Gleaning Clues on Sunny Days From the Clouds

The following is an excerpt from an article in:


The New York Times
Wednesday, October 24, 2012

Gleaning Clues on Sunny Days From the Clouds

By DAVID FERRIS

CARLOS F. COIMBRA knew from the outset that he would have to crack the code of clouds. As an engineering professor new to the University of California’s campus in Merced, he led a successful drive to get 15 percent of the school’s power from an array of solar panels.

But clouds, wandering and capricious, had foiled his efforts on two occasions by casting sudden shadows, forcing the school to rely on conventional power instead. To neutralize the clouds, he would have to track them.

So Professor Coimbra, a Brazilian-born expert in fluid mechanics with a flair for computer modeling, tried a new kind of forecast. The campus would make better use of sun power if he could figure out exactly when a puffy drifter would arrive overhead. He wrote a computer algorithm to project how clouds move and change shape as they move across the sky — one of the most complex and chaotic phenomena on earth, influenced by an endless set of variables.

Now, six years later, Professor Coimbra, 44, and his collaborator, Jan P. Kleissl, 37, have created a forecasting engine that they say is 20 to 40 percent more accurate than the model in common use. Weather, energy and power grid experts said that the innovation could accelerate the adoption of renewable energy, save billions of dollars in energy costs and help turn cloud-watching from an idle pastime into a vital and profitable part of the weather forecast.

“I can’t tell you what’s going to happen at 4:23 p.m. on a Sunday,” said Professor Coimbra, whose forecasts extend to seven days but with decreasing accuracy. “But I can tell you what will happen between noon and 6 today.“

Potential cost savings are drawing the interest of companies that build and operate solar-power plants, as well as utilities and grid operators. Each bets a bottom dollar on when the sun will come out tomorrow. A fine-tuned forecast makes it easier for utilities and grid operators to use the sporadic power of sun and wind when they are available, giving renewable energy a reliability close to that of a fossil-fuel or nuclear power plant.

Furthermore, it could help utilities predict exactly when homeowners will turn on their air-conditioners in the summer, which could reduce the power grid’s need for backup power plants.

As it saves money in energy markets, the technology could also shake up the world of weather forecasting by providing greater resolution. Such data could give airports a firmer window of when storms will arrive and leave, resulting in fewer flight delays.

It could tell farmers when to expect the first frost, or when a rainstorm will hit, reducing the need to pump water for irrigation. A precise prediction could guide the maneuvers of forest firefighters, project the path of bioterror attack or pinpoint the path of a tornado.

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