Which came first, the warmer temperatures or the clearer skies?
Answers to that and similar "chicken or egg" type questions could have a significant impact on our understanding of both the climate system and manmade global warming.
In an invited talk the week of December 14 at the American Geophysical Union's fall meeting, Dr. Roy Spencer from The University of Alabama in Huntsville discussed the challenge of answering questions about cause and effect (also known as forcing and feedback) in the climate.
"Feedbacks will determine whether the manmade portion of global warming ends up being catastrophic or barely measurable," Spencer said recently.
Spencer's interest is in using satellite data and a simple climate model to test the simulated feedback processes contained in climate models that are used to forecast global warming.
"I am arguing that we can't measure feedbacks the way people have been trying to do it," he said. "The climate modelers see from satellite data that warm years have fewer clouds, then assume that the warmth caused the clouds to dissipate. If this is true, it would be positive feedback and could lead to strong global warming. This is the way their models are programmed to behave.
"My question to them was, 'How do you know it wasn't fewer clouds that caused the warm years, rather than the other way around?' It turns out they didn't know. They couldn't answer that question."
One problem is the simplicity of the climate models. Because cloud systems are so complex and so poorly understood, all of the climate models used by the United Nations' Intergovernmental Panel on Climate Change use greatly simplified cloud parameters to represent clouds. But the calculations that set those parameters are based on assumed cause-and-effect relationships.
Those assumptions might be working in the wrong direction, Spencer said. "What we have found is that cloud cover variations causing temperature changes dominate the satellite record, and give the illusion of positive feedback."
Using satellite observations interpreted with a simple model, Spencer's data support negative feedback (or cooling) better than they support positive feedback.
"This critical component in global warming theory - cloud feedback - is impossible to measure directly in the real climate system," Spencer said. "We haven't figured out a good way to separate cause and effect, so we can't measure cloud feedback directly. And if we don't know what the feedbacks are, we are just guessing at how much impact humans will have on climate change.
"I'm trying to spread the word: Let's go back to basics and look at what we can and cannot do with measurements of the real climate system to validate both climate models and their predictions."
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