a better fashion.

For example, Weather Data and other private forecasting services generally shy from untried theories in favor of supplementing weather service data with their own field reports. They also produce very detailed forecasts tailored for specific customers and deliver them precisely when and in the format the customer desires--all things that the weather service, as a public agency, lacks the time and money to do.

The weather service, on the other hand, can invest in the latest versions of forecasting hardware. It has begun a $4.2-billion modernization plan that promises no revolutionary change in how forecasts are made but will improve every step in the existing process.

Hundreds of machines around the country will automatically measure current conditions hourly and radio them to weather service computers; new satellites will use radar to measure moisture in clouds and spectrometers to measure air temperatures; a better model will run in a faster supercomputer; a data-display system will let forecasters consider all available information at once rather than shift among a half-dozen screens; new “Doppler” radars will reveal the structure of thunderstorms, measure rain as it falls and continuously clock wind speeds at different altitudes up to 50,000 feet.

“It’s absolutely stunning,” said Churchill of the University of Miami. “I saw one that produced amazingly detailed pictures of a (clear) cold front moving over Colorado. We could never see that before.”

National Weather Service Director Elbert W. (Joe) Friday said new computer displays should produce faster, more accurate forecasts. “Too often, forecasters spend too much time getting data and not enough time analyzing it,” he said.

However, this incremental approach to improving forecasts has its critics. They ask if an imperfect but reliable system is being replaced with something that might not work as well.

Roger Wakimoto, a UCLA atmospheric scientist, said the new radar was tested in the Midwest and may not work as well in mountainous areas. He noted that Southern California’s radar site in Ventura County would be 50 miles and two mountain ranges from downtown and the airport.

In Colorado, meanwhile, a Federal Aviation Administration manager told his boss last month that automated weather monitors “(do) not always give accurate weather, especially when the weather is bad or changing rapidly.” He asked that they be mothballed until made more reliable.

Weather service official Dave Mannarano said the automated system is much better than human observers in many ways--making measurements once a minute if required, for example--although it is not perfect. “We acknowledge (it) can’t do it all,” he said. “That’s why we are going to retain staff (to personally observe weather conditions) at selected locations.”

The National Weather Service Employees’ Organization is unsatisfied. This union--which has filed suit in federal court in New York seeking to block the modernization--claimed problems with the automated system contributed to a fatal airplane crash in Oklahoma in December.

However, Brent Baylor, the National Transportation Safety Board investigator working on the crash, said it is too early to determine what factors might have contributed to the accident.

Local forecasters acknowledge there are bugs in the new system, but most said they think it still will be better than what they have.

“It’ll be trial-and-error at first,” said forecaster Constantine (Deano) Pashos, “but that’s true of every system.”

“With today’s equipment,” said Jerry McDuffie, meteorologist-in-charge of the Los Angeles office, “we still sometimes have to call the Highway Patrol in Daggett or someplace and ask, ‘Do you see any rain or flooding?’ Because of ambiguous satellite photos and gaps in our radar coverage, we have no other way of knowing.

“With the new system, we’re getting a little more scientific--and hopefully a little more accurate.”

Watching the Weather

Doppler-shift radar, developed by the military to track missiles, is being adapted to peer inside storm clouds, watch tornadoes form and measure wind speeds in the upper atmosphere. The radar is sensitive enough to detect a target as solid as a hailstone or as ephemeral as a gust of wind.

The Doppler Effect: How It Works

WHAT: Detecting and measuring movement by studying sound waves or electromagnetic waves.

HOW: The frequency of waves (which people perceive as the pitch of a sound or the color of light) appears to change slightly if the source of those waves is moving.

WHY: A train horn seems to have a higher pitch when approaching because it is closer to you each time it emits a new sound wave. Each wave must travel a shorter distance to your ear, so it arrives closer to the wave ahead of it. The frequency seems compressed, so the pitch sounds higher. When the horn moves away, the wavelength is stretched and the pitch sounds lower.

The New Radars

Doppler-shift radar takes advantage of this effect by emitting precise microwave pulses. If the pulses hit a raindrop, or even a gust of wind, they would reflect back part of each pulse. A computer can compare the original signal with these reflections to calculate the velocity of the raindrop or wind gust. For example:

* Shorter pulses and pauses: Each pulse travels a shorter distance before bouncing off the target; indicates the raindrop or wind gust is moving toward the radar.

* Longer pulses and pauses: Each pulse travels a longer distance before bouncing off the target; indicates the raindrop or wind gust is moving away from radar.

Seeing Storms

Sophisticated computer programs can analyze the radar signals reflected by storms for much more than simply which way the wind is blowing or rain is falling. Unlike older radar systems, which could only hint at a storm’s intensity, full-color displays on the new units can tell:

* When a tornado is forming

* The power of a thunderstorm

* Total moisture locked in a cloud

* How much precipitation is falling

* Where a storm came from and is likely to go

* Whether a storm is producing rain, hail or snow

Better Prediction

The Weather Service also has improved forecasts with better computer models. They forecast fronts and atmospheric pressure 36 hours in advance with 95% accuracy today, compared to less than 35% in 1955.