“IFAR” isn’t a typo. It’s a tool used by climate scientists (or scientivists as they are sometimes called, merging “scientist” with “activist” in name as so many do in practice) to measure the costs from extreme weather events that can be attributed to your gas stove, i.e. greenhouse gas emissions. “FAR” stands for “Fraction of Attributable Risk”, as in attributable to anthropogenic climate change, and “I” stands for Impact, as in the costs of an extreme weather event like a flood or a hurricane. Multiply the two together, the argument goes, and you get the dollar value of the damage done by CO2 emissions. Do people actually do these calculations and present them as solid even to several decimal places? Why yes. Indeed IFAR calculations are very popular among scientivists and are speeding like a hurricane to a courtroom near you. But now a courageous young climatologist has told his colleagues they’ve gone too IFAR. The method is flawed and, surprise surprise, grossly exaggerates the value of extreme weather events attributable to greenhouse gases.

The scientist in question is none other than Patrick Brown, a climatologist who teaches at Johns Hopkins and works at the Breakthrough Institute and who recently penned a confessional essay admitting that he had to distort his findings in the alarmist direction in order to get them published in a top science journal. In the case of his new IFAR paper, published in the journal Climatic Change, it seems he didn’t have to twist his own findings because they come through loud and clear.

Brown argues through a series of examples that the IFAR method assumes a binary world where extreme weather events either happen or don’t happen and if they do they're always the same size. Thus if its practitioners calculate that a storm was made twice as likely due to climate change, so the “FAR” is 0.5, and does a billion dollars in damages, so the “I” is $1 billion, they multiply I times FAR and get half a billion dollars of damage due to greenhouse gases. But Brown says this binary assumption about weather events is wrong if “the weather or climate phenomena in question are on a continuum”. Thus windstorms, for instance, do not either have no wind or a ferocious gale; they range from a light wind to a stiff one to a howling one to a hurricane, with the vast majority never being catalogued but being there anyway.

So if climate change makes weather worse, you’re far more likely to get most of them having slightly stronger wind. And those that cross the definition threshold from, say, a tropical storm to a hurricane or from a Category 3 to a Category 4 hurricane are not conjured up from nothing, they are just made worse. So saying there was a “FAR” of 0.5 that a Category 4 hurricane would occur because of climate change doesn’t mean without climate change there’d have been a gentle breeze. It means there’d have been a formidable Category 3.

By making the contrary oversimplifying assumption, Brown says, “the IFAR calculation inflates the impacts associated with ACC [anthropogenic climate change] in these circumstances because it inaccurately assumes that there would have been zero impact had the geophysical value chosen to define eventhood not been exceeded”. And the proper calculation would be of the difference between the more serious damage actually inflicted by, in our example, having two Category 4 hurricanes because of climate change and the damage that would have been done by one Category 4 and one Category 3 without climate change. And that kind of calculation, Brown shows, yields much smaller numbers than the IFAR method.

Of course any such calculation requires models and guesses and extrapolations to construct an artificial alternative world without greenhouse gases, so there are no guarantees the revised method is correct either, in all sorts of ways.

For instance, why is it always assumed that CO2 makes the weather worse every time? What if anthropogenic climate change created conditions in which a terrible storm that would have happened dissipates instead and we get a week of pleasant warm conditions? Then we should get credit for our carbon emissions, but no one ever does those calculations. And who, indeed, can say that a storm that didn’t happen would have if it were 1.1°C warmer than it is? But by the same token, who can say that a storm that did happen wouldn’t have if it were 1.1°C cooler? It’s a classic case of a hypothesis that cannot be tested, and real science doesn’t have time for those.

Still, we’re grateful to Brown for correcting the faulty logic of the climate ambulance-chasers. And if he believes in this kind of modeling we hope that he will expand his analysis to include not just the bad weather events that happened due to CO2, but the bad ones that didn’t happen due to CO2. After all, it’s only IFAR to look at both sides.