This week we talk about ENSO, El Niño, and attribution science. We also discuss climate change, natural disasters, and the trade winds. Recommended Book: Titanium Noir by Nick Harkaway Transcript The field of attribution science, sometimes referred to as "extreme event attribution," focuses on figuring out whether and to what degree a particular weather event—especially rare weather disasters—are attributable to climate change. Severe floods and tornadoes and hurricanes all happen from time to time, which is why such events are sometimes referred to as once in a decade or once in a century disasters: the right natural variables align in the right way, and you have a disaster that is rare to the point that it's only likely to happen once every 10 or 100 years, but such rare events still happen, and sometimes more frequently than those numbers would imply; they're not impossible. And they're not necessarily the result of climate change. Folks working in this space, which is a blend of meteorology and the rapidly evolving field of climate science, do their best to figure out what causes what, and how those odds might have been impacted by the shifts we're seeing in global average temperatures in particular, and the knock-on effects of that warming, like shifts in the global water cycle; both of which influence all sorts of other planetary variables. The most common means of achieving this end is to run simulations based on historical climate data and extrapolating those trend-lines forward, allowing for natural variation, but otherwise sticking with the range of normal fluctuations that would have been expected, had we not started to churn so much CO2 and other greenhouse gases into the atmosphere beginning with the industrial revolution. So if we hadn't done the Industrial Revolution the way we did it, what would our global climate and weather systems look like? They have a bunch of models with different assumptions baked into them that they have running, and they can simulate conditions, today, based on those models, and compare them with the reality of how things actually are in the real world, a world in which we did start to burn fossil fuels at a frantic rate, with all the pros and cons of that decision aggregating into our current climactic circumstances. This comparison, between a baseline, non-climate-change-impacted Earth, and what we see happening on real Earth, allows us to gauge the different in likelihoods for various weather systems and increasingly even specific weather events, like massive floods or hurricanes. It also allows us to ascertain what elements of a disaster or system are more or less likely, or the same, compared to that baseline Earth; so maybe we look at a regional heat wave and discover that it was a rare event made more likely by climate change, but that the intensity of the heat wasn't impacted—as was the case with a heat wave in Russia in 2010; climate change made the heat wave more likely, but had such a heat wave occurred, despite its low likelihood, in that non-industrial revolution scenario, the heat would have been roughly the same intensity as it was in real life. Both components of this system, attributing events and patterns to climate change, and confirming that they were not impacted, that they were just run of the mill bad luck, the consequence of natural systems, are arguably important, as while the former provides data for folks wanting to predict future climate change-related outcomes, and provides some degree of ammunition for the argument that climate change is making these sorts of things worse, which helps put a price tag on not moving faster to shift away from fossil fuels, it's also vital that we understand how climate and weather systems work, in general, and that we are able to set proper expectations as to what will change and how, as the atmosphere's composition continues to change, while also understanding what will remain the same, what various regions around