The most definitive scientific assessment of global warming to date, a report released earlier this month from the Intergovernmental Panel on Climate Change (IPCC), concluded with “very high confidence” that humans are contributing significantly to global warming. The report also precisely defines the scientific uncertainties concerning the extent, impacts, and timing of global warming. Ronald Prinn, professor of atmospheric chemistry at MIT and one of the lead authors of the report, says that estimating and understanding these uncertainties is key to evaluating climate data and to deciding on a course of action. Prinn, a leading climate scientist and the director of a worldwide project that carefully monitors the amounts of dozens of greenhouse gases, recently sat down with Technology Review to explain why climate-change science is uncertain, how technology is reducing that uncertainty, and what challenges remain.
Technology Review: What is the IPCC report based on?
Ronald Prinn: The IPCC asked the climate modelers to do two exercises. One, to simulate the climate that we actually have. Here are the greenhouse gases over the last 100 years. Here are the sulfate aerosols that come from coal and actually cool the system. So all of these human influences are prescribed. And then they say run your models and give us your output for global average temperature.
Then they were given a separate exercise: take the [year] 1900 greenhouse-gas levels and keep them constant for the 100 years.
At the global scale, it’s pretty clear that the results from the two exercises, at about 1960, totally diverge. If you look at that and say, Could I explain the observed temperatures with the models that don’t include human-caused increasing greenhouse gases?, the answer is one chance in ten.
TR: This confidence–that there is a 90 percent chance human influences cause global warming–is new to this report. Where does that confidence come from?
RP: It is a combination of growing volume of observations of the planet and various signals of climate change, but [it’s] also a significant component of computer modeling. Just from the observations alone, you can’t answer key questions, so you need to combine observations with computer models of the system.
In the last six years, these climate models have gained in realism; they have improved in their physics, chemistry, and biology. They’ve improved their spatial resolution because computers have gotten faster. There’s better confidence that these models are looking a bit more like the planet we live on. But they’re never going to be to the point of simulating every leaf, and so on.
[It’s also important] that there are now enough climate models being built around the world that different philosophies can be encapsulated in that.
TR: Are there technological advances that have made modeling better?
RP: The fact that computers have been getting faster and faster has been extremely important. For observing greenhouse gases, there have been big strides in the last 10 years, particularly with the introduction of automated mass spectrometers. In the last three or four years, the use of satellite remote sensing using very high-resolution spectra measured from space to deduce trace gas concentrations around the world is growing, although it has not played much of a role to this point. Looking to the future, the use of satellite remote sensing of greenhouse gases is going to certainly grow.
As far as temperature is concerned, the same story is true. We have a ground network. We have a meteorological balloon network. But particularly in the last 20 years, the measurement of temperatures from using infrared and microwave wavelengths from orbiting satellites is getting better and better. It doesn’t give the altitude resolution of a balloon rising through the air. But it gives you global coverage, whereas the previous observing systems were spotty.
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