The latest reports to come out estimated that 2010 carbon emissions exceeded the 2007 International Panel on Climate Change’s worst case projection. China beat out America as the world’s biggest emitter of fossil fuel carbon. These statements paint a pretty grim picture of humans ability to achieve goals we make as well as our future survival here on earth.
However, scientists have made gloomy predictions before with very little to show for it. For example, a famous research paper by Peter Cox back in 2000 claimed that by 2050 all the Amazon would be destroyed and replaced with savanna shrubs and grassland, basically destroying both the carbon and water cycles as we know them. Cited in more than 1,000 other research papers, Cox’ paper definitely shook the world from the scientists to the politicians.
Yet other scientists found fault with the model Cox chose (including Cox himself), and that glitch gave way to politicians and global climate change naysayers saying, “See, told you so. Even the scientists can’t agree. Therefore, climate change isn’t real.”
Yes, the Hadley model was not the most precise, in fact, none of the models humans have ever produced ever are. Data have errors. Yet does that mean scientists should just throw in the towel, policy makers should throw their hands in the air, and citizens need to give up the idea that either climate change doesn’t exist or, if it does, we can do nothing to stop the impending doom that faces us?
No. First, scientists do agree on the fact that carbon dioxide is a greenhouse gas; greenhouse gases are increasing in the atmosphere; and we humans are contributing a chunk of greenhouse gases to the air through the burning of fossil fuels and other landuse changes. What scientists do not know 100% is what kind of feedback those certainties create, i.e. if the Amazon is going down quickly or exactly how U.S. heartland crops are affected.
“What we need to keep in mind is that data have errors, and errors are not necessarily bad,” says Lucy Hutyra, scientist and professor at Boston University. “What is bad is ignoring those errors. We need to be honest about them and explain them when showing our research.” Scientists need to be ready to explain the errors in their data and the level of uncertainty in the models.
And journalists need to be ready to explain the greater implications of the scientists’ research to the public. That’s where I come in, where my colleagues, my professors, my employers, where all of us translators come in. We have a duty, just as the scientists do, to inform our public of every angle and its meaning and not paint the entire collection of research with one bold stroke. No more x causes y, this means that, we are here now statements. The public is sick of that. Journalism and science are about truth and information. Now, more than ever, let’s remember that.