Skip to content

News Center

Home > News Center > Publications > EnVision


EARTH SCIENCE | Contents | Next

Fine-Tuned Atmospheric Model
Simulates Hurricanes to Climate Change


s Hurricane Andrew slammed into the southeast coast of Florida in 1992, its central eye pressure plum-meted unexpectedly to the third lowest recorded this century for a hurricane at U.S. landfall. With this sudden pressure drop, Andrew intensified to a maximum sustained wind speed of 125 knots (145 mph) and gusts in excess of 150 knots (175 mph). The category-four hurricane led directly to 26 fatalities and became the most expensive natural disaster in U.S. history, causing property damage estimated at $25 billion. Joseph Eastman, Mel Nicholls, and Roger Pielke, Sr., of Colorado State University (CSU) have been probing the dynamics of Andrew and other hurricanes in unprecedented detail by running the Regional Atmospheric Modeling System (RAMS) on NPACI’s Blue Horizon. These and other RAMS simulations are advancing atmospheric science in a variety of areas. The work is also revealing unexpected relationships between factors such as ocean warming and hurricane behavior, as well as land use and climate change.

Simulation of Hurricane Georges at landfall on Puerto Rico

Figure 1. Simulation of Hurricane Georges at landfall on Puerto Rico

This RAMS simulation examines the effects of sea surface temperature on hurricane intensity and effects of topography on a hurricane at landfall. The model is in reasonable agreement with recorded data and captures details of Georges’s eye. The simulation uses a 5-km horizontal mesh with more than 500,000 simulation cells. Environmental WorkBench (EWB), courtesy of SSESCO, Inc., generated the graphics. The animation is available at

"RAMS could be seen as a sort of ‘Swiss Army Knife’ of atmospheric models," said Eastman, a research associate in the Department of Atmospheric Science at CSU. Scientists are using this sophisticated modeling system to simulate events from cloud dynamics, flash flooding, and hurricanes to large-scale weather systems and climate studies. Simulations can be as local as wind flow around urban buildings or extend to global scales. "RAMS is even being used in prototype, real-time weather forecasting, which it can do very accurately if enough computer resources are available," said Eastman.

He was the first to apply the power of a mesoscale model (covering scales from the area of a city to a continent) to hurricanes. For the first time, these simulations were able to resolve features as detailed as the sloping eye wall of Andrew and the rapid intensification event, a 42-millibar (mb) drop in central pressure to 922 mb in just 24 hours. The rapidly plunging pressure was a crucial factor in the hurricane’s destructiveness and is a dangerous phenomenon that conventional forecast models do not predict well.

Perspective view of Hurricane Georges

Figure 2. Perspective view of Hurricane Georges

In this rotated view of Figure 1, the vertical is stretched by a factor of 11 to highlight flow over the mountains and show hurricane size relative to clouds over the Dominican Republic. Note developed eye and bump of overshooting cloud tops, marking area of most intense convection. Graphics generated with Environmental WorkBench courtesy of SSESCO, Inc.

"In our simulations, we start the model off using the weather data recorded at a certain time for the actual hurricane, and then let the computer model of the storm ‘spin up,’ which takes about six simulated storm hours," said Eastman. The hurricane simulation is integrated forward in time for an additional 42 hours. The realism of RAMS simulations comes from its greater reliance on fundamental physics, with fewer approximations. "By including properly resolved microphysics, we obtain better predictions of clouds, rain, hail, and so forth, leading to a realistic thermodynamic profile," said Eastman. "These feedbacks are very important in hurricane behavior, and you really have to include them."

Eastman recently used RAMS to model Hurricane Georges. In addition to extensive property damage, authorities attributed 602 fatalities to the 1998 category-four hurricane, mainly in the Dominican Republic and Haiti. In the Dominican Republic, Georges dropped 39 inches of rain in 24 hours, devastating the island with flash floods and mud slides.

"Most forecast models operate at a horizontal grid spacing of 20 km or greater, and many important phenomena slip through the cracks," said Eastman. The computational power of Blue Horizon enabled him to run RAMS at a 5-km grid spacing for Georges. At that finer resolution there are 16 grid points in each of the previous larger cells, which enables the model to resolve more details of the storm (Figures 1 and 2).

Effects of clouds and rain on photosynthesis

Figure 3. Effects of clouds and rain on photosynthesis

This simulation couples RAMS to the University of Kansas General Energy and Mass Transfer Model. Green and yellowish patches are areas of photosynthesis enhanced by previous precipitation, while darker blue areas indicate decreased photosynthesis due to shade and precipitation from passing clouds.


The researchers are focusing on the effects of topography and vegetation on tropical cyclones, which is important when these storms make landfall and do much of their damage. To explore this, Eastman ran RAMS simulations with and without topography included. "This lets us form hypotheses, test them, and run the simulation again," he said. "We’re learning more about basic hurricane science, and at the same time moving toward better hurricane predictions."

