Here at the Earth Observatory we know as well as anybody that explaining the nuance and complexity of climate modeling isn’t easy.
In May, Nature Climate Change published a study pointing out that the number of news articles that mention climate change has been declining since 2007. There was a slight increase in mentions following the “Climategate” scandal in 2009, but the number has fallen rapidly since then (see the dashed line below).
Climate models are especially unpopular. Just a tiny fraction of the articles about climate science mention models (see the solid black line in the graph above). And, among the influential newspapers, that number is declining (see graph below).
When climate models do appear in the news, they’re often flagged as inaccurate, and political opinion outlets — rather than news outlets — account for a surprisingly large percentage of the mentions. Twice as many of the media outlets that mentioned climate models did so in a negative rather than a positive light, the study found. Political commentary outlets — The Rush Limbaugh Show, The Nation and The National Review — had the highest frequency of negative content about climate models, but a variety of other news outlets had ample negative content about models as well.
That’s surprising given the central role that modeling has played in revealing key aspects of climate science and in how the Earth works at a basic level. If you attend a scientific meeting these days, you’ll find there are few Earth science topics that don’t involve some sort of modeling. Want to know, for example, whether the plume from the huge fire burning in New Mexico is going to blow into Albuquerque? You need a model. Whether that hurricane brewing in the Gulf of Mexico will be coming to your city? You need a model. Whether there’s enough groundwater for your soybean crop to thrive? Again, you might well get your answer from a model. See the video below to see how researchers are predicting the severity of the Amazon fire season months in advance with the help of models.
Most earth science models, it’s worth noting, base their output on huge amounts of real observations; scientific modelers are not just pulling numbers from thin air. One model based at Goddard called the Modern Era Retrospective-analysis for Research and Applications (MERRA), for example, has ingested more than 50 billion satellite observations made since NASA launched the Terra satellite — and a new era of Earth observations — in 1999. Another model called GEOS-5, one of the highest-resolution models, also ingests huge amounts of data from the real world. GEOS-5 simulated the massive winter storm that struck the eastern United States in 2010 with remarkable accuracy.
Models are not just for earth science. The same sort of complex, numerical models are used all over the sciences. Alfio Quarteroni, a professor of mathematics at a university in Switzerland, laid out a few of them in an article in Notices of the Mathematical Society in 2009.
Aerospace engineers, he points out, use numerical models of fluid dynamics to make wingtips and fuselages more aerodynamic. Likewise, cardiovascular researchers take advantage of similar models to calculate how quickly blood flows through key arteries and how much stress the flow puts on artery walls as they narrow. Quarteroni has even used fluid dynamics models to try to figure out the best way to sail in different wind conditions.
Atmospheric scientists would be the first to point out that climate models aren’t always perfect. But as NASA modeler Gavin Schmidt pointed out in this Physics World article (which is worth the read if you want to understand what climate models can and can’t do), that lack of perfection doesn’t mean they’re not useful.