Pale Blue Dot: Climate policy must take science into account

Environmental activists have struggled with making politicians take climate change seriously for years. Because environmental protection is such a long-term and confusing issue, it is difficult for legislators to formulate policy on, and even more difficult to talk about on the campaign trail — saying that the planet isn’t going to get worse than it already is isn’t quite as exciting as talking about health care or infrastructure reform, which bring about direct, tangible benefits.

But the one thing that has proven to convince politicians (other than locking them in a room and forcing them to watch “An Inconvenient Truth”) is money. That’s not an anti-politics quip — politicians and government agencies tend to base their decisions on the possible economic impact of climate change. Moreover, these economic impacts are calculated by environmental algorithms that are painfully in need of an update.

Policymakers rely on climate-economic models to estimate the monetary damage a change in global temperature would cause, and how much changes in environmental policy would cost.

Global climate models are essentially giant algorithms, like the ones used to predict weather, but on a much larger scale. They simulate the atmosphere, oceans, ice and land for the whole planet, and can run through various scenarios while also computing economic outputs. These models are typically run on tennis court-sized supercomputers and have enough code to fill 18,000 pages of printed text.

Yet, the models that governments tend to favor are flawed. Their projections of the economic impacts of climate change do not match up with the current state of physical science. For instance, physical scientists predict that a 6-degree Celsius rise in global temperature would cause the planet to be unlivable, causing forests to grow on the poles, deserts to form in Europe and ocean levels to wipe out coastal cities — not to mention kill off most species and launch the planet back into the Eocene age. In contrast, the Dynamic Integrated Climate-Economy model, a favored alternative, predicts that the same rise in temperature would only result in a 10 percent drop in global GDP.

It seems hard to believe that a change in climate that could cause mass migration, a global fight for resources and the obliteration of major cities would only dent the global economy by 10 percent. While that is an extreme example (if climate experts are successful, the world can corral its temperature rise around 3 degrees), it reveals the major pitfalls of using economic impact as a reliable metric for environmental policy.

If tools are solely being used for cost-benefit analysis of climate policy, we are unlikely to ever convince politicians to take firm action against climate change. Where we may see a tropical hellscape to rival Jurassic Park, they might only see a modest decline in economic outcomes.

These models may not be built to make projections so grand, but as they are currently being used, they allow policymakers to remain blissfully ignorant about the true costs of climate change. Furthermore, they give credence to “lukewarmers” — people who do not deny that human activity is causing climate change, but insist that climate change would not affect the planet that much.

A new paper by former Environmental Protection Agency staffer and current Smith College professor Alexander Barron lays out some specific changes that could be made to the small group of climate models that set expectations and policy in the United States. Folks at the EPA would be wise to read it, even though they are currently too busy buying mattresses and Greek yogurt for Scott Pruitt.

Barron advocates for an update of the technology cost data in the models, which does not account for the current success of renewable and electric energy sources due to the glacial pace of academic research. He also recommends adding factors for the global health costs of pollution and climate change, which are not currently included in any of the models. Even these two changes could close some of the blind spots in climate policy.

The faults of global climate models are prime examples of why policy change must come from all areas, including the very algorithms we use to evaluate climate change. Updating the tools that we use to estimate and prepare for climate change is a key step in convincing politicians that the earth as we know it is worth saving, even if it means sacrificing aspects of our current quality of life. Though policymakers should be convinced simply by the specter of global climate change, we live in a world that requires hard evidence in dollars and cents; therefore, we must also tackle the issue from that end through a reform of climate-economic models.

Kylie Harrington is a junior majoring in journalism. Her column,“Pale Blue Dot,” runs Wednesdays.