The traditional way of studying climate change has relied on looking at minute fluctuations in temperature, ocean currents and weather systems over a prolonged period.
Scientists then take the averages of those measurements to get an idea of what will happen in centuries to come. But this method requires a serious amount of data-crunching over a long period of time by a supercomputer.
Researcher Brad Marston at Brown University developed a new method of climate simulation that requires no data and can be done in a fraction of the time.
Called direct statistical stimulation, Marston’s method is based on theoretical physics.
“The approach that we’ve been taking has been to try to calculate statistics directly,” Marston said. “Average quantities like average temperatures, winds, and also their fluctuations, how much they vary from moment to moment — those quantities can be solved for.”
His research, done with University of Leeds mathematician Steve Tobias, was published last month in the Physical Review of Letters, which largely serves an academic audience.
Promoting their findings among the general public required a different approach, and for that, Marston created a desktop app that displays visual models of both methods — his and the traditional approach — to allow users to compare the two.
The app — called GCM for General Circulation Models — uses waves of different colors over spheres resembling the globe to illustrate how air and water move across the planet.
“This technology is so easy that anyone can play with it, and I hope it will demystify some of the science behind climate modeling,” he said.
The basic idea of calculating climate in this more straightforward way — by focusing on its fundamental forces and not on the minutiae of weather changes — was proposed 50 years ago by Edward Lorenz, the father of chaos theory.
“At the time they didn’t have the resources to do this and that idea laid fallow,” Marston said. “We’ve revived it.”
But the method is not without hiccups: The approach is based on approximations, which become less accurate as the amount of energy used in the statistical model increases.
“What we found is that if we start pushing energy through the model faster and faster so that it approaches the rate at which the winds themselves are swirling around, then this approach loses its accuracy,” Marston said, adding that the statistical technique is “on the cutting edge.”
GCM from Brown University is one in a string of apps from scientists that attempt to promote their work and inform the wider public.
NASA two years ago released the Visualization Explorer app to let users interact with the images and videos generated by the agency’s earth-science research team. The aim was to help students better understand planetary features such as glaciers, hurricanes and volcanoes by seeing them in action.
Researchers at Stanford University last summer created an app that allowed users to follow northern Californian white sharks in real time. The goal of the project was to create a better understanding of the marine ecosystem and promote the protection of sharks, tuna and turtles that inhabit the area.
Brita Belli is the editor of E-The Environmental Magazine and the author of two environmental books. Her writing has appeared on Environmental Health News, MSN.com and the website of National Geographic.Tags: Business,Business Intelligence,Corporate Responsibility,Downtime,Education,Mobile Apps,Technology