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The headlines are bleak: Regions of our planet becoming uninhabitably hot (1), crippling droughts, wildfires, and floods, collapsing ecosystems. Extreme climate change, models suggest, is likely if nations continue to increase emissions at close to their current rate, with global average temperature rises of at least 1.1 to 3.1 °C by 2100. Such warming is probably enough to trigger planetary tipping points, says Gavin Schmidt, director of the NASA Goddard Institute for Space Studies in New York, NY. “We may hit a threshold even with [low emissions],” Schmidt says. “We are at the top of the [ski] mountain and there’s only black runs. And we’ve got to hope the one that we choose is not the one with the double-black diamond moguls that only a true expert can maneuver.” These projections stem in part from something called integrated assessment models (IAMs). The “process-based” versions of these models are mathematical representations of the world, with modules representing the climate, biosphere, energy, and economy. They’re a popular and extremely important tool, but one that isn’t always well understood. Better explicating their strengths and shortcomings will help refine projections and improve transparency in the years ahead. The conundrum posed by climate change is that policymakers need to act immediately to avoid warming decades hence. IAMs help them to envisage the desired future and the impacts of climate policies. For example, researchers might specify an emissions target and then use an IAM to work out what policies and technologies might be the most cost-effective way to

Integrated assessment climate policy models have proven useful, with caveats