Eastman is running simulations of Georges at an even finer horizontal grid spacing of 1 km. "This is approaching a simulation that can resolve large turbulent eddies in the atmosphere," he said. "We think it will give better predictions of precipitation, which has always been challenging to model." For simulations of Hurricane Georges at 5-km grid spacing, RAMS ran on 64 of Blue Horizon’s 1,152 processors. The 1-km simulations require more computation, with 25 points in each previous 5-km cell as well as requiring shorter time steps. They run on 256 or more processors.

Eastman and his colleagues have also examined the possible effects of ocean warming on hurricanes. It has been widely speculated that a sea-surface warming due to global climate change might produce more intense hurricanes with higher wind speeds. The researchers were surprised to find that including a 2°C ocean warming in the simulation did not produce more intense hurricanes; however, it did result in significantly increased precipitation. Since excessive rainfall often causes more damage than high winds, these results raise the possibility of more destructive hurricanes in a warmer climate.


RAMS is an easy-to-use mesoscale model. It has a good parallel interface and runs on different platforms from Linux and AIX to Windows 2000. Based on a multiple grid nesting scheme, RAMS provides options that allow it to be tailored to many different problems.

"RAMS is capable of modeling not only hurricanes, but also a wide array of other atmospheric phenomena at a level of detail never before possible," said Pielke, a professor in the Department of Atmospheric Science at CSU. "RAMS simulations are providing important research insights into the basic dynamics of weather and climate. And they are also producing information that has practical and predictive value."

RAMS had its beginnings at CSU in the early 1980s. Researchers at CSU and the Mission Research Corporation are refining it in step with greater computing power, incorporating both more realistic physics and greater flexibility.

The accurate physics and sophisticated radiation and land-surface parameterizations included in RAMS require greater computing resources than simpler models. Initially this limited the model to running at regional scales, but as the power of computers has grown, the realism of RAMS has allowed it to scale upward until it is now being tested in a global version.


As RAMS has become more scalable and realistic, researchers have combined it with other models. Eastman is linking the weather and climate modeling power of RAMS to land cover and biodiversity models in collaboration with NPACI Earth Systems Science partners at SDSC, the University of Kansas, and the Long-Term Ecological Research (LTER) program.

With computer scientist Tony Fountain of SDSC, Eastman has run RAMS in one-day integrations on a 10-km horizontal grid, using a combined atmosphere-ecosystem model. "We know that atmosphere and biosphere are interrelated, but modeling this has been a challenge," said Fountain. "Few ecosystem models include dynamic atmospheric feedbacks, so we’re very interested in the results of this coupled model."

For example, the model can simulate changes in photosynthesis due to cloud cover or rainfall (Figure 3). Eastman also is working with Bob Waide, LTER Network Office executive director at the University of New Mexico. They are analyzing regional vulnerabilities to such environmental influences as landscape change. They are working on a yearlong run with RAMS and a coupled plant model on a 10-km grid that covers the U.S. In previous runs on a 50-km grid, the researchers found that changes in land use since European settlement--deforestation and different vegetation--can make just as much difference in local and regional climate change as doubling the atmospheric concentration of the greenhouse gas carbon dioxide. "This result was a big surprise," said Eastman. "Everyone tends to assume that global warming, as characterized by a predicted doubling of carbon dioxide, is the first and main human influence on climate."

RAMS model output has also been used to drive a biodiversity model developed at SDSC called the Genetic Algorithm for Rule-Set Prediction (GARP) in runs on Blue Horizon. The researchers are trying to understand how climate change may affect biodiversity in simulations that span several hundred years. "In these simulations, we’re going from 50 km to a much finer 10-km grid," said Eastman. "This is a very useful step because we’ll begin to resolve mountain, valley, and other mesoscale circulations." These atmosphere dynamics are important to local climate, which influences species occurrence. Resolving such phenomena will help researchers model biodiversity more reliably.

RAMS is also being used in coupled atmosphere-ocean simulations, linked to local pollution models in air quality research and used in other research applications. "It’s amazing what we’re able to do now," said Eastman. "Five years ago, I didn’t think these things would be possible, but with the power of Blue Horizon, it’s feasible to run high resolution simulations that have never been done before. This evolution keeps teaching us new things." –PT


Project Leaders
Joseph Eastman
Colorado State University
Roger Pielke, Sr.
Colorado State University

Tony Fountain

Mel Nicholls
Colorado State University

A. Townsend Peterson
University of Kansas

Robert Waide
LTER–University of New Mexico

Eastman, J. L., M. B. Coughenour, and R. A. Pielke, 2001: The effects of CO2 and landscape change using a coupled plant and meteorological model. Global Change Biology, in press.

Pielke, R.A., Jr. and R.A. Pielke, Sr., 1997: Hurricanes: Their Nature and Impacts on Society. John Wiley and Sons, England, 279 pp.

Pielke, R. A., W. R. Cotton, R. L. Walko, C. J. Tremback, W. A. Lyons, L. D. Grasso, M. E. Nicholls, M. D. Moran, D. A. Wesley, T. J. Lee, and J. H. Copeland, 1992: A comprehensive meteorological modeling system–RAMS. Meteor. Atmos. Phys., 49, 69-91.