updated 3/10/2006 4:01:34 PM ET 2006-03-10T21:01:34

Scientists who studied detailed satellite data about North America's forests, fields and grasslands say they have used it to create more accurate forecasts of severe weather and tornado outbreaks.

Their computer model takes into account water vapor released by tree leaves, grasses and crops  moisture that can trigger or stifle severe weather by interacting with storm fronts, said Dev Niyogi, a Purdue University scientist who led the study.

Niyogi, an assistant professor of agronomy and earth and atmospheric science, said the weather model he and five other scientists created incorporates improved satellite data of vegetation-moisture levels.

Although numerous studies have examined the impact of using improved soil moisture data in forecasting, Niyogi said weather forecasts have not noticeably improved. The problem seems to be that existing computer models include overly simplistic representations of vegetation.

Temperature and moisture have long been known as two key forces behind weather systems. But Niyogi said the new, detailed vegetation-moisture data appear to be "the missing link" needed to boost the accuracy of forecast models that use a complex mix of variables.

"Our study shows is that subtle differences in vegetation can affect the timing, intensity and location of thunderstorm formation," Niyogi said.

The team's findings arose from the results of their predictions of the scope and intensity of storms that developed during a severe weather outbreak in western Texas in May 2002.

Those results were published in the January issue of the Monthly Weather Review, a publication of the American Meteorological Society.

Roger A. Pielke Sr., a professor of atmospheric science at Colorado State University, called it an "important paper" that highlights the need for scientists to accurately simulate the interaction between vegetation and weather systems.

"This added fuel for thunderstorms is a critical issue with respect to how intense they become," he said.

Niyogi said his team's model represents about 15 types of vegetation, such as mixed forest, grassland, savanna and irrigated crops — each of which produce different amounts of moisture as they convert sunlight into nutrients.

That moisture can strengthen, weaken or deflect storm intensity, he said.

Stephan P. Nelson, program director of physical and dynamic meteorology at the U.S. National Science Foundation, said scientists are beginning to understand the important role that vegetation wields over soil moisture and temperature — and how they influence storms.

"Currently, numerical weather prediction models do not handle these aspects of surface variability well," Nelson said.

Niyogi, who is Indiana's state climatologist, said he and his co-authors are working on creating a more complex forecast model. He said it could be ready in a couple of years.

The team's other members were: Teddy R. Holt from the Naval Research Laboratory, Monterey, Calif.; Fei Chen, Kevin Manning and Margaret A. LeMone from the National Center for Atmospheric Research in Boulder, Colo.; and Aneela Qureshi from North Carolina State University.

The study was funded by NASA, the Office of Naval Research and the National Science Foundation.

Copyright 2006 The Associated Press. All rights reserved. This material may not be published, broadcast, rewritten or redistributed.

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