How can you predict global warming if you can't predict rain?
Some say climate change is part of a complex natural cycle – so complex, in fact, that it can't be forecast. Are current climate models reliable?
To those of us who are not climate scientists, it may come down to this: How can we be so certain what the climate will be like a century from now if you can't get a decent weather forecast more than two weeks ahead? In the end, isn't climate change just too complex?Skip to next paragraph
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True, weather forecasters are fallible, and there is no planet out there similar to Earth so we can truly gauge the effect human activity is having on our climate. But climate researchers are increasingly confident of their models and simulations. Besides, some argue, predicting the weather is tougher than predicting the climate, and scientists have been working on perfecting climate models for more than a century.
In a chilled, windowless room here at the National Oceanic and Atmospheric Administration's Geophysical Fluid Dynamics Laboratory (GFDL), a supercomputer is furiously crunching numbers in an attempt to mimic Earth's climate system.
It's a tool Svante Arrhenius could only dream about. In 1896, the mustachioed Swede gave the first detailed description of carbon dioxide's warming effect on climate. He had to solve some 10,000 equations to do it. Armed with his crude climate model, he reckoned that if the amount of CO2 in the atmosphere doubled, global average temperatures might rise by up to 9 degrees F. Today's modelers say his estimate is high – but not by much.
Today's climate models try to simulate more than one feature – more than Arrhenius's CO2 – of the climate system and in greater detail. They're still far from perfect and miss important processes.
It's complicated, modelers say. And there will always be uncertainties. But modeling is the only way to tackle some of the questions they and their colleagues are asking about the climate, they add.
Field measurements and observations are critical, notes Michael Winton, a member of the model-development team at the GFDL. They serve as a reality check on models and may spur further observations. In the end, however, "you can't end with observations. At the most basic level, you want to say something about the future. And there isn't any way to put these observations together that would give you any detail about the future."
Moreover, Earth has no identical twin nearby undergoing the same basic physical processes but unaffected by human activity. The only place to approximate that "twin" is inside a supercomputer. Thus, "simulation – and not just in climate and weather but in a lot of different fields – has become a third leg, in addition to theory and observation, to help us figure out what's going on," says Brian Gross, the GFDL's deputy director.
The building blocks for many of today's climate models are modules that simulate conditions in the atmosphere, ocean, on land, and around sea ice. Researchers use historical measurements to set the sea level, as well as levels of atmospheric gases, airborne particles, and sunlight for each year they include in the model.
Then they turn the model loose to calculate how wind, temperature, air pressure, and moisture patterns over a particular period will evolve.
In early models, researchers say, large adjustments were needed to keep climate models from spinning off into the twilight zone. The adjustments had no real-world climate counterpart; they were made to keep the simulations plausible. As models have improved, the need for such intervention has receded, and any tweaking has reflected real-world observation.
Such interventions have led some to say that modelers are merely telling the model to yield a specific result. Dr. Winton dismisses that charge. "People overestimate the control we have," he says.
With more powerful computers, scientists have been able to model climate behavior over shorter timespans. The need to intervene in the models is disappearing but not likely to vanish, says Caroline Katsman, a researcher at the Royal Netherlands Meteorological Institute in De Bilt. No computer can crunch numbers for every point on the globe.
One measure of a model's success is how well it captures the main features of natural climate variation. Assuming it can do that, researchers can then use the model to test ideas about atmospheric conditions and their plausible causes.
Last month, for example, researchers at NOAA's Earth Systems Research Laboratory in Boulder, Colo., concluded that slightly more than half the unusual warmth the United States experienced in 2006 was probably due to the buildup of greenhouse gases in the atmosphere